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THE JOURNAL OF DEVELOPMENTAL AND LEARNING DISORDERS
2003
Volume 7
CONTENTS
The Origin of Language: Evidence from Longitudinal Research in AutismMichael Siller & Marian Sigman Is One Style of Early Behavioral Treatment for Autism ' Scientifically Proven?'Morton Ann Gernsbacher Disorders of Speech Sound Perception in Children with Asperger Syndrome Dana Boatman , Ph. , CCC-
Executive Function Deficits in Children with Autism- Ellen Simon B. Sherry, Stuart Shanker , Judith Codd
Bialystok
Neuropathology and Alterations in the GABAergic System in AutismGene J. Blatt , Ph. The Trimodal Brain and reading I: A new synthesis and some predictionsJudith L. Lauter, Ph. The Trimodal Brain and reading II: Preliminary data on the co-occurrence of problems in phonemic awareness and eye-movement coordinationJudith L. Lauter, Ph. D. & P. Frank McKane Ph. Technology s Role in Encouraging Social and Cognitive Development in
Children with Autism- Daniel R. Gillette, Ed. Perceiving Speech by Ear and Eye: Multimodal Integration by Children with Autism- Dominic W. Massaro , Ph. D. and Alexis Bosseler Book Review: You re Going to Love this Kid!: Teaching Students with Autism in the Inclusive Classroom- Robert A. Naseef , Ph.
www.icdl.com Bethesda , Maryland
ICDL
Copyright
cg 2002
ISBN: 0- 9728925-
111
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The Journal of Developmental and Learnin Disorders Editor Stanley I. Greenspan , M. D. George Washington University
Associate Editor Serena Wieder, Ph. D. Assistant Editor
Georgia DeGangi , Ph. Treatment and Learning Center
Administrative Editor Jo Raphael , M.
Editorial Board Margaret Bauman , M.
Toby Long, Ph.
Harvard University
Georgetown University
Harry Chugani , M. Wayne State University
Stephen W. Porges, Ph.D. University of Maryland
Leon Cytryn , M.
Barry Prizant , Ph.D. , C.
George Washington University
Brown University
Sima Gerber,
Ricki G. Robinson , M. , Ph. D. University of Southern California
Ph.
Queens College
, P.
Rebecca Shahmoon Shanok , M. SW. , Ph. Child Development Center, New York
Arnold P. Gold, M.
Columbia University
Myron Hofer, M. Columbia University
Milton Shore, Ph.
Pnina Klein , Ph. Bar- llan University,
Richard Solomon , M. University of Michigan
Pat Lindamood, M.
Catholic University
Israel
, C.
Lindamood- Bell Learning Processes
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Page 1
THE ORIGIN OF LANGUAGE: Evidence from Longitudinal Research in Autism
Michael Siller , M.
Abstract.
, and Marian Sigman , Ph.
Long before children acquire an understanding of the semantic and syntactic char-
acteristics of spoken language, children have already developed a vast knowledge about the prag-
matics of human communication. To a large extent, this knowledge develops during preverbal interactions between the infants and their parents. Emphasizing the continuity between preverbal and verbal communication is of great intuitive appeal; however, it has proven difcult to emPirically validate specifc links between the infants ' preverbal experiences and the subsequent origin of spoken language. The findings reviewed in this paper provide such a specifc link. During the second half of the first year, tyPically develoPing infants and their parents start to collaborate in establishing a shared interest in the world around them. Our findings suggest that, at least in the case of autism, the success of the parent- child dyad in managing such a shared interest in external objects or events is developmentally linked to children s long- term language outcomes.
Learning a native language is an accomplishment that is within the grasp of most toddlers. Yet, as Jerome Bruner and Virginia Sherwood put it discovering how children do it has eluded generations of philosophers "
(Bruner & Sherwood , 1983 , p. 41). stretching historically from St. Augustine to traditional learning theory, made us believe that language acquisition is essentially a process of forming associations between words on the one hand and agents , actions , and objects on the other (O' Connell , 1969; Skinner , 1957). The limitations of this associationist view
Early accounts ,
became obvious in the late 1950s , particularly in the work of Noam Chomsky (Chomsky, 1957). Chomsky s insight was that the process of language acquisition is
far more complex than connecting words with meaning. Children also acquire a grammar - an underlying system of rules enabling them to generate an infinite number of new sentences. Importantly, in shifting the emphasis from word learning to
, traditional principles of associative learning suddenly appeared il equipped to explain children s growth in language. It seemed unreasonable to assume that children could learn about the underlying structure of language just by imitating their elders and exposure to systematic reinforcement. Given the constrained view on learning predominant at the time , Chomsky took his argument as far as to question the learnability of language altogether. He argued that all human rule acquisition
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languages share a common set of syntactic rules - these rules are part of children innate endowment , ready to be recognized as soon as children are exposed to their native languages. It wasn t until the early 1980s that Bruner pointed out that parents participate in language learning in a manner far beyond serving either as a model to imitate or as a source of reinforcement (Bruner , 1981; Bruner & Sherwood , 1983). From early on , mother and child develop conventions for carrying out joint tasks. It is the structure inherent in these joint tasks that may shape children s learning about the structure underlying spoken language. Bruner s proposal of developmental continuity between preverbal and verbal exchanges was sparked by John Austin s insight that, even when mature language is considered , word meaning and grammar are insufficient to convey a speaker s communicative intent (Austin , 1962). Bruner provides the example of a trivial question that is being asked at a dinner party: " Would you be so kind as to pass the salt?" Very likely, the listener wil interpret this question as a polite request for the salt rather than an inquiry concerning his or her perceived kindness. This interpretation is possible a) because of the listener s familiarity with the communicative context , and b) because the listener shares some of the speaker s notions about intentions. For developmental psychologists , this characterization of mature language use is intriguing
because it points in the direction where continuity may be found between preverbal and verbal exchanges. Long before children appreciate the semantic and syntactic characteristics of spoken language , they already have acquired a rich body of knowl-
edge about the context in which communication takes place as well as intentional states that motivate people to communicate. This knowledge may serve as a " matrix into which syntactic and semantic achievements can be set" (Bruner , 1981 , p.l59). To a large extent, Bruner s empirical work on the origin of language was concerned with describing and characterizing the early social experiences of infants. Based on a number of extensive longitudinal single case studies , Bruner emphasized that the communicative life of preverbal infants is limited to a rather small number of familiar interactive routines (Bruner & Sherwood , 1983; Ninio & Bruner , 1978; Ratner & Bruner , 1978). In his view , these familiar routines provide the infant with the experiences necessary to interpret the communicative intentions of other people: Infants and their mothers develop and conventionalize the rule structure governing the exchange , infants learn to make their intentions plain , and mothers learn to interpret the intentions of their children. Moreover , Bruner argues that the vast majority
of early mother- infant exchanges are governed by three basic communicative intentions: affiliating, requesting, and sharing. During the first six months of life , most social encounters between mother and infant are aimed at establishing affiliation. Initially, interactions are concerned with the mutual adaptation between the infant's cycling physiological needs and the mother s attempts to anticipate and fulfill these needs. For example , studying early feeding interactions , Kenneth Kaye was able to show that even during the first two weeks of life mothers and infants learn to read each other s signals and to anticipate one another s behaviors (Kaye , 1977 , 1982). As infants achieve control over their own gaze during the second month (Bronson , 1974), the face- to- face encounter becomes
, &
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the primary context for social interaction. But again ,
interactions are directed
towards establishing affiliation: Mothers and infants learn to regulate eye contact and arousal , to share each other s emotions , and to respond to each other s facial cues (Brazelton , Koslowski , & Main , 1974; Cohn & Tronick , 1988; Kaye & Fogel , 1980; Stern , 1974). As infants move through the second half of the first year , mothers and infants increasingly communicate
about
objects and events outside the dyad (e. g.
toys or
food). In managing such a triadic setting, involving mother , infant , and a toy, two communicative intentions become visible. First , mother and infant develop interactive routines aimed at regulating each other s object directed behaviors. Initially, these routines have the exchange of objects as their common theme. The infants
learn to request objects being held by their mothers and also to return them when being prompted to do so. Later , the interactive routines increase in sophistication now being directed at obtaining help in carrying out one s own goal directed actions (e. g.
blowing
up
a balloon). The second communicative intention emerging during
the second half of the first year is directed towards achieving and maintaining a shared interest in surrounding objects and events. That is , mothers and infants develop interactive routines concerned with directing and following each other attention. Here, communication is not instrumental in the sense that it is intended to obtain objects or services from another person. Rather , it serves the sole purpose of recruiting another person s attention to objects , states , and topics that are at the center of one s own attention. Empirical evidence linking infants ' experiences within these early interactive rou-
s subsequent rate of language acquisition has been scarce. Rare exceptions are a number of longitudinal studies that demonstrate the predictive significance of the dyad' s success in managing a shared interest in surrounding objects tines to children
or events. In several longitudinal studies on play interactions between 9 to 15 month old infants and their mothers , Melinda Carpenter , Michael Tomasello , and colleagues have demonstrated that infants who spent more time in a state of shared toyengagement with their mothers subsequently developed language at a faster rate than infants who spent less time in shared toy- engagement with their mothers initially (Carpenter , Nagell , & Tomasello , 1998; Tomasello , MannIe , & Kruger , 1986; Tomasello & Todd , 1983). In addition , researchers have also studied the individual
contributions of mothers and infants in establishing such a shared interest in the external world. Focusing on the parents ' interactive behaviors , several longitudinal studies have shown that the tendency to describe objects or events occupying their children s current focus of attention reliably predicted the rate of children s subsequent language learning. (Akhtar , Dunham , & Dunham , 1991; Bornstein & TamisLeMonda , 1989; Dunham & Dunham , 1992; Smith , Adamson , & Bakeman , 1988; Tamis- LeMonda , Bornstein , & Baumwell , 2001; Tamis- LeMonda , Bornstein Damast, 1996; Tomasello & Farrar , 1986). Similarly, with respect to the infants ' early communication skils , Jessica Markus and colleagues have shown that the twelve month olds ' capacity to follow another person s pointing gesture to an interesting
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object or event is a reliable precursor of children s subsequent language developMundy, Morales , Delgado , & Yale , 2000). Taken together , these
ment. (Markus ,
empirical studies suggest that episodes of shared interest between parent and infant provide a unique context for children s emerging language skils. They also provide
some insight as to which behaviors of parents and infants are key in managing such encounters. That is , both the parents ' responsiveness to the infants ' focus of attention and the infant's responsiveness to the parents ' bid for joint attention were shown to be linked to children s subsequent growth in spoken language.
Managng a shared interest in typical development In the late 1920s ,
Lev Semonovich Vygotsky argued that the origin of new skils
is typically embedded in social situations where children are prompted or scaffolded by an expert , for example a parent (Cole , John- Steiner , Scribner , & Souberman 1978). During recent decades , a variety of authors includingJerome Bruner , Kenneth Kaye , Roger Bakeman , and Lauren Adamson have used Vygotsky s framework to
conceptualize infants ' emerging abilities to actively manage social encounters with their parents (Bakeman & Adamson , 1984; Bruner , 1981; Kaye , 1982). The authors
argue that initially the roles of managing shared and reciprocal interactions are not distributed evenly between infants and parents. At first, it is the primary responsibility of the parents to respond to the infants ' built in rhythms and contingencies , to interpret and complete their intentions , to imitate certain aspects of their behavior and to be responsive to their actions. Only gradually, as the infants develop the skils necessary to playa more active role in managing the social encounter , parents relinquish increasing amounts of responsibility to their children. A similar framework has been applied specifically to describe the infants ' emerging ability to manage a shared interest in surrounding objects or events. Since infants achieve control over their own gaze during the second month , the predominant context for social interaction with their parents is the face- to- face encounter. This changes around five months of age as infants increasingly develop an interest in the world of objects. Initially, however , infants stil lack the social understanding necessary to coordinate their interest in objects with their interest in people. " Objects are perceived and used , and persons are communicated with-but these two kinds of intention are expressed separately " (Trevarthen & Hubley, 1978 , p. 184). During these early stages of development, parents carry a large share of responsibility to assure that a shared interest in an object or event is established. In a variety of studies , researchers have documented the parental eagerness to convert the single object orientation of their infants into a social situation. The predominant strategy used to do so is to join the infants ' spontaneous interest in an object , and to provide them with a simultaneous vocal or gestural commentary (Collis & Schaffer , 1975; Newson , 1978). In providing
such a commentary, mothers and infants were described to develop games where a certain object- directed
behavior of the infant ' causes ' an effect in the expressive body
parts of the mother (hands , face , voice). Based on longitudinal observations of a sin-
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gle mother- infant dyad , Trevarthen & Hubley (1977) described that it was in the context of such a game that the infant for the first time attended to the mother s face while playing with an object. Using a larger longitudinal sample of 28 mother- infant dyads Bakeman and Adamson were able to provide further documentation of this maternal tendency to tune into the infants ' ongoing engagement with objects (Adamson & Bakeman , 1984 , 1985; Bakeman & Adamson , 1984 , 1986). Importantly, even though at first infants may show no explicit acknowledgement of their mothers ' attempt to join their ongoing toy engagement (for example by alternating their gaze between the toy and their mothers ' face), findings from this longitudinal study suggest that these episodes of supported joint engagement provide an important context for the infants social learning. First, the authors reported that the infants ' earliest referential gestures (e. g. pointing) emerged in situations where parents had tuned into their infants ongo-
ing engagement with a toy. Second , Bakeman and Adamson were able to show that episodes characterized by a shared interest in an object are generally accompanied by elevated levels of affective involvement on behalf of the infant. Similar levels of affec-
tive involvement are rarely observed when children played with the toys on their own. Interestingly, infants showed the same elevated levels of affective involvement during joint engagement, independently of whether they explicitly acknowledged their mothers ' presence or not. In summary, by joining the infants ' ongoing toy engagement , parents assure the infants ' participation in social encounters that involve a shared interest in an object or event. Frequent participation in such encounters provides the infant with the expe-
riences necessary to acquire the social skils needed to playa
more
active role in
managing such encounters. Around nine months of age , a range of such social behaviors emerge in the behavioral repertoire of typically developing infants: infants start
to follow their mothers ' gaze direction and pointing gesture in order to determine the target of mom s interest, infants alternate their gaze between an interesting object or event and their mothers ' face in order to check ' if she also sees , and they start to
point to and show objects in order to capture their mother s interest. This group of behaviors is frequently referred to as joint attention behaviors (Tomasello , 1999; Tomasello , Kruger , & Ratner , 1999).
Managng a shared interest in autism Children with autism show a specific and unique deficit in behaviors used to establish and maintain a shared interest with other people. In two previous studies conducted in our lab , we compared the nonverbal communication skils of children with autism to language matched controls of typically developing children , children with Down syndrome , and a heterogeneous group of children with developmental delay (Mundy, Sigman , Ungerer , & Sherman , 1986; Sigman & Ruskin , 1999). In these studies , nonverbal communication skils were assessed using a procedure called the Early Social Communication Scales (ESCS , Mundy, Hogan , & Doehring, 1996; Seibert , Hogan , & Mundy, 1982). In this procedure the child and the tester sit facing
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each other at a small table. A set of toys is in view but out of reach of the child. The tester presents a variety of toys and plays a series of games aimed at eliciting requesting, sharing, and affiliating behaviors. In addition , on several trials , the tester points to the left, right , and behind the child to evaluate whether the child follows the experimenter s bids by turning his or her head in the designated direction. The procedure is videotaped and coded for the frequency of specific social behaviors. These behaviors fall into five mutually exclusive categories: a) initiates social interaction (affliation): g. initiates a turn taking game by rolling a ball towards the experimenter; b)
responds
g. establishes eye contact with an adult during a pause in a face- to- face game , or returns the ball to the experimenter during a turn taking game; c) initiates joint attention: (sharing): g. alternates gaze between an to bids for social interaction (affliation):
active mechanical toy and the experimenter s face , establishes eye contact while examining a toy, points to toys within reach , or shows an object to the experimenter; d) responds to bids ftr joint attention (sharing): g. follows the experimenter s pointing gesture towards a poster on the wall; e)
initiates behavior regulation (requesting):
reaches towards a toy that is out of reach , establishes eye contact with the experimenter when a mechanical toy ceases , or points to a toy out of reach. Interrater reliability for this scale has been established multiple times and mean generalizability coefficients are at about . 80. Findings from this research suggest that children with autism show deficits across a range of joint attention behaviors. As compared to language matched controls , children with autism were less likely to respond to the experimenter s pointing gesture; they were less likely to initiate joint attention by alternating gaze between a toy and the experimenter s eyes; and they were less likely to initiate a shared interest by pointing at a toy or by showing a toy to the experimenter or a parent. In contrast, a mixed picture of deficits and strengths emerged with respect to requesting and social interaction (affiliating) behaviors. Although children with autism were found to initiate social interaction less than children with Down syndrome , no group differences were found between children with autism , typically developing children , and chil-
dren with heterogeneous developmental delay. Similarly, children with autism did not differ from matched controls in their responsiveness to social interaction. Finally, with respect to requesting behaviors , we found that typically developing children showed on average more requesting behaviors than any of the other three groups. In turn , a deficit in requesting behaviors is characteristic not only for children with
autism but also for children with other developmental delays. However , we also found evidence that the deficit in requesting behaviors is somewhat more profound in children with autism than it is in children with heterogeneous developmental delays.
In reviewing the literature on typically developing infants , we emphasized that a shared interest between parent and infant emerges based on contributions from both partners. We also emphasized that especially during early stages of development the responsibilities for assuring a shared interest are not distributed evenly between parent and infant. Early in development, when infants stil lack the skils necessary to play an active role in managing a shared interest in an object , parents respond to the
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infants ' limitations by adopting a tendency to tune into their children s ongoing toy engagement. Given that children with autism also lack the skils necessary to manage a shared interest with their parents , the question arises , how do parents of children with autism cope with their children s behavioral limitations? The few studies that have compared the interactive behaviors of parents of children with autism to the behaviors of parents of typically developing children have
documented that parents of children with autism tend to be more directive and demanding (Kasari , Sigman , Mundy, & Yirmiya , 1988; Watson , 1998). That is , they tend to initiate more activities , show more physical prompts , and use more redirecting utterances. Similar findings are also often reported when behaviors of parents of developmentally delayed children are compared to parents of typically developing children (Cunningham , Reuler , Blackwell , & Deck , 1981; Eheart , 1982;Jones , 1977).
At this point , very little is known as to why parents cope with the behaviorallimitations of young children with autism by assuming a more directive role during play interactions. Part of the reason may be that the spontaneous play behaviors of young children with autism are often rather narrow in content, involve many repetitions , and lack functional or symbolic play acts. In communicating clear expectations about what the child should do and how the child should do it, parents may try to advance their children s object directed play behaviors. Despite the good reasons that parents may have for assuming a more directive and demanding role during interactions , such interactive behaviors may compromise an important goal of parent- child
interaction:
the mutual managing of a shared interest in surrounding objects or events. As emphasized above , parents of typically developing infants initially assure a shared interest by joining the infants ' spontaneous object engagement. They do so , even though at first the infant might not even acknowledge the parent's involvement. It might be that the emerging social understanding and language development of young children with autism would benefit from the same kinds of interactive experiences.
Longitudinal prediction of language outcomes in autism The following discussion wil be based on data from an ongoing long- term longitudinal study conducted in our lab. During the late 1970s and early 1980s , we recruited a sample of 70 preschoolers with autism (mean chronological age = 3 years
11 months). Subjects were then followed up, once during mid- childhood (N = 51; mean chronological age = 12 years 10 months), and once again during early adulthood. Data from the early adulthood follow-up are stil in the process of analysis. For this reason , findings from this second follow- up wil only be reported for a sub- sample of 19 early adults (mean chronological age = 20 years 3 month), and only as part of a longitudinal follow-up for a sub- study on early mother- child play interaction.
The initial diagnosis of each child was made independently of the research by a group of clinicians experienced in the evaluation of developmental disorders using DSM III (American Psychiatric Association , 1980) criteria. Initial clinical diagnoses were supplemented with diagnoses based on two other sources , a videotaped inter-
,&
."'
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action scored with the Childhood Autism Rating Scale (CARS , Schopler , Reichler Renner , 1986), and an interview during which the Autism Behavior Checklist (ABC Krug, Arick , & Almond , 1980) was administered to the parents. As part of the followup assessments , the diagnoses were confirmed using the Autism Diagnostic Interview- Revised (ADI- , Ie Couteur , Rutter , Lord , & Rios , 1989; Catherine Lord Rutter, & Le Couteur , 1994). At each assessment point, a standardized language test was administered. The language measures used were either the Reynell Developmental Language Scales (Reynell , 1977) or the Childhood Evaluation of Language Fundamentals- Revised (CELF- , Semel , Wiig, & Secord , 1987), depending on children s skilleve1. Both measures provide age equivalence scores for children s language abilities. Figure 1 displays the individual language profiles of the participants in our study as a function of chronological age. Only data from the initial and mid- school follow10
9 8 7 -
6 5 -
4 3 2 -
Chronological Age (in years) FIGURE 1. Individual language profiles of the participants as a function of chronological age.
1 In two
cases , language skils during early adulthood were assessed using the Mullen Scales of Early 1995) or the Childhood Evaluation of Language Fundamentals- Preschool (CELFPreschool , Wiig, Secord , & Semel , 1992).
Learning (Mullen ,
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up are included in this graph. As expected , when compared to typically developing children , most children in our sample developed language late and at significantly slower rates (Ie Couteur et al. , 1989; C. Lord & Rhea, 1997). What is more curious is the finding that although most children were largely nonverbal when assessed during preschool , some of them went on to develop language later on , while others were stil considered nonverbal when assessed during mid- school or early adulthood. A central aim guiding our research was to learn more about the characteristics of pre-
verbal preschoolers with autism who go on to acquire language. Particularly, we aimed to find out what sets these children apart from preschoolers who don t show this subsequent growth in language skils. According to a commonly held belief concerning preschoolers with autism , language abilities (e. g. presence of communicative speech before the age of 5) as well overall intellectual level are the strongest predictors of long- term outcome (American Psychiatric Association , 1994). The predictive relation between initial language skils and language outcomes was supported by our findings. Controlling for variations in r(39)= chronological age , we found a statistically significant correlation of between preschool and mid- school language scores. With respect to children with autism who were stil nonverbal at age 4 , findings from our longitudinal study suggested that initial assessments of intelligence did not differentiate the children who later acquired language from those who did not. In turn , preschool measures of intelligence did not add any predictive value above and beyond what was predicted by individual differences in language abilities. The size of the correlations reported above suggests that about one- third of the variance in the outcome language scores was explained by variations in initial language abilities. This seems substantial , but it also leaves room for other variables to operate. As argued above , theories on typically developing children emphasize the continuity between children s preverbal social experiences and the subsequent origin of spoken language. Particularly, the success of the mother- infant dyad in establishing a shared interest in surrounding objects and events has been repeatedly linked to children s subsequent rate of language development. In the case of autism , we have argued that the mother- child dyad may face unique challenges in managing such a shared interest. Based on this reasoning, we developed two hypotheses. First , we expected that preschoolers with autism who demonstrate better joint attention skils wil develop superior language skils until mid- school as compared to preschoolers who have less joint attention skils initially. Second , we expected that parents who are more responsive to children s focus of attention and ongoing activity have children who develop language more rapidly than children whose parents use more directive strategies in establishing a shared focus. Findings from our longitudinal study provide evidence for both of these predictions. Predicting language growth from early nonverbal communication skills. Children s nonverbal communication skils were assessed during the initial visit of our longitudinal study using the Early Social Communication Scale described above. The five pre-
school measures of nonverbal communication skils (initiates social interaction responds to social interaction , initiates joint attention, responds to bids for joint atten-
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tion , initiates behavior regulation) were used to predict children s language scores during the mid- school period. Given the stability of children s language abilities over time , all analyses statistically controlled for individual variations in initial language scores. The results showed that children s responsiveness to bids for joint attention reli-
ably predicted their expressive language scores during the mid- school assessment; r(33) = .46; Ol. That is , children who were more likely to respond to the experimenter s bids for joint attention during preschool had significantly better long- term language outcomes than children who were less responsive initially. This predictive relation was not explained by variations in initial language abilities. Besides joint attention , none of the other measures of nonverbal communication showed a reliable association with children s language outcomes. Neither their capacity to initiate social interaction , nor their responsiveness to social interaction initiated by the experimenter reliably predicted children s mid- school language abilities. Further , no reliable association was found between the frequency of the preschoolers ' requesting behaviors and language abilities during mid- school. Predicting language growth from the parents ' interactive
engagement during play. During the initial assessment of our longitudinal project, parents were provided with a standardized set of toys and asked to play with their children ' as they normally would' The interactions were videotaped and later analyzed using a micro- analytic coding system for which good inter- coder reliability has been demonstrated. In coding the videotaped interactions , we focused on a range of interactive behaviors used by the mothers and were particularly interested in how these behaviors related to children ongoing focus of attention as well as children s ongoing object engagement. A comprehensive description of the coding system including a detailed report on the find-
ings is provided elsewhere (Siler & Sigman , 2002). For the purpose of this presentation , we wil only focus on the parents ' verbal engagement during play. In a first step, we coded the onset of each of the mothers ' verbal utterances. In a second step, for each utterance it was decided a) whether the maternal utterance referred to a toy that the child was already looking at, and b) whether the maternal utterance reflected an intention to comment on the object or whether the utterance was demanding the performance of a specific object directed behavior. The measure included in our analysis was based on the frequency of maternal utterances that were responsive to children s focus of attention and also reflected an intention to comment
rather than demand. This measure was referred to as a measure of maternal synchronization. For the data analysis , the primary operation was to use the measurements of maternal synchronization to predict children s subsequent growth in language abilities until mid- school and early adulthood. Findings from this analysis indicate that
'The final measure of maternal synchronization used in this analysis was based on the frequency of synchronized maternal utterances but also controlled for a) the mothers ' overall verbal engagement , and b) the duration children spent attending to toys. Neither of these control variables was in itself related to chil-
dren s language outcomes.
~, ." 001- 018
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~.
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mothers who showed higher levels of behavioral synchronization initially had children who developed superior language skils until mid- school (r (17) = . 005) and early adulthood (r (19) = . 001). Importantly, further analysis showed that
this predictive relation between maternal synchronization and children s subsequent language growth was not due to variations in initial child characteristics such as language , IQ, or joint attention.
Conclusion Long before children acquire an understanding of the semantic and syntactic characteristics of spoken language , children have already developed a vast knowledge about the pragmatics of human communication. To a large extent , this knowledge develops during preverbal interactions between the infants and their parents. Emphasizing the continuity between preverbal and verbal communication is of great intuitive appeal; however , it has proven difficult to empirically validate specific links between the infants ' preverbal experiences and the subsequent origin of spoken lan-
guage. The findings reviewed above provide such a specific link. During the second half of the first year , typically developing infants and their parents start to collaborate in establishing a shared interest in the world around them. Our findings suggest that , at least in the case of autism , the success of the parent- child dyad in managing such a shared interest in external objects or events is developmentally linked to children s long- term language outcomes. Specifically, the research reviewed above had three major findings. First, when compared to matched controls , children with autism showed a specific deficit in
behaviors used to establish joint attention with other people. Second , preschool aged children with autism who were more responsive to another person s bid for joint attention had reliably better language skils when assessed during mid- school than did children who were less responsive to bids for joint attention initially. Third , parents who were more responsive to their children s focus of attention and ongoing
activity during initial play interactions had children who developed language skils until mid- school and early adulthood that were superior to children of parents who were less responsive initially. Importantly, both predictive relations were independent from each other and could not be explained by variations in children s initial language ability or overall intellectual level. Until recently, children with autism were believed to suffer from a rather generic social deficit, affecting all areas of human communication. According to the Third Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM III), published as late as 1980 , the social deficits of children with autism include a " failure to develop interpersonal relationships a lack of responsiveness to and a lack of interest in other people , a " failure to develop normal attachment behaviors , as well as an " indifference or aversion to affection and physical contact" . During the last two decades , researchers and clinicians became increasingly aware that the aloof picture painted in these early accounts on autism did not do justice to the quality of the rela-
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tionships that children with autism entertain with other people. Much of this reevaluation was sparked by Bruner s insight that human communication serves a variety of different functions. Recent research , evaluating the social characteristics of children with autism across different communicative situations has identified a complex pattern of strengths and weaknesses. Social encounters between young children with autism and their parents are most successful when directed at affiliation. Such exchanges frequently utilize a face- toface situation and involve activities such as tickling, chasing, rough and tumble play,
or peek- boo. In the context of these social activities , children with autism usually require only minor support from their parents , participate with enjoyment and eye contact , take turns and even take the initiative in order for the game to continue. Along the same lines , a number of studies have shown that children with autism once reunited with their parents after a few minutes of separation , demonstrate clear signs of attachment (Capps , Sigman , & Mundy, 1994; Rogers , Ozonoff, & MaslinCole , 1991 , 1993; Shapiro , Sherman , Calamari , & Koch , 1987; Sigman & Ungerer 1984). That is , during reunion episodes , children with autism were shown to direct more social behaviors and physical contact to their parents than they do to a stranger. Another social encounter of relative strength involves situations where children with autism are motivated to request objects or assistance from another person. Clearly, children with autism share the notion that other people can be instrumental for acquiring help. This is not to say that the communicative means children with autism use to communicate requests are as advanced as one would hope. In requesting objects or assistance , children with autism tend to be limited to direct means of communication (e. g. guiding another person s hand , reaching), lacking symbolic behaviors such as gestures and language. Our research showed that the social difficulties of children with autism are most apparent during social exchanges directed at establishing and maintaining a shared interest in the surrounding world. This finding is very robust and has been replicated in other research laboratories (Loveland & Landry, 1986). Also , most current diagnostic inventories consider joint attention behaviors as an important indicator for autism , for example , the Autism Diagnostic Observation Schedule - Generic ADOS- G (DiLavore , Lord , & Rutter , 1995), or the Modified Checklist for Autism in Toddlers , M- CHAT (Charm an et al. , 2001; Robins , Fein , Barton , & Green , 2001). Moreover , the success of the parent- child dyad in establishing a shared interest in external objects , events , or topics appears to be linked to children s subsequent origin of spoken language. That is , both children s responsiveness to the parents ' bids for joint attention and the parents ' responsiveness to the children s focus of attention and ongoing activity reliably predicted the rate of children s subsequent language acquisition. It is important to emphasize that the predictive relation between preschoolers access to certain interactive experiences Uoint attention , maternal synchronization) and children s subsequent language development is correlational in nature. Correlational findings do not allow us to draw firm conclusions about the underlying causal mechanisms. That is , correlated variables , even when separated by time , do
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not necessarily reflect a direct causal link but can also be the outcome of an unidentified third variable. For example , it would have been possible that children s initial language or overall intellectual functioning was linked to both , children s access to interactive experiences and their language outcomes. Using methods of statistical control , our data showed that both variables , initial language and IQ, were not able to account for the predictive relations identified in our research. However , in longitudinal research there is no way of knowing whether other variables that have not been evaluated as part of the study could provide such an alternate explanation. In order to identify the causal network underlying the predictive relations identified in our research , future studies would need to move towards research designs where subjects are randomly assigned to different treatment conditions.
According to Bruner , typically developing infants and their mothers collaborate in developing interactive routines that enable infants to conventionalize three fundamental communicative intentions: affiliating, requesting, and sharing. In comparison interactive exchanges between preschoolers with autism and their mothers are less routinized and the underlying communicative intentions are much harder to detect. Nevertheless , interventions targeting communication skils in young children with
autism have developed a variety of interactive strategies that help children with autism to make their intentions plain. Many such strategies have focused on children s requesting behaviors , for example: Incidental Teaching (McGee , Morrier Daly, 1999), Pivotal Response Training (Koegel , Koegel , Harrower , & Carter , 1999; Koegel, Koegel , Shoshan , & McNerney, 1999; Laski , Charlop, & Schreibman , 1988; Schreibman , Kaneko , & Koegel , 1991), or Developmental , Individual- Difference Relationship- Based Program , DIR , (Greenspan & Wieder , 1998 , 1999). Generally, these approaches use environmental arrangements (e. g. placing attractive objects in children s view but out of their reach) and interactive strategies (e. g. gently interrupting the children s play by placing a hand on the toy, providing the children with a choice of attractive items) to elicit a state of heightened emotions where children are likely to request objects or assistance. Once children communicate this intent (e. g. by guiding the adults hand towards the desired objects) the adult uses prompting strategies to shape children s communicative means (e. g. by purposefully misunderstanding the child' s request). Similar interactive strategies have been developed to conventionalize children s affiliating behaviors. Intervention programs such as DIR face exchanges to promote eye contact , to promote children s active
utilize face- to-
participation during reciprocal games , and above all to increase the length of the communicative exchange (the number of circles of communication that are opened and closed).
Developing interactive strategies that elicit and conventionalize acts of sharing from children with autism has proven to be much more difficult. Our data suggest that following children s lead and commenting on their ongoing experiences with objects might be a first step. Joining the children in manipulating the preferred toy might be a second step. However , to be successful in joining the object engagement of children with autism , adults have to be very careful not to throw the child off by being too demanding or intrusive. Encounters where adults and children are engaged
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in parallel activities might be more successful if adults assume an attitude where chil-
dren are considered to be the expert on how to play with the toys. Once parallel activities are established , the encounter can be elaborated in many directions: adults may start to imitate some of their children s actions; they might develop games where adults act contingent upon children s object directed behaviors; they might leave some of their actions unfinished; or they might create situations where unexpected things can happen. All these elaborations might prompt the children to acknowledge the adults ' involvement by alternating their gaze between the toy and the adults ' face or by completing or imitating the adults ' actions. The account presented above emphasizes that humans communicate for various
reasons and that researchers or clinicians concerned with the development of communication skils are well advised to carefully consider the different functions that communication plays in the life of young children. Our research shows that this perspective is very productive not only for pinpointing the social deficits of young children with autism but also for identifying social experiences that are linked to children s subsequent language development. Particularly, our research emphasizes that episodes of shared interest in an object , event, or topic provide a unique context for language learning. Helping parents to be successful at managing such encounters might be an important piece in a comprehensive intervention program targeting communication and language in young children with autism.
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SILLER AND SIGMAN Mailing Address:
Michael Siller, M.A. UCLA School of Medicine
NPI68-237 760 Westwood Plaza Los Angeles,
CA 90024- 7759 (370) 825- 8866 (370) 825- 2682 FAX Email address: sillerr:ucla. edu
Acknowledgements article was supported by the Program Project Grant HDDCD35470 , Grant HD 17662 from the National Institute of Child Health and Human Development and the National Institute of Deafness and Communication Disorders Grant NS25243 from the National Institute of Neurological Diseases and Stroke , and the M. I.N. D. Institute Research Program. We wish to thank the children who allowed us to observe them growing up. We
Preparation of this
extend our appreciation to their parents who committed so much time and effort to our project.
We also wish to thank all the researchers who contributed to this project over the years.
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Is One Style of Early Behavioral Treatment for Autism ' Scientifically Proven?'
Morton Ann Gernsbacher , Ph.
Within the field of autism spectrum disorder, the attribute 'scientifcally proven ' is most commonly seen in reference to the results of early behavioral treatment, and in particular one style of early behavioral treatment. In this brief article, such claims are evaluated. Concerns
Abstract.
raised by other researchers about the methodology of the original Lovaas
(7987)
study are briefly
concern that has been raised repeatedly is the lack of random assignment of particiPants to treatment versus control group. A more recent study (Smith, Groen Wynn, 2000), which included the necessary random assignment of particiPants to treatment versus control group and assessed multiple outcome measures, is reviewed. The results of the Smith et al. (2000) study with random assignment appear to be less dramatic than the results
summarized. A particular
from the original Lovaas
(7987)
study.
The attribute ' scientifically proven ' is common bait for consumers. Over 20 books advertised on Amazon. com contain in their title the phrase scientifically proven. These books include titles promising readers that they can reverse heart disease (Ornish , 1996); gain physical fitness without exercise (Stamford , 1990); become an effective coach (Smith & Small , 1996); cure age- related memory decline (Crook & Adderly, 1998); and create world peace (Roth , 1994). Over 300 000 websites promise scientifically proven solutions to a myriad of challenges, ranging from the scientifically proven way to stop cancer (www. stopping- cancer- naturally. org/) to the
scientifically proven " best
way to lace
your shoes " (www. techdirt.com/arti-
cles/20021204/1436200. shtml). There is even a U.S. political party (www. naturallaw. org) whose members claim that their platform is based solely on " scientifically proven solutions to the nation s problems. Of those 300 000 websites promising scientifically proven solutions , over 600 discuss scientifically proven ' solutions ' for autism. Frequent among these websites about autism are the following claims: " FACT: There is a scientifically proven effec-
tive treatment principle for treating children with autism. This treatment is called Applied Behavior Analysis (ABA). Using highly trained certified staff administering 30- 40 hours per week of intensive one- to- one
treatment ,
the studies show that 47% of
the children reach normal functioning. They are indistinguishable from their peers. (www. oregonparen tsunited. org/ articles/ effective _ autism treatment)
, "
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MORTON ANN GERNSBACHER
Indeed , many agencies and individuals claim that only one style of early behavioral intervention for autism is scientifically proven. For instance , BridgesABAtapes. com (a company that sells audio tapes for ABA training) claims that " although parents of autistic children are constantly bombarded by theories claiming to cure autism , only one treatment is passing the test of time and research: Applied Behavior Analysis (ABA)" (www. bridgesabatapes. com/autism. html). A student at Drury University reporting about her summer internship claims that "ABA therapy is the only scientifically proven and documented way of enabling preschoolers to enter grade school indistinguishable from their peers " (www. drury. edu/multinl/story. cfm?ID=4397&
NLID=202). In his online comment about Maurice et al.' s (1996) book , a readerreviewer on the Barnes & Noble website claims: " Behavioral therapy, the discrete trial method used by Dr. Lovaas , is the only scientifically proven treatment for autism. The sense of singularity among some individuals is so strong that the Clinical
Practice Guideline for Assessment and Intervention of Young Children with Autism/ sponsored by the New York State Department of Health , recommends that some interventions not even be included in a child' s therapeutic program because those interventions might take time away from an intervention that had been scientifically proven. Behavior Analysis , Inc ominously warns that " diverting attention , even for a brief period of time , away from treatment methods that have been scientifically proven to be effective is a disservice and can have serious consequences " (www. behavior- analysis. org).
Pervasive Developmental Disorder (1999),
But what is the science behind these claims that one style of early behavioral intervention for autism is ' scientifically proven?' Are there , as stated on the Surgeon thirty years of research demonstrating the efficacy of applied General's website behavioral methods in reducing inappropriate behavior and in increasing communication , learning, and appropriate social behavior " (www. surgeongeneral.gov/library/
mentalhealth/chapter3/sec6. html#autism)? This question can be answered by referring to the New York State Department of Health Guideline for Assessment and Intervention of Young Children with Autism/Pervasive Developmental Disorder (1999) because , in formulating their guideline , the authors conducted a thorough literature search. The authors found " 232 articles that reported using behavioral and educational approaches in children with autism. ... These articles were systematically
screened and five articles (reporting four studies) were found that met the (authors established criteria for adequate evidence about efficacy " (p. IV- 17). Thus , of the 232 articles that the authors of the New York State Guideline found in their exhaustive literature search ,
only five articles met their own standards for adequate evidence. And those five articles report only four studies. Those four studies are what can now be called the classic study by Lovaas (1987) published over fifteen years ago , a study by Birnbrauer and Leach (1993), a study by Smith and colleagues (1997), and a study by Sheinkopf and Siegel (1998). Those four studies are the only scientific proof that met the New York State Department of Health Clinical Practice Guideline s criteria for adequate evidence.
,"
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SCIENTIFICALLY PROVEN' TREATMENT FOR AUTISM
However , as even the New York State Guideline state: " None of the four studies that met criteria for effcacy used random assignment of the children to groups (such as to the group receiving intensive behavioral intervention versus the group receiving a comparison intervention)" (p. IV- 22). Random assignment is the practice of assigning participants to conditions (e. , treatment versus control) such that each participant has an equal chance of being assigned to each of the conditions. As any scientist knows , random assignment is a core feature of scientific credibility in treatment studies. Unfortunately, however , even though Lovaas ' (1987) study did include an experimental and a control group- indeed , there were two intended control groupsassignment to either the experimental or the control group was not random. Rather as the authors described , assignment to the experimental versus control group was based on the therapists ' availability. Birnbrauer and Leach' s (1993) study also included an experimental and a control group; unfortunately, as with the Lovaas (1987) study, assignment to either the experimental or the control group was again not random. In this case it was based on what the authors called " practical factors. And neither Smith et aI's (1997) study nor Sheinkopf and Siegel's (1998) study used a classic experimental design. Rather. both used retrospective data (i. , once the out-
comes were known , the authors looked back in time to see which treatment the subjects had received; therefore , by definition , subjects were not assigned randomly to those treatments). Thus , only the Lovaas (1987) and the Birnbrauer and Leach (1983)
studies qualify as true experimental designs , but disappointingly neither used random assignment, which is a prerequisite for empirical interpretation. Although the New York State Guideline authors suggest that " it has been argued that the (non- random)
method for group assignment probably did not bias the
results " (p. IV- 22), many scientists would draw the same conclusions as those drawn in a recent article titled Separating fact from fiction in the etiology and treatment of autism: A scientific review of the evidence " which was published in the Scientifc (Herbert , Sharp, & Gaudiano , 2002; see also Foxx Review of Mental Health Practice 1993; Kazdin , 1993; Schopler , Short , & Mesibov , 1989). The Scientifc Review of Mental Health Practice
existing
article suggests that the " methodological weaknesses of the
studies , however , severely limit the conclusions that can be drawn about
their efficacy. ... Of particular note is the fact that no study to date has utilized a true experimental design , in which subjects were randomly assigned to treatment conditions " (p. 37). Indeed , Herbert and Brandsma (2001) wrote , in an editorial titled Applied Behavioral Analysis for childhood autism: Does the emperor have Behavior Analyst Today: Most critically, the Lovaas study clothes? " published in the was not a true experiment, as participants were not randomly assigned to (treatment versus control) groups. The manner in which subjects were assigned to groups raises serious questions about the possibility of selection bias , which are underscored by pre- intervention differences between the experimental and control groups. These methodological weaknesses limit the conclusions that can be drawn from this hallmark study (p. 47).
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However , in 2000 , Smith , Groen , and Wynn published the first truly randomized trial of intensive early intervention for children with pervasive developmental disorder. As the authors wrote: " To address criticisms of previous research and increase methodological rigor , we conducted a fully randomized clinical trial with uniform comprehensive assessment protocols for all participants " (p. 271). Smith et al.' s (2000) experiment attempted to overcome other criticisms , as well. Despite claims that early intervention based on the principles of ABA can produce " large , comprehensive lasting and meaningful improvements in many important domains " (Green , 1996 38), the original Lovaas (1987) study included only two outcome measures: posttreatment IQ scores and public school placement. Changes in IQ could reflect increased compliance with testing rather than true changes in cognitive abilities , and school placement could have more to do with parent advocacy and differential school policies than with actual functional changes. Thus , Smith et al.' s (2000) first randomized treatment study overcame these limitations by including assessment of several important domains of functioning. Smith et al.' s (2000) study involved 28 children , whose age at intake ranged from
24 months to 43 months and whose age at follow up ranged from 41 months to 117 months. Fifteen children were randomly assigned to the treatment group, and 13 children were randomly assigned to the control group. The children randomly assigned to the treatment group received Lovaas style intervention for an average of 25 hours per week lasting a range of 18 months to 63 months. The children randomly assigned to the comparison group received intervention as delivered by their parents. In other words , the comparison group received parent- instructed treatment. At either intake or at follow- up,
Smith et al. measured these domains: Intelligence ,
Academic
Achievement, Language , Socioemotional Functioning, and Adaptive Functioning. The researchers measured intelligence using either the Stanford- Binet Intelligence Scales (Thorndike , Hagen , & Sattler , 1986) or the Bayley Scales ofInfant Development- Mental Development (Bayley, 1969) and the Merril Palmer Scale of Mental Tests (Stutsman , 1948). The researchers measured academic achievement via Wechsler Individualized Achievement Test (WIAT). The WIAT was administered only at follow up. The researchers measured language via the Reynell Developmental Scales (Reynell , 1990), which have a scale for expressive language how well the child produces language- and receptive language- how well the child comprehends language. The researchers measured socioemotional functioning via the Achenbach Child Behavior Checklist (Achenbach ,
1991). This checklist , which
was also administered only at follow up, was completed by both the child' s primary caregiver and the child' s teacher. The checklist covers issues such as social withdrawal , social problems , attention problems , and behavior problems such as aggression. The researchers measured " adaptive functioning " using the Vineland Adaptive Behavior Scales (Sparrow , Balla , & Cicchetti , 1984). These scales are derived from an interview with the primary caregiver. The study used three scales: Communication
Daily Living Skils , and Socialization. Adaptive functioning was assessed at both intake and follow up.
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As Smith et al. (2000) report: " Two of the 15 intensively treated children met the criteria used by Lovaas (1987) and McEachin et al. (1993) for classifying children as best outcome,' namely placement in regular classes without special services and IQ/85). " Thus , in contrast to Lovaas ' (1987) reported 47% success rate according to their two outcome measures of IQ and school placement for children treated with Lovaas- style intervention , using the scientifically crucial random assignment Smith et
al. reported only a 13% success rate. The other outcome measures were also substantially less dramatic. There were statistically significant differences between the Lovaas- style treatment group and the parent-based treatment group at follow up on both the Stanford- Binet and the Merril Palmer. There was only a marginally statistically significant difference between the Lovaas- style treatment group and the parent- based treatment group on the measure of academic achievement. However , this statistical analysis might be somewhat com-
promised because nearly one- third of the control group was missing data on this test. There were no statistically significant differences between the Lovaas-style treatment group and the parent- based treatment group on either of the two language scales. Although this is reported to be a significant difference in the paper , there was an error in data analysis (and an erratum was subsequently published , Smith , 2001). There were also no statistically significant differences between the Lovaas- style treatment group and the parent-based treatment group in socioemotional functioning,
assessed by the Achenbach Child Behavior Checklist. And there were no statistically significant differences between the Lovaas- style treatment group and the parentbased treatment group in adaptive functioning as assessed by the Vineland Scales of Communication , Daily Living Skils or Socialization or even as assessed by a composite of those three scales. Indeed , even within the Lovaas- style treatment group there were no gains in adaptive functioning from intake to follow up. Smith et al. (2000) should be heartily applauded for undertaking the definitive test of Lovaas- style intervention using the crucial ingredient of randomized assignment. Such an experiment was far from easy to conduct; if it were , others would have done it much earlier. Most strikingly, no other intervention has been submitted to such empirical scrutiny. It is to the great credit of ABA proponents that they have consistently sought to provide scientific evidence of the efficacy of their treatment. However , given these data , namely that only one area of assessment showed a statistically significant difference due to treatment , and that only 13% met the criteria of success outlined by Lovaas (1987), it is perhaps appropriate to agree with the following admonition from the Scientifc Review of Mental Health Practice: Given the current state of the science , claims of ' cure' and ' recovery ' from autism produced by ABA are misleading and irresponsible "
(p. 37).
article about intervention for autism (Tarkan , October 2002) began by stating that " no one has found a cure for autism , the neurological disorder that leads to lifelong impairments in a child' s ability to speak , respond to others , share affection and learn. But there is a growing consensus that intensive early intervention is both effective and essential- the sooner after diagnosis , the better. Early intervention , which involves many hours of therapy with one or more specialA recent
New York Times
),
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ists (NB: the article later states that there are several different types of therapy) does not help every autistic child to the same degree... and for reasons that are unclear it does not help some children at all. But for those who are helped , their parents say, the changes are miraculous.
It behooves all of us to find the avenues that wil lead to what every parent would call miraculous. In route to finding those avenues , we should most likely exercise caution in claiming that one style of intervention has been scientifically proven.
References Achenbach ,
T. M. (1991).
Integrative guide for the
7997
Child Behavior Checklist/4-
Burlington: University of Vermont ,
Teacher Report Form profiles.
, YSR, and
Department of
Psychiatry. Bayley Scales of Infant Development. New York: Psychological Corporation. Birnbrauer j., & Leach , D. (1993). The Murdoch early intervention program after 2 years. Bayley, N. (1969).
Behavior Change
Crook , T. ,
63- 74.
& Adderly, B. D. (1998).
can slow, halt,
The memory cure: The safe, scientifcally proven breakthrough that
New York: Pocket Star Books. Foxx , R M. (1993). Sapid effects awaiting independent replication. AmericanJournal of Mental Retardation , 375- 376. Green , G. (1996). Early behavioral intervention for autism: What does the research tell us? In C. Maurice , G. Green , & S. C. Luce (Eds. Behavioral interventions ftr young children with autism: A manual for parents and professionals (pp. 29- 44). Austin , TX: PRO- ED. Herbert j. D. & Brandsma , L. L. (2001). Applied behavior analysis for childhood autism: does or even reverse age- related memory.
the emperor have clothes?
Herbert
j. D. ,
, 45-50.
The Behavior Analyst Today,
Sharp, 1. R , & Gaudino , B. A. (2002). Separating fact from fiction in the etiol-
ogy and treatment of autism: A scientific review of the evidence.
Mental Health Practice
The Scientifc Review of
, 25-45.
Kazdin , A. E. (1993). Replication and extension of behavioral treatment of autistic disorder. American Journal of Mental Retardation , 377-380. Lovaas , O. 1. (1987). Behavioral treatment and normal educational and intellectual functioning in young autistic children.
Journal of Consulting and Clinical Psychology,
Maurice , C. , Green , G. & Luce , S. C. (Eds. ),
, 3-
(1996). Behavioralinterventions ftr young children with
autism: A manual for parents and professionals. Austin , TX: PRO- ED. McEachin j., Smith , T. , & Lovaas , O. 1. (1993). Long- term outcome for children with autism who received early intensive behavioral treatment.
AmericanJournal of Mental Retardation
359-372. New York State Department of Health Early Intervention Program. (1999).
Clinical practice
Autism/Pervasive Developmental Disorders. Assessment and intervention for young children (age 0- 3 years). New York , NY. Ornish , D. (1996). Dr. Dean Ornish's program for reversing heart disease: The only system scientifcally proven to reverse heart disease without drugs or surgery. New York: Ivy Books. Reynell , j. K. (1990). Reynell Developmental Language Scales. Los Angeles , CA: Western Psychological Corporation. Roth , R (1994). TM- Transcendental Meditation: A new introduction to Maharishi' s easy, efctive and scientifcally proven technique ftr promoting better health, unfolding your creative potential, and creating peace in the world. New York: Fine. Schopler , E. Short, A. , & Mesibov , G. (1989). Relation of behavioral tratement to " normal functioning; " Comment on Lovaas. Journal of Consulting and Clinical Psychology, 47 162- 164. guideline: The guideline technical report.
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Sheinkopf, S., & Siegel , B. (1998). Home-based behavioral treatment of young children with autism. , 15- 23. Journal of Autism and Developmental Disorders Smith , R. E. , & Small , F. L. (1996). fVy to go, coach: A scientifcally proven approach to coaching effctiveness. Portola , CA: Warde Publishers. Smith , T. , Eikeseth , S. Klevstrand , M. , & Lovaas , O. 1. (1997). Intensive behavioral treatment for preschoolers with severe mental retardation and pervasive developmental disrder. AmericanJournalof Mental Retardation 102 , 238-249. Smith , T. , Groen , A. D. , Wynn j. W. (2000). Randomized trial of intensive early intervention
for children with pervasive developmental
Retardation 105 269- 85. Smith , T. , Groen , A. D. , Wynn
j. W. (2001). Erratum.
106 , 208. Sparro , S. , Balla, D. A. , & Cicchetti ,
disorder.
American Journal of Mental
AmericanJournal of Mental Retardation
D. V. (1984). The Vineland Adaptive Behavior Scales. Circle River , MN: American Guidance Service. Stamford , B. (1990). Fitness without exercise: The scientifcally proven strategy for achieving maximum health with minimum effort. New York , NY: Warner Books. Stutsman , R. (1948). Guide for administering the Merrill-Palmer Scale of Mental Tests. New York: Harcourt, Brace & World. Tarkan , L. (2002). Autism therapy is called effective , but rare. New York Times. Thorndike , R. L. , Hagen , E. P. , & Sattler j. M. (1986). Stanford-Binet Intelligence Scale (4th ed.
Chicago: Riverside. Mailing Address:
Morton Ann Gernsbacher, Ph. Sir Frederic
C.
Bartlett Professor
University of Wisconsin-Madison
7202 WJohnson Street Madison, WI 53706- 7677 (608)
262- 6989
ffx (608) 262- 4029)
http://psych. wisc. edu/lang/MGcover. html
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Disorders of Speech Sound Perception in Children with Asperger Syndrome
Dana Boatman , Ph.
, CCC-
Key words: auditory processing disorder , speech perception , Asperger syndrome autism Abstract:
Asperger syndrome (AS) is a neurodevelopmental disorder characterized by severe
impairment of social behavior with seemingly normal language and cognitive development. Recent studies, however, have identifed subtle receptive and expressive language abnormalities in AS The possibility of a low- level speech perception disorder in AS has yet to be examined. In this preliminary investigation, we evaluated auditory processing of speech sounds (phonemes) in six normal- hearing children with AS Three aspects of phoneme processing were tested: blending, closure, and discrimination. All AS particiPants demonstrated impaired phoneme processing when speech stimuli were acoustically or lexically degraded. Concurrent tests of auditory working memory, tone discrimination, and word recognition were normal. These results suggest subtle impairments in the fUndamental speech perception abilities of children with AS
INIODUCTION Asperger syndrome (AS) is a neurodevelopmental disorder characterized by impaired social behavior and focused interests , in the context of seemingly normal language and cognitive development (American Psychiatric Association , 1994). Although social aspects of language are impaired in AS, as in most autism spectrum disorders (Landa ,
2000), other language functions appear normal. The reported
absence of language delays in AS and the observation that language abilities in these often highly verbal individuals are typically better than in other autism spectrum disorders support this view (Baltaxe & Simmons , 1985; Tager- Flusberg, 1981; Wing, 1981).
Recent studies , however , have revealed subtle language abnormalities in AS. Using fine- grained
analyses , Shriberg and colleagues (2001) identified articulation
"Portions of this paper were presented at the Interdisciplinar Council on Developmental and Learning Disorders Sixth Annual International Conference on Autism and Disorders of Relating and Communicating in McLean , Virginia on November 9, 2002.
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distortions in 33% of their AS subjects. Higher- level
receptive and expressive lan-
guage abnormalities have also been observed (Howlin , 2003; Koning & MagillEvans , 2001). To date , little is known about basic speech perception abilities in AS.
Deficiencies in early processing of spoken speech , including the ability to decode consonant and vowel speech sounds (phonemes), can impact language functions , as observed in children with developmental language disorders (Tallal , Stark , & Mellits 1985). Moreover , it has been shown that children with autism fail to show the same preference for speech sounds as normally developing children (Klin , 1991). In light of these reports , investigation of phoneme processing in AS appears warranted. In a preliminary attempt to address this issue , we tested multiple aspects of phoneme processing in six children with AS.
METIODS
Parcipants Six children (age 9- 14; mean age 10;6 years), five boys and one girl participated (Table 1). All met DSM- IV criteria for AS , as determined by a pediatric neurologist (American Psychiatric Association , 1994). Diagnostic criteria included severe socialbehavioral impairments , focused interests , and normal language and cognitive devel-
opment. Four were right handed and two were left handed. Normal language development was defined clinically as the absence of language delays or regression with production of 2- 3 word phrases by age 3 years (American Psychiatric Association , 1994). On neuropsychological testing, all participants obtained full- scale IQ scores
93 (mean = 118 ,
SD :t18. 7) on the Wechsler Intelligence Scale (WISC-
III R , Wechsler , 1991). All had normal neurological examinations , negative tests for Fragile X , no co- morbid neurological disorders (e. , seizures), no history of chronic otitis media , and no history of hearing or speech disorders. Because the presence of a hearing loss can interfere with detection of acoustic cues used to process phonemes (Schuknecht, 1974), only AS subjects with normal hearing were included. Subjects with a history of chronic otitis media , defined as more than two ear infections by age 6 years , were also excluded because of an association with hearing loss. Two partici-
Table 1. Parcipant Demographics
Gender Age Handedness Full Scae
Medications
Disorders Right Right Right Left
Right Left
134 129 123 135
None None None None Depression
ADHD
None None None None sertraline methylphenidate
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pants were on medication , one for treatment of depression (Participant 5 , sertraline) and one for treatment of an attention disorder (Participant 6 , methylphenidate). Four
of the children had undergone previous EEG and/or MRI studies , with normal results.
Other features associated with AS were present, but not used diagnostically. These included hyper- verbalization (5 participants), flattened intonation and prosody (4 participants), observed " clumsiness " reported by parents and pediatricians (5 participants), and hypersensitivity to sound (3 participants). Two participants had a family history of social- behavior difficulties (paternal uncle , maternal grandfather), and two had histories of repetitive behavior (e. g. hand flapping). Previous speech- language evaluations yielded age- appropriate scores on tests of expressive and receptive language , including the Expressive One-Word Picture Vocabulary Test (Gardner , 1979) and the Peabody Picture Vocabulary Test- III (Dunn & Dunn , 1981). All six had difficulty with idiomatic expressions , figures of speech and other pragmatic language functions.
Procedures All testing was performed in a sound- treated audiometric booth using a two- channel audiometer (GSI- 30) and an acoustic immittance system (Madsen Zodiac 901). Testing was completed in one session , with the number of breaks determined by indi-
vidual needs. Parental consent was obtained for all participants in accordance with our institution s IRB requirements.
Hearng evaluations All participants underwent routine hearing evaluations to confirm normal hearing. Otoscopic exams were performed to rule out excessive cerumen or foreign bodies in the ear canal that might interfere with test results. Pure tone air and bone conduction thresholds were established behaviorally for each ear at seven octave and inter- octave frequencies from 0. 25- 8 kHz. Participants pressed a button in response to sound presentation. Results were interpreted based on published clinical norms of s: 20 dB HL as the range of normal hearing thresholds (ASHA , 1978). In light of concerns that examiner bias and subject factors can affect testing of individuals with autism spectrum disorders (Gravel et al. , 1994), Distortion Product Otoacoustic Emissions (DPOAEs) were performed to provide an objective measure of the frequency- specific responses of outer hair cells (Kemp, 1978). A handheld screener (ERO SCAN , Etymotic Research) was used with an eartip probe that fit into the ear canal with a seal. DPOAEs were elicited for each ear at six frequencies (1.5 , 2 , 3 , 4
5 and 6 kHz). Emissions were measured in the 2fl- f2 frequency band (fl intensity = 65 dB SPL , f2 intensity = 55 dB SPL), using a pass criterion of 5 dB or greater above the average noise level in adjacent frequency bands. Speech reception thresholds
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were determined with spondee words , and word recognition was tested in quiet using CID W22 word lists (40 dB SL , 25 words per ear). Tympanometry (226 Hz probe), performed to assess middle ear function , yielded tympanograms classified as normal (Type A , :t150 daPa) or abnormal (Types B , C). Acoustic middle ear reflexes were tested (2000 Hz , contralateral stimulation) and determined to be normal if they occurred at ,s 90 dB SPL. Auditory brainstem response (ABR) testing was also performed in light of previous reports of brain stem auditory dysfunction in children with autism spectrum disorders (Ornitz , 1974; Tanguay et al. , 1982; Rosenhall et al. , 2003). Two participants
had undergone ABR testing previously, with normal results. For the four remaining participants , ABRs were elicited with rarefaction clicks presented (21/sec) monaurally at 75 dB SPL (?: 55 dB SL) with 45 dB of masking noise in the contralateral ear.
Four silver disk electrodes were used to record from vertex (Cz) to the mastoid (AI A2) ipsilateral to the stimulated ear , with a low forehead electrode (Fp) as ground. Electrode impedances were maintained below 5 kOhm. The EEG filter was set to bandpass 100- 3000 Hz. A total of 2000 trials were recorded for each ear using a Nicolet Spirit Evoked Response System. For each participant , waveforms were averaged using a post- stimulus analysis time of 15 msec. Peak latencies for waves I-V were identified for each ear. Absolute and inter- peak latencies were compared to clinical norms for subjects ' age ranges.
Phoneme processing Three tests of auditory phoneme processing were administered. All used single
words or syllables produced by male native speakers of English. Test stimuli were presented from compact disc through insert earphones (Eartone , 3A), at 50 dB HL following 2- 4
practice items.
Phoneme blending.
The standardized Phoneme Synthesis Test was used to assess
participants ' ability to blend individual phonemes into words (Katz & Fletcher , 1998). Twenty- five phoneme strings , each containing 3-4 individual phonemes , were presented binaurally. Participants said the words they derived by blending each phoneme string. For each participant , the total number of correctly synthesized words was compared to published age norms. Phoneme closure. The standardized Filtered Word subtest of the SCAN- CIA test was administered to evaluate participants ' ability to compensate for loss of high- frequency phonological cues resulting from low- pass acoustic filtering (Keith , 1994 2000). The children s version (SCAN- C) was administered to the four participants ,s 11 years of age , and the SCAN- A was administered to the two older children. Participants repeated forty monosyllabic low- pass filtered words (1.0 kHz cut off, 32 dB/octave roll- off) presented to each ear. Each participant's score was compared to published age norms. Phoneme discrimination. A binary, forced- choice , same- different paradigm in which twenty- five digitized (44 kHz , 16 bit sampling) consonant- vowel syllable pairs (e.
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SPEECH PERCEPTION IN ASPERGER SYNDROME
pa- , di- di) were administered binaurally. This test has been used with other populations (Boatman , Lesser , & Gordon , 1995; Boatman , Vining, Freeman , & Carson
2003). Eighteen syllable pairs differed in initial consonant. The remaining seven pairs were identical. For this preliminary investigation , only consonant contrasts were used because of their known association with phoneme processing (Boatman et al. , 1995; Studdert- Kennedy & Shankweiler , 1970). Participants responded by pointing to one of two colored shapes representing ' same ' or ' different'. Because the phoneme blending and closure tests both used verbal responses , we chose a nonverbal response for the phoneme discrimination test to control for possible speecharticulation effects. To provide a comparative basis for evaluating participants ' performances , 6 control subjects were selected from a pool of normal subjects recruited previously to establish test norms. They were matched to our AS subjects by age gender , and handedness. All of the normal controls had 1) negative histories for neurological, speech- language , or hearing disorders; 2) confirmed normal hearing bilaterally; and 3) normal scores on the SCAN- CIA and Phoneme Synthesis tests.
Other testing Tone discrimination. A control test consisting of twenty pairs of frequency- modulated (FM) tones (starting frequencies = 0. , 0. 9 Hz , slope = 0 , 0.4 , 0. 8 kHz) was
administered from compact disc using the same paradigm as the phoneme discrimi-
nation test. FM tones were selected over steady- state tones because of their comparability to the consonant- vowel transitions of the phoneme discrimination stimuli. Seven tone pairs were contrasted by direction of the frequency change (e. , rising versus falling), seven by slope of the frequency change (e. , 0.4 Hz versus 0. 8 kHz), and six were identical. One participant (Participant 6) was evaluated before the tone discrimination test was added to the experimental protocol. Individual scores were compared with results from the same normal controls tested on the phoneme discrimination test. Digit Span test. To assess auditory (verbal) working memory, participants repeated (forward , backward) digit sequences of increasing length that were administered livevoice from the Wechsler intelligence scales (Wechsler , 1991).
RESULTS Participants were fully compliant and completed all testing. Test results are summarized in Table 2. All participants demonstrated normal pure tone air conduction (-s 20 dB HL , 0. 25- 8 kHz) and bone conduction (-s 20 dB HL , 0. 4 kHz) thresholds bilaterally. All met DPOAE pass criteria for both ears, confirming the normal behavioral threshold findings. For all participants , speech reception thresholds were within 10 dB of pure tone averages (0. 2 kHz), suggesting good response reliability, and word recognition in quiet was within the normal range (?: 92%). Type A tym-
(p
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Table 2. Test Results Given as Proporton Correct
year)
AS Parcipants (ag in
Tests (9
yr)
(9 yr)
(10
yr)
(10
Nonns
yr) (12 yr) (14 yr)
Phoneme Processing Tests
Phoneme Blending Phoneme Closure
72b
24b
68c
92- 1.0 80- 1.0 95- 1.0
76c
.48'
Phoneme Discrimination Other Tests
FM Tone Discrimination Digit Span Test
1.0
1.0
85- 1.0
"Phoneme blending as measured by the Phoneme Synthesis Test (Katz & Fletcher , 1998) bLower limit of normal for age 9 = . 72 on the Phoneme Synthesis Test (Katz & Fletcher , 1998) cLower limit of normal for age 10 = . 84 on the Phoneme Synthesis Test (Katz & Fletcher , 1998) dPhoneme closure measured by the Filtered word subtest of the
SCAN- CIA
(Keith ,
1996
2000)
eLower normal limit for age 9 = . 75 on the Filtered Word Subtest of the SCAN- C (Keith , 2000) fLower normal limit for age 10 = . 77 on the Filtered Word Subtest of the SCAN- C (Keith , 2000) gTest results given as scaled scores (Mean 10 , SD :t 3)
NA = not administered
panograms were obtained bilaterally in all cases , suggesting normal middle ear function , and acoustic reflexes were present at normal levels. ABR recordings yielded reproducible waveform morphologies. Based on clinical norms , absolute and interpeak latencies for waves I -V were determined to be within the normal range at stimulus presentation levels of 75 dB , with no significant inter- aural differences in wave
V latencies. All participants performed below normal limits for their age on tests of phoneme processing. On a test of phoneme blending (Phoneme Synthesis Test), five partici-
pants performed below the normal range (92- 100%), with an average score of 64% (range 24- 88% , SD :t24.l), and one participant (Participant 1) performed at the lower limit of normal for his age. AS participants demonstrated impaired phoneme closure abilities , as measured by the Filtered Word test. Compared with normal subjects who obtained a mean score of 88% (range = 80- 95% , SD :t7), the average score for AS participants was 60% (range = 48- 76% , SD :t 12), with five performing three
or more standard deviations below the normal range. Response errors on the phoneme blending and closure tests consisted largely of consonant substitutions andlor deletions (e. , pie;: buy, hit;: hop, need;: knee). On the phoneme discrimination test , AS participants ' scores ranged from 76- 96% (mean 85% , SD :t 7.84), while those of the normal controls ' ranged from 92- 100% (mean 98% , SD :t 3. 34). Logistic regression was used to compare the two groups , allowing over dispersion in the scale parameter to account for correlation within subjects (McCullagh & NeIder 1989). The AS participants performed significantly worse on the phoneme discrimination test than the normal controls = 0. 0002 , logistic regression).
(p
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On the FM tone discrimination test, AS participants ' scores (mean 96% , range 90- 100% , SD :t1.09) did not differ significantly = 0. , logistic regression) from
those of the normal controls (mean 93% , range 85- 100% , SD :t1.04). There was considerable overlap in the range of scores for both groups , with the AS participants performing slightly higher overall. On the Digit Span test of auditory working memory, five AS participants obtained scaled scores that were normal (10 :t 3), or better. One participant (Participant 2) scored just below the lower limit of normal (scaled score = 6).
DISCUSSION This study provides preliminary evidence that phoneme processing is impaired in children with AS. The perceptual deficiencies observed in our six AS participants were relatively subtle , emerging only when the speech stimuli were degraded acoustically (phoneme closure) or lexically (phoneme blending, phoneme discrimination).
The subtle nature of these phoneme processing difficulties may explain why they have previously gone undetected in AS. Behavioral evidence of phoneme processing difficulties coupled with normal hearing and ABR results , suggests a dysfunction higher in the auditory system. Lesion studies have associated
phoneme processing
disorders with dysfunction of the left temporal lobe (Boatman et al. ,
1995; Luria
1976; Miceli , Caltagirone , Gainotti , & Payer- Rigo , 1978). Neuroimaging and electro-
physiology studies have also identified left temporal lobe abnormalities in individuals with autism spectrum disorders (Bruneau , Roux , Adrien , & Barthelemy, 1999; Jones & Kerwin , 1990; Zilbovicius , et al. , 2000). The concurrent sparing of frequency- modulated (FM) tone discrimination further suggests that their perceptual difficulties did not stem from a more general auditory dysfunction or from difficulty comprehending task instructions. Differences in the acoustic complexity of the speech versus tone stimuli , however , preclude any definitive claims about the speechspecific nature of our participants ' perceptual difficulties. Although all were impaired
on measures of phoneme processing, there was considerable variability in their performance. Additional studies with larger numbers of AS participants as well as normal controls wil help to determine the range of variability and the extent to which there may be overlap with that of normal subjects. Participants ' errors on the phoneme blending and closure tests consisted largely of phoneme substitutions and/or deletions. Because these tests relied on verbal responses , the possibility of confounding effects from articulation warrants consideration. While previous speech- language evaluations revealed no evidence of overt articulation disorders , we cannot rule out more subtle articulation difficulties in the absence of detailed acoustic analyses , as recently suggested (Shriberg et al. , 2001). Participants ' poor phoneme processing scores cannot be attributed entirely to speech production difficulties , however , since they also performed poorly on the phoneme discrimination test that did not involve verbal responses. It may be argued that an impairment of auditory working memory would account for participants ' poor performances on phoneme tests that used longer stimuli , including the phoneme blend-
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ing and discrimination tests. However , all but one participant demonstrated normal auditory working memory abilities on digit span testing, and all performed normally on the tone discrimination test , which used the same presentation format as the phoneme discrimination test. Alternatively, an impairment of attention might account for the pattern of per-
ceptual deficits observed especially
since the
phoneme processing difficulties
emerged only under adverse listening conditions that also impose increased attention demands. Although only one participant had been diagnosed with an attention disorder , we cannot rule- out the possibility of a mild , previously unidentified attention
disorder in the others. Because all perceptual tests administered were behavioral and therefore , involved attention , we cannot rule- out potential effects of attention on participants ' performances. Electrophysiological recordings offer one means of evaluating auditory processing independent of attention. A recent electrophysiology study
of speech sound processing in children with high- functioning autism found evidence of a selective impairment in attention orienting to vowel sounds , with otherwise normal sensory processing of vowels and acoustically matched complex sounds (Ceponiene et al. , 2003). This suggests that the impairment in speech sound perception occurs after early sensory processing and reflects deficiencies in attention. Because children with very poor verbal language abilities were included , we cannot make direct comparisons with our participants , who had normal verbal language abilities. However , given the reportedly high rate of attention difficulties in AS (Schatz , Weimer , & Trauner , 2002), this issue clearly warrants further investigation. Our participants ' history of normal language development is surprising given their observed phoneme processing difficulties. One possibility is that their phoneme processing difficulties were sufficiently subtle as to not impede language develop-
ment. Alternatively, the predominantly single- word tests used to evaluate their receptive and expressive language abilities may have lacked sufficient sensitivity, as recently suggested (Konig & Magill- Evans , 2001). It is also possible that early delays
in language development resulting from perceptual deficiencies may have gone undetected because formal testing is usually not performed before age 3 , by which time these children may have begun to catch up with their peers (Howlin , 2003; Landa , 2000). Further investigation is needed to identify AS children who would
benefit from early remediation of their phoneme processing and , in turn , other language skils (Lindamood , Bell , & Lindamood , 1997; Merzenich , Jenkins , Johnston Schreiner , Miler , & Tallal , 1996). In summary, all six normal- hearing AS participants demonstrated impaired phoneme processing abilities , as measured by tests of phoneme blending, closure and discrimination. Their perceptual difficulties are not readily attributed to disorders of the peripheral or brainstem auditory system , articulation , working memory, or general auditory dysfunction. The potential contribution of attention difficulties to
the perceptual impairments observed remains to be determined. Future studies wil help to clarify the exact nature of the phoneme processing difficulties observed , the extent to which they may be modality specific and/or influenced by attention , and their potential effects on language and cognitive function in AS.
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SPEECH PERCEPTION IN ASPERGER SYNDROME
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Dunn , L. , & Dunn , M. (1981). Peabody Picture Vocabulary Test- Revised manual. American Guidance Service: Circle Pines , MN. Gardner , M. F. (1979). Expressive One- J;rd Picture Vocabulary Test manual. Novato , Academic Therapy Publications.
Goldman , R , & Fristoe , M. (1969). Goldman- Fristoe Test of Articulation. American Guidance Service. Gravel j. (1994). Auditory integration training: placing the burden of proof. of Speech- Language
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Howlin , P. (2003). Outcome in high- functioning adults with autism with and without early language delays: implications for the differentiation between autism and Asperger Syndrome. Journal of Autism and Developmental Disorders 33(1), 3- 13. British Jones , P., & Kerwin , R (1990). Left temporal lobe damage in Asperger s syndrome. 156 , 570- 572. Journal of Psychiatry, Katz j., & Fletcher , C. (1998) Phonemic Synthesis Test. Vancouver , WA: Precision Acoustics. Keith , R (1994). SCAN-A: A Testftr Auditory Processing Disorders in Adolescents and Adults. San Antonio , TX: Psychological Corporation. Keith (2000). SCAN- C: A Test for Auditory Processing Disorders in Children: Revised. San Antonio , TX: Psychological Corporation. Kemp, D. (1978). Stimulated acoustic emissions from within the human auditory system. , 1386- 1391. Journal of the Acoustical Society of America Klin , A. (1991). Young autistic children s listening preferences in regard to speech: a possible
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Konig, C. & Magil- Evans , Asperger syndrome.
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and language skils in adolescent boys with
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Landa ,
R (2000). Social language use in Asperger Syndrome and high- functioning autism. In Klin , A. , Volkmar , F. , & Sparrow , S. (Eds. Asperger Syndrome (pp. 125- 155). New York: The Guilford Press. Lindamood , P. , Bell , N. , & Lindamood , P. (1997). Sensory- cognitive factors in the controversy over reading
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Luria , A R (1976). Basic Problems of Neurolinguistics. The Hague: Mouton. McCullagh , P. , & Nelder j. (1989). Generalized Linear Models. London: Chapman and Hall. Merzenich , M. Jenkins , W Johnston , P. , Schreiner , C. , Miler , S. , & Tallal , P. (1996). Temporal processing deficits of language- learning impaired children ameliorated by training. Science 271 , 77 - 81.
Miceli , G. , Caltagirone , C. , Gainotti , G. , & Payer-Rigo , P. (1978). Discrimination of voice versus place contrasts in aphasia. Brain and Language , 47-51. Ornitz , E. M. (1974). The modulation of sensory input and motor output in autistic children. , 197-215. Journal of Autism and Developmental Disorders Rosenhall , U. , Nordin , v. , Brantberg, K. , & Gilberg, C. (2003). Autism and Auditory Brain Ear and Hearing, 24(3), 206-214. Stem Responses. (2002). Brief Report: Attention differences in Schatz , A.M. , Weimer , A.K. , & Trauner , D. Asperger Syndrome. , 359- 360. Journal of Autism and Developmental Disorders Schuknecht , H. (1974). Pathology of the Ear (pp. 389-403). Cambridge , MA: Harvard University Press. Shriberg, L.D. , Rhea , P. , McSweeny, j.L. , Klin , A , Cohen , DJ., & Volkmar , F.R (2001). Speech and prosody characteristics of adolescents and adults with high- functioning autism and asperger syndrome.
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1097- 1115. Studdert- Kennedy, M. , & Shankweiler , D. (1970). Hemispheric specialization for speech per, 579- 594. ception. Journal of the Acoustical Society of America Tager- Flusberg, H. (1981). On the nature of linguistic functioning in early infantile autism. , 45-56. Journal of Autism and Developmental Disorders Tallal , P. , Stark , R , & Mellits , D. (1985) The relationship between auditory temporal analysis and receptive language development: evidence from studies of developmental language disorder. Neuropsychologia 23(4), 527- 534. Tanguay, P. E. , Edwards , R M. , Buchwald j., Schwafel j., & Allen , V. (1982). Auditory brainstem evoked responses in autistic children.
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Wechsler , D. (1991). WISC- III R manual. New York , Psychological Corporation. San Antonio TX: Psychological Corporation (Harcourt). Wing, L. (1981). Asperger s syndrome: a clinical account. Psychological Medicine , 115- 129. Zilbovicius , M. , Boddaert, N. , Belin , P. , Poline , J- , Remy, P. , Mangin , J-F. , Thivard , L. Barthelemy, C. , & Samson , Y. (2000). Temporal lobe dysfunction in childhood autism: a PET study.
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Mailing Address:
Dr. Dana Boatman Department of Neurology
TheJohns Hopkins HosPital 600 North Wolf Street, Meyer 2- 747 Baltimore, Maryland 27287 US.A. Telephone: (470) 955- 0227; Fax: (470) 955- 0757 Email: dboatma(fPjhmi. edu
ACKNOWLEDGMENTS This study was supported by the National Alliance for Autism Research. Special
thanks to Dr. D. Miglioretti for the statistical analyses , and to Drs. B. Gordon , A. Zimmerman , and S. Reich for helpful discussion.
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Executive Function Deficits in Children with
Autism
Ellen Bialystok , Simon B. Sherry, Stuart Shanker and
Judith Codd
Keywords: Executive functioning, Autism , Inhibition , Dimensional change card sort task Abstract.
A group of 8-year- old children with autism was compared to a group of tYPically-
develoPing 4-year- olds (approximately matched for verbal mental age)
and to a group of tyPically-develoPing 8-year- olds (matched for chronological age) on a computerized version of the dimensional change card sort task. This task requires children to classif a set of stimuli first by one dimension (pre- switch phase) and then to reclassif the same stimuli by another contrasting dimension (post-switch phase). There were four conditions that difred in the nature of the
demands required by the post-switch phase. Children with autism were both quantitatively and qualitatively difrent from the other children in the post- switch phase. They obtained the lowest scores across the four conditions and were the only group to experience difculty in the simplest condition in which only a single perceptual feature was used to sort the stimuli. Nonetheless, the children with autism solved the rule used to sort the stimuli and the processing
most difcult condition based on a conceptual
classifcation better than the tyPically- develoPing
year- olds, once vocabulary level was controlled. The results are discussed in terms of the role of inhibition in the executive
fUnctioning of children with autism.
For children with autism ,
cognitive deficits are only one aspect of a complex set of symptoms , including ritualism , behavioural rigidity, perseveration , social difficulties narrow focus , impulsivity, and communication impairments (American Psychiatric Association , 1994). The cause of the cognitive deficits in particular is a matter of controversy. Planning and regulation (e. , Adrien et al. , 1995; Hughes , 1996), metarepresentation (e. , Baron- Cohen , 1994; Baron- Cohen , Leslie , & Frith , 1985), inhibitory control and selective attention (e. , Hughes & Russell , 1993; Ozonoff & Strayer 1997), working memory (e. , Boucher , 1981; Boucher & Lewis , 1989), and weak central coherence (e. , Frith , 1989; Frith & Happe , 1994), have all been considered as the locus of the cognitive deficit implicated in the pathogenesis of autism.
Although children with autism present a common, identifiable symptom profie (American Psychiatric Association, 1994), the course , severity, aetiology, and expression of autism is heterogeneous (e. , Pelios & Lund , 2001).
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Two primary hypotheses have been proposed for the cognitive deficits of autism:
the theory of mind (TOM) or " mindblindness " hypothesis , and the executive dysfunction hypothesis. According to the TOM hypothesis , autism is caused by impair-
ments in intuiting and representing mental states on both an intrapersonal and an interpersonal level (Baron- Cohen , 1989 , 1995; Perner , Frith , Leslie , & Leekam 1989). Advocates of this view contend that TOM deficits render the mutual understandings , shared feelings , surmised intentions , and jointly held beliefs characteristic of everyday social relationships and interactions inaccessible to children with autism (Baron- Cohen , 1989). This hypothesis was proposed by Baron- Cohen , Leslie , and
Frith (1985) when they discovered that many children with autism had diffculty in passing the Sally- Anne false belief task (Wimmer & Perner , 1983), a classic measure of TOM. Since then , extensive evidence has accumulated supporting this interpretation (Grant, Grayson , & Boucher , 2001; Happe , 1995; Or & Yirmiya , 1993; Yirmiya Erel , Shaked , & Solomonica- Levi , 1998). There is a substantial literature supporting this view , but several issues challenge the TOM hypothesis. Foremost among these are concerns about reliability and validity. Regarding reliability, not all children with autism are characterized by TOM deficits. For performance on first- order TOM tasks , Dahlgren and Trilingsgaard (1996) report a
10% failure rate among 20 children with autism (age range = 6. 3 to
Prior , Dahlstrom , and Squires (1990) report a 40% failure rate among 20 individuals with autism (age range = 5. 0 to 25. 0); and , Reed and Peterson (1990) report an 85% failure rate among 13 participants (age range = 4. 3 to 29.1). Therefore , some children with autism maintain at least some TOM abilities , undermining its causal role in the disorder. Regarding validity, children with autism demonstrate proficiencies in daily living that would presumably be impossible with their alleged subnormal TOM abilities (Frith , Happe , & Siddons , 1994; Happe , 1994). Some researchers (e. , Happe , 1995; Hobson , 1991) contend that the poor performance of these chil15. 5);
dren on TOM tasks is (in
part) an artefact of the structure of those tasks that chal-
lenges other difficulties that children with autism experience. Even children who pass these tasks may do so by using compensatory strategies that enable them to mimic appropriate responses without fully appreciating the mental states of others (Frith Morton , & Leslie , 1991; Happe , 1993 , 1995). The relation between TOM and autism may be mediated by language ability. A study by Peterson and Siegal (1995) revealed that 17 of 26 patients with prelingual deafness (age range = 8 to 23), all with normal intelligence , failed a simple TOM task. Using more precise linguistic measures , de Viliers (1999) has identified the syntactic ability to use that- complement clauses as the single best predictor of performance in TOM tasks. She speculates that this linguistic achievement might be one factor in the failure of children with autism to solve these tasks. Children with autism frequently
suffer from poorly developed
language competence , and several studies have
demonstrated a positive relation between verbal mental age and performance on TOM tasks (Eisenmajer & Prior , 1991; Leekam & Perner , 1991).
An alternative to the TOM hypothesis is that executive dysfunction is the primary explanation for the cognitive deficits typical of autism (Bryson , Landry, &
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Wainwright, 1997; Pennington & Ozonoff, 1996). ' Beginning with the seminal investigation of Hermelin and O' Connor (1970) and subsequently replicated in numerous studies , it has been shown that individuals with autism consistently perseverate on a well- known measure of executive dysfunction: the Wisconsin Card- Sorting Task (WCST) (Bennetto , Pennington , & Rogers , 1996; Ozonoff, 1995; Ozonoff & McEvoy, 1994; Ozonoff et al. , 1991; Prior & Hoffman , 1990; Rumsey, 1985; Rumsey & Hamburger , 1988; Shu , Lung, Tien , & Chen , 2001; Szatmari , Tuff, Finlayson Bartolucci , 1990). Zelazo Jacques , Burack , and Frye (2002) extended these results by
showing that severely impaired children with autism perseverated on the dimensional change card sort task , similar to the WCST , but that there was no relation between their performance on the card sort task and TOM tasks. Perseveration on these tasks is regarded as a failure to inhibit a well- rehearsed , prepotent response and a tendency " to persist with a specific strategy, despite corrective feedback" (Ozonoff 1995; Shu et al. , 2001 , p. 170). Executive dysfunction comprises impairments in goal- directed , future- oriented
mental operations that are mediated by the frontal lobes and involve planning, attention , inhibition , cognitive flexibility, working memory, and organized searching (McEvoy, Rogers , & Pennington , 1993; Ozonoff, 1995; Pennington et al. , 1997). Using criteria such as these , Ozonoff andJensen (1999) point out that the majority of studies on children with autism have uncovered evidence of executive dysfunction. battery of tasks administered to children with autism , attention-
In a wide- ranging
deficit/hyperactivity disorder (ADHD), dyslexia , and mild mental retardation Ozonoff et al. (1991) found that only the executive dysfunction measures (i. , the WCST and the Tower of Hanoi) discriminated among groups. Although first- order TOM tasks correctly classified 65% of the 23 children with autism (age range = 8. 0), executive dysfunction measures correctly classified 80% of the children with autism.
to 20.
Recent research has examined the cognitive architecture underlying the executive dysfunction hypothesis in an effort to determine the exact nature of the impairment. Some studies (e. , Noterdaeme , Amorosa , Mildenberger , Sitter , & Minow 2001; Ozonoff & Jensen ,
are related to
1999) have considered how various executive components
different developmental disorders (e.
, autism vs. attention-
deficit/hyperactivity disorder), while others have investigated how the cognitive processes encompassed by the executive dysfunction hypothesis relate to autism. For example , Russell and his colleagues have shown that children with autism struggle with (1) disengaging attention from a focal object (Hughes & Russell , 1993), (2) attentional set- shifting and planning (Hughes , Russell , & Robbins , 1994), (3) choosing between equally weighted alternatives (Russell , Jarrold , & Henry, 1996), (4) encod-
'Unlike Ozonoff , Pennington , and Rogers (1991) or Pennington et al. (1997), we do not consider executive dysfunction to be the primary cause of autism. We do , however , believe executive dysfunction to be an important aspect of autism , functioning as a contributing factor but not as a causal agent. Thus , like Liss et al. (2001), we maintain that " although impaired executive dysfunction is a commonly associated feature of autism... (it) is unlikely to cause (autism)" (p. 261).
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ing rules in a verbal form (Russell Jarrold , & Hood , 1999), and (5) following arbitrary procedures (Biro & Russell , 2001).
Problem solving inevitably requires an intentional focus on some parts of a problem display, some aspects of an associated mental representation , or some portion of
a knowledge base. Identifying the details relevant to a problem entails excluding
irrelevant ones that may appear
to be connected but are actually misleading.
Attention to these irrelevant cues must be inhibited. As Chao and Knight (1997 67) point out: " One of the main functions of the attentional system is to enable cognitive processing to focus on stimulus attributes and ignore or inhibit irrelevant aspects. " The ability to control attention and inhibition in this matter develops significantly in the first five years (Diamond , 2002; Diamond & Taylor , 1996; Gerstad Hong, & Diamond , 1994) and has been credited for a variety of important changes in problem solving (Dagenbach & Carr , 1994; Dempster , 1992; Harnishfeger & Bjorklund , 1993). The dimensional change card sort task , developed by Zelazo and his colleagues (e. , Zelazo & Frye , 1997) and administered to children with autism (Zelazo et al. 2002) provides a means of examining the development of these processes. Children are required to sort a set of cards by one dimension and then to re- sort the same cards by a competing dimension. Thus , the feature that is attended to in the first stage must be ignored in the second. This is difficult for typically- developing children and they are not successful until they are about 5-years old. The error is to continue to sort the cards according to the pre- switch rule.
We explored the problem in more detail by creating a computerized version of the dimensional change card sort task consisting of four conditions , called (1) the colour game , (2) the colour- shape game , (3) the colour- object game , and (4) the function- location game (Bialystok & Martin , in press). The intention was to vary the atten-
tion and inhibition demands of each condition to isolate their role in solving the task. All four conditions required the cards to be reclassified in the post- switch phase , but all four presented different representational (and , therefore , inhibition) problems. One of the conditions , the colour game, was based on a single perceptual feature; two conditions , colour- shape and colour- object, were based on two perceptual features and the fourth condition , function- location , was based on a conceptual feature of the depicted objects. The task difficulty is in re- assigning the stimuli to a new perceptual (or conceptual) category when there is interference from the previously relevant category that needs to be ignored (Bialystok & Martin , in press). The task involves two kinds of inhibition , and the results point out the difference between them. The first response inhibition is the suppression of a practised response between a stimulus and response that needs to be overridden. In a study or association by Jacques , Zelazo , Kirkham , and Semcesen (1999), children observed as a puppet performed the classification and the child simply decided if the puppet sorted correctly or not. This procedure eliminated the need for children to carry out the motor response and therefore eliminated the need to inhibit this response in the post- switch phase. Nonetheless , performance in this modified task was no better than that on the standard version and they concluded that inhibition was not a factor in solving the
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problem. Similarly, Perner (2001) demonstrated that a control condition that requires reversing the destination of the card following the switch , even in the absence of con-
flicting information from the targets , does not improve children s performance. This is the kind of inhibition required in the colour game. The second conceptual inhibition, is the suppression of attention to a salient but
competing mental representation. This is the inhibition central to the other three conditions- attention has to be shifted from one stimulus feature (e. , colour) to another (e. , shape), even though the initial feature (colour) remains present and salient. The function- location condition is more difficult than the other two because the classifications are not based directly on perceptual features-children need to
identify the objects and then classify them to one of the two categories (Bialystok & Martin , in press). At the same time , the classification itself is difficult, and children make many errors in both the pre- switch and post- switch phases. This condition therefore , requires higher levels of representation ability than the other three to identify, classify, and then re- classify the stimuli. The interpretation that conceptual inhibition is responsible for problem difficulty is supported by research that has assisted children s focus on the relevant dimension in the post- switch
phase. This can be achieved by removing one of the stimulus fea-
tures during the post- switch phase (Bialystok & Martin , in press; Zelazo & Frye , 1997; Zelazo & Jacques ,
1996), questioning children about the feature to which they are
Redbond , Houston- Price , & Cook , 2000), or requiring children to label the relevant dimension on each sorting trial (Kirkham , Cruess , & Diamond , in attending (Towse ,
press). These methods all significantly improve performance and point to the role conceptual inhibition as the primary difficulty in the task. In sum , the dimensional change card sort task includes at least three kinds of processing demands: response inhibition , conceptual inhibition , and representational complexity. The potential to isolate these three processes makes the task a promising test of the kind of executive process that might be impaired in children with autism. If children with autism have a specific impairment in the ability to inhibit attention to prepotent responses (response inhibition) or to competing mental representations (conceptual inhibition), then they wil find the task difficult. Comparing their performance to the different conditions of this problem and to the performance of chil-
dren who are comparable in verbal mental age and chronological
age wil help to
identify one of the core cognitive deficits in autism. The hypothesis was that children with autism would be delayed in their ability to solve the problems requiring conceptual inhibition and that increasing demands on representational complexity would disproportionately disrupt their performance relative to the typically- developing children. In contrast , we expected no relative deficit in their performance on the colour game that depends primarily on response inhibition.
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Method Participants This study compared a group of children with autism and two groups of typically-
developing children on their ability to solve the four conditions of the dimension change card sort task. The first group included 15 children (14 boys and 1 girl; mean age = 8;4 years) who had received a diagnosis of Autistic Disorder (American Psychiatric Association , 1994). The cognitively- matched control group included 184year- olds (9 boys and 9 girls; mean age = 4;7 years) and the age- matched control group included 11 8-year- olds (5 boys and 6 girls; mean age = 8;0 years). Parents , educators , and clinicians verified diagnoses for children with Autistic Disorder and relevant records were consulted whenever possible. Participants were recruited through announcements to service organizations , day care centers , public schools , and special programs in major urban centres. Participants ' socio- economic status ranged from middle class to upper-middle class. All participants had received
their diagnosis of Autistic Disorder from qualified medical experts according to DSM- IV (American Psychiatric Association , 1994) diagnostic criteria. Participants were free from psychoactive medication and no participants were diagnosed with co-
morbid mental disorders.
Instruments Forward Digit Span. The forward digit span was used to assess verbal short- term memory capacity (WISC- R; Weschler , 1974). A sequence ofrandom digits was read twice , and the child was asked to repeat this sequence to the experimenter. The test began with a sequence of three digits , and the number of digits increased by one after
each correct trial. If an error occurred, a second sequence was given at the same length. Testing ended when two consecutive errors were made at the same length. The number of digits in the last correct sequence is the forward digit span score. One child with autism was unable to perform the forward digit span. Ravens Coloured Progressive Matrices (sets A , AB , B). The Coloured Progressive Matrices (Raven , Court , & Raven , 1986) was employed to assess visual- spatial abilities (i. , abilities to arrange spatial perceptions into semantically related wholes) and
to assess comparison- making skils. The task is comprised of 36 pictures (organized as 3 sets of 12 items), each of which has a portion missing. Children must select which of six possible segments correctly completes the picture. The score is the total number of items out of 36 that the child completes correctly. One child with autism was unable to complete the task. Peabody Picture Vocabulary- Revised (PPVT- R). This task was used to assess
receptive vocabulary and verbal mental age (Dunn & Dunn , 1981). The child is asked to select one picture from a set of four that ilustrates the word spoken by the exper-
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imenter. Items become more difficult as testing progresses. Testing continues until the participant makes six mistakes in eight consecutive responses. Raw scores are converted to standard scores by means of normalized tables. Computerized Dimensional Change Card Sort Task. This task included four con-
ditions (games) that were presented to the children on an IBM Thinkpad. A black cover was placed over the keyboard exposing only three keys: the " , the " , and the spacebar. The " W" and " P" keys were selected for their symmetry to the screen and were covered with keycaps clearly marked " X" and " , respectively. The spacebar was covered with a blank white keycap. An animated character appeared on the screen before each new game and each switch phase in order to explain the rules of each game to the child. For each game , the stimulus to be classified appeared in the centre of the screen and children were given instructions about which key to
press. For three of the games , small target stimuli also appeared near the bottom of the screen directly aligned with one of the response keys. This configuration is ilustrated in Figure 1 for each of the four conditions. The child was allowed three practice trials with feedback. If the child was incorrect on one of the practice trials , the rules of the game repeated automatically. This continued until the child was able to perform the three practice trials accurately. The experimenter remained with the child and repeated instructions if the child did not fully understand the task.
a. Colour Task
b. Shape- Colour Task
OR8
c. Colour- Object Task
FIGURE 1: Sample of stimuli for four conditions.
d. Function- Location Task
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a. Colour Game
The children were told to watch for either a blue square or a red square. In the first set of rules , they were told to press the button with the X on it when the red square appeared , and to press the button with the 0 on it when the blue square appeared. There were 10 items in this set , including equal numbers of red and blue squares presented in a random order. Following this , they were told that the rules had now switched and they were to press the X if the blue square appeared , and the 0 if the red square appeared. Again , there were 10 trials , and the squares were presented in a random order. The order of these rules was counterbalanced across all children.
b. Colour- Shape Game This condition , consisting of red and blue circles and squares , was presented as the colour game or the shape game in counterbalanced order. If the colour game was first , the child was told to put all the blue pictures in the box with the blue picture on , and all the red pictures in the box with the red picture on it. Two boxes appeared at the bottom of the screen with the appropriate picture on the box, and the image to be sorted appeared in the middle of the screen. If the boxes had a red square and a blue circle on them , then the pictures to be sorted were red circles and blue squares. The child pressed the button closest to the box that the picture was to be placed in.
The picture visually dropped into the appropriate box. When the first part of the game was completed , the animated figure appeared again and explained the post-
switch rules. In this example , the new game was the shape game, and children were told to place the squares in the box with the square on it , and the circles into the box with the circle on it. Again , there were 10 trials in each of the two games , consisting of five circles and five squares presented in a random order. The programme randomized whether the sorting stimuli were blue circles and red squares or red circles and blue squares.
c. Colour-Picture Game
This task was identical to the previous condition except that the stimuli were red or blue rabbits or flowers.
d. Function-Location Game Unlike the previous three conditions , the sorting dimensions in this game were not perceptual features but functional properties of the stimuli. In the first part of the
"We did not expect any difference between these two conditions but wanted to vary the kind of stimuli that was used.
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game , the children had to sort the pictures based on whether they would play with the item or wear the item. All 10 pictures clearly belonged to one category or the other (these were: a bicycle , a skateboard , a pail and shovel , a skipping rope , a kite a pair of slippers ,
a nightgown , a bib , ballet slippers , and baby pyjamas). The post-
switch rules required the child to sort the
pictures based on whether these items
belonged inside or outside the house. The target stimuli on the sorting compartments were a winter jacket (wear , outside) and a teddy bear (play, inside). There were items in each of the two games and the order (function and location) was counterbalnaced across subjects. The task demands change across these conditions. The colour game requires response inhibition to resist placing the card in the previously correct manner but no conceptual inhibition because there is only one possible dimension to which to attend , namely colour. Representing this rule is also straightforward. The colourshape and colour object games require response inhibition because , like the colour game , each card must be placed in the box opposite to that used in the pre- switch phase. Additionally, however , these conditions require conceptual inhibition because the dimension that previously defined the correct placement is stil present but is now misleading. The representation demands require the ability to represent two perceptual dimensions. The function- location game has the same demands for response inhibition and conceptual inhibition as do the two previous games , but the representational demands are more difficult because the classification needed is based on functional properties that must be conceptualized from the pictures rather simple perceptual attributes.
The conditions were presented in the fixed order described above but items were randomized within the games. The order of games (e. , colour versus shape) within conditions was counterbalanced. The scores were the number of correct classifications out of 10 in each of the pre- switch and post- switch phases of each game.
Procedures The children were tested individually during two separate sessions that lasted roughly 25 to 35 minutes. Testing sessions were self- paced; breaks were permitted to ensure attention and co- operation. During Session 1 ,
participants received the for-
ward digit span , the Ravens Matrices and the PPVT- R. During Session 2 , participants completed the computerized dimensional change card sort task.
Results Children s scores on the background cognitive measures are reported in Table A one-way ANOVA for digit span scores indicated that the difference between the groups was not significant F(2 42) = 2.
~.
~. 037- 056
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~.
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ELLEN BIALYSTOK, ET. AL.
Table 1: Mean scores and stadard deviatons on cognitive taks by group
Group Digit Span PPVT Autism year- olds year- olds
2 (1.5) 9 (1.6) 5.4 (0.
43. 7
Raw PPVT Standard 50. 8
Ravens
67.4 (14.
117.0 (17.8)
18. 21 (7. 7) 12. 7 (5.
95. 3
105.1 (15.1)
23.1 (5.
(18.4)
(11.0)
(13.4)
PPVT raw scores and standard scores are presented in Table 1. PPVT raw scores reflect absolute performance levels. Although PPVT standard scores (i. , the normalized calculation of PPVT raw scores in terms of the child' s age) are generally
more meaningful because they allow children to be compared across ages , they are not utilized in this study (but are reported in the table) because a standardized conversion according to chronological age is inappropriate for children with autism. Predictably, a one- way ANOVA for group on these standard scores indicated a significant difference 42) = 73. 0001 , and Duncan contrasts revealed that the 4- year- olds and 8 year olds levels were not significantly different from each other but the children with autism scored significantly lower than the other two groups. This is the expected finding, because the purpose of the standard scores is to adjust the raw scores according to age of typically- developing children , making them all
equivalent irrespective of age. A one- way ANOVA on PPVT raw scores was used to determine the relative proficiency of the autistic and typically- developing groups without considering age dif43) = 35. 0001 , and Duncan contrasts revealed three distinct levels. Therefore , the receptive vocabulary of the children with autism is more impoverished than that of typically developing 4-
ferences. This analysis showed an effect of group,
year- olds in absolute (raw) terms. A one-way ANOVA for the total score on the Ravens Matrices revealed an effect 0004 , caused by the difference between the 8-year, 42) = 9.45 of group, olds who scored the highest and the 4- year- olds who scored the lowest. These scores are reported in Table 1. The children with autism performed the same as typicallydeveloping children on the Ravens Progessive Matices , a test of nonverbal intelligence , but were significantly lower than the two control groups in a test of receptive vocabulary knowledge (PPVT).
Results for the card sort task are analysed in two ways. The traditional procedure is to determine a criterion level of performance and classify children as either passing or failing the post- switch phase (Zelazo & Frye , 1997). The present analyses use both the conventional pass- fail categories and a more detailed three- way classification that includes a category for guessing. Second , to obtain a more graded understanding of the results , analysis of variance and covariance was used to determine the effect of group and task differences on performance.
Children were classified into one of three categories based on their score in the post- switch phase of each condition. Children who correctly sorted between 7 and 10 4Another control group consisting of 5-year- olds , not reported in this paper , scored exactly the same as the children with autism on the Ravens Matrices but was even higher than the 4-year- olds included here on the PPVT. Therefore , the 4- year- olds were considered to be a more appropriate control group.
~. 037- 056
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=.
-( .
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EXECUTIVE FUNCTION IN AUTISM items in the post- switch
phase of a particular game were classified as " Correct" responders for that game; children who sorted between 4 and 6 items correctly were called " Chance " responders; and those who correctly classified only 0 to 3 items in were designated as " Perseverators " for that game. This adaptation of the usual binary classification is more precise because it enables a distinction to be made between children who fail because they perseverate and those who fail because the post- switch
they respond at chance. The combination of these two non- correct the usual pass- fail
categories yields
distinction. The number of children in each category for each of
the games is reported in Table 2. The chi- square analyses , conducted for both the two- way and three-way classifi-
cation of responders , indicate the extent to which the distribution across the categories is the same for the three groups. The results are indicated in the table beside the distribution for each condition. Chance responding was rare , and the consistency of the analysis for both the two- and three- category classification suggests that guessing was not a problem , or at least , not a problem specific to only one of the groups. The only distribution to differ from chance is the colour condition in which the children with autism were disproportionately weak. For the other three conditions , the proportion of children passing and failing was the same. The result does not change if the chi- square analysis compares only the children with autism and the 4-year- olds for their likelihood of passing and failing in each condition. Again , the distribution is 01. Therefore , the responses of different only for the colour game , X' (1)= 6. the children with autism are qualitatively different from those in the other two groups for the colour condition but the same as the other children for the other three. Although children passed the other three games in equivalent proportions , their relative success on these games may stil be different. Therefore , analysis of variance was used to provide more detail about children s performance. The mean scores out of 10 for the pre- and post- switch phases of each condition are displayed in Figures 2 and 3 respectively. A 3- way ANOVA for group (3), condition (4), and phase (2) Table 2: Distrbution
of responses by group on the computeried dimensional change card sort tak
Game
Group
Correct (Pass)
Autism years years Colour- Autism years Shape years Colour- Autism years Object years Function- Autism Location years years
Colour
Fail
Chance
Perseverator
Pass- Fail df= 2 12.
4.42
2 3- Category df= 4
002
14.4
5.47
006
~.
p~
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p~
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ELLEN BIALYSTOK, ET. AL.
F(2 41) = 18.10 0001 , MSE = 11.39 , condition 0003 , MSE = 5. , and phase F(1 41) = 78.12 0001 , MSE= 12. 27. The group effect was that all three groups were significantly different from each other , with the highest scores obtained by the 8- year- olds and the lowest by the chil-
indicated main effects of group,
F(3
123)
dren with autism. The condition effect indicated that the colour condition was easier than the other three , which did not differ from each other. The phase effect reflected the higher performance on the pre- switch problems.
The children with autism obtained lower scores than the other children in all four conditions. However , the children with autism also had lower receptive vocabulary scores than the other children , and this disadvantage in verbal skil may have been partly responsible for their performance. Therefore , scores were re- examined using
EJ 8 years
4 years
Autism
Colour
Colour- Shape Colour - Obj
ect
FunctionLocation
FIGURE 2. Means scores in pre- switch phase by condition and group.
8 years
4 years Au ti sm
Colour
Colour
Colour
FunctionLocation
FIGURE 3. Means scores in post- switch phase by condition and group.
~.
~. 037- 056
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5 : 09
~.
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EXECUTIVE FUNCTION IN AUTISM
ANCOVA analysis with PPVT Stanine scores as the covariate to establish performance levels that might be obtained assuming relative equivalence of vocabulary lev-
els. The least squares means generated from this analysis for each group and condition are presented in Table 3. Note that these means do not correspond to those plotted in Figures 2 and 3 because they have been adjusted for vocabulary ability. Because the executive processing demands of each condition were different , sep-
arate analyses were conducted for each to focus on group differences in performance of these specific problems when vocabulary knowledge has been controlled. Consequently, there were four two-way ANCOVA (PPVT covariate) analyses for phase (pre- and post- switch) and group. For the colour game , there was an effect of , 39) = 6. 003 , MSE = 4. , in which all three groups were differgroup, ent from each other , the 8- year- olds achieving the highest and the children with autism receiving the lowest scores. The colour- shape game also revealed an effect of 39) = 3. , MSE = 7.88 , this time indicating that both the 8- yeargroup, olds and 4- year- olds (not differing from each other) performed better than the children with autism. The colour- object game produced only a main effect of phase 39) = 13.14 0008 , MSE = 10.17 , in which pre- switch scores were consistently higher than post- switch for all the children. Finally, the function- location condition , MSE = 7.96 , and phase F(1 39) revealed an effect of group, F(2 39) = 4. = 7.27 01. The 4-year- olds obtained the lowest scores with no difference between the 8- year- olds and children with autism. Pre- switch trials were reliably better than post- switch trials for all the children.
Discussion A group of 8- year- old children with autism was compared to a group of typicallydeveloping 4-year- olds who were expected to match for mental age and to a group of typically- developing 8- year- olds who were matched for chronological age on a
computerized version of the dimensional change card sort task. All the children performed similarly on a digit span test, a rough guide to verbal short- term memory capacity. The children with autism were not significantly different from either the 4year- olds or the 8- year- olds on the Ravens Progressive Matrices , although these two groups were different from each other. Scores for receptive vocabulary, however indicated an important disparity between the groups. This is an unfortunate outcome but it may be unavoidable. The standardized receptive vocabulary scores for the
Table 3: Least squares means (PPVT Covarate) and stadard errors on the computeried dimensional change card sort tak by group Colour
Group Autism years years
Pre
Post
9 (. 71) 8.4 (. 52) 6 (.49)
7.1 (.85)
5 (1.2) 5 (. 82)
ColourPre Post
ect ColourPre Post
2 (. 87) 8 (. 63) 9.1 (. 60)
6 (.63) 9.4 (.46) 8 (.44)
2 (1.7) 5.4 (1.2) 7.4 (1.2)
2 (1.7) 7 (1.3) 5.4 (1.2)
F unction- Location Pre Post 8.4 (. 75) 6 (. 55) 7 (.52)
5 (1. 7)
3 (1.2) 2 (1.2)
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year- old children with autism was lower than that for typically- developing 4- yearolds , but matching to a control group younger than 4-years old would not have been reasonable for the other tasks. A group of 3- year- olds , for example , may have provided a better match in receptive vocabulary for the children with autism ,
but they would not have provided a match on the Ravens Progressive Matrices and their performance on the experimental sorting task would likely have been unreliable , if they could do it at all. Our solution , therefore , was to use analysis of covariance to statis-
tically control for initial differences in levels of vocabulary knowledge. The data were examined by means of chi- square analysis , ANOVA , and ANCOVA to investigate different aspects of the results. First, the chi square analyses compared the proportion of children who passed or failed each of the conditions across groups. This proportion was only different for the colour game , where a significantly larger group of children with autism failed the post- switch phase. This pat-
tern indicates a qualitative difference in the way in which children in these three groups solve this problem. Importantly, the chi- square analysis of the three-way classification indicated that very few of the children were chance responders , although the majority of guessers were children with autism. Second , the ANOVA analysis showed that the scores of the children with autism were lower than those of all the other children across all the conditions. The main effect of group also indicated the superiority of the 8- year- olds for all the conditions. This was a difficult task , especially for the children with autism. Finally, the ANCOVA provides more detailed understanding by comparing the performance of each group on each condition controlling for initial differences in
vocabulary knowledge. These results showed that the children with autism performed lower than the other children in both the colour game and the colour- shape game , but were not lower on the other two games. In fact , these children were better than the 4- year- olds in the function- location condition. Once corrections for vocabulary knowledge have been made , the children with autism were only slightly disadvantaged on these semantically complex conditions based on more sophisticated representations. Therefore, initial deficits in language proficiency account for some but not all of the diffculty that children with autism experience on this task. Evidence that children with autism score poorly relative to typically- developing children on a cognitive task is not surprising; it is more important to identify the specific deficit responsible for that poor performance. Consider the three processes involved in solving this task: representation , response inhibition , and conceptual inhibition. The 4-year- olds experienced difficulties with representation and were particularly challenged by the function- location game; the children with autism experienced difficulties with response inhibition even though the colour game was easy for the other children; and all the children , including the 8-year- olds , found the conceptual inhibition demands to be challenging, as even this oldest group did not achieve ceiling performance on the most difficult condition. Three aspects of this pattern are striking. First , children with autism are distin-
guished by their difficulty in inhibiting a familiar or learned response association to a single perceptual cue as in the colour game. This finding is congruent with a grow-
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ing body of research (e. , Bryson , Landry, & Wainwright , 1997) implicating executive function deficits , especially inhibitory control (e. , Hughes & Russell , 1993), in the pathogenesis of autism. Second , when initial vocabulary levels were controlled children with autism performed as well as typically- developing 8-year- olds and significantly better than typically- developing 4- year- olds on a problem that was based on a complex conceptual classification. Hence , the ability of children with autism to represent conceptual information ,
once vocabulary had been adjusted ,
was not
impaired. This optimistic interpretation is confirmed by their performance on the Raven s Matrices. Together , these results locate the source of difficulty for the children with autism in the need for inhibition , particularly for response inhibition. Finally, the surprising finding that typically- developing 8- year- olds continue to perseverate on the dimensional change card sort task , especially in its more complex
development of inhibitory executive processes is more protracted than previously believed (e. , Zelazo , Frye , & Rapus
representational forms , suggests that the
1996). In the executive dysfunction perspective on autism , inhibitory control is a primary source of cognitive impairment (e. , Hughes & Russell , 1993). Our results corroborate this view but point to a particular deficit in response inhibition that is not evident in the other typically- developing children. Children with autism also have less control over conceptual inhibition than do typically- developing children , but
only when the conceptual basis for the classification is easy (colour- shape game). As that conceptual basis becomes slightly richer , requiring more detailed mental repre-
sentations , the children with autism do just as well as the other children if language proficiency is taken into account (colour- object game) and better than 4-year- olds if the classification is based on functional categories instead of perceptual ones (function- location game). Future efforts aimed at specifying the exact inhibitory executive
children with autism may want to distinguish between response inhibition and conceptual inhibition so as to enable precise conclusions. The results point to an executive deficit in children with autism in which they have difficulty in disengaging from a simple ongoing cognitive routine and making an adjustment in that routine. Children with autism are compromised both in the extent to which inhibition processes are functional and in the nature of inhibition processes that are impaired. These children not only experienced deficits in performance on all tasks requiring conceptual inhibition , but also experienced deficits in a condition requiring response inhibition. These inhibition processes are central to the executive system that is responsible for planful and controlled problem solving. Such executive function deficits may contribute to social communication impairments in children with autism. Unable to flexibly and efficiently disengage and coordinate attention , the rapid shifts and constant changes that typify social communication confuse children with autism (e. , Courchesne et al. , 1999; McEvoy processes impaired in
et al. ,
1993).
Autism is a complex disorder influencing many domains , including social difficulties , behavioural rigidity, and communication impairments. Although our results address one notable aspect (i. , inhibition of attention) of one important component
),
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ELLEN BIALYSTOK, ET. AL. (i. , cognitive deficits) of the symptomatology of children with autism , they do not explain the potentially simultaneous involvement of other impairments in different domains. It may be that cognitive deficits (such as inhibition of attention) underlie social difficulties (such as mindblindness) or that social difficulties encourage cognitive deficits or that cognitive deficits and social difficulties emerge in a complex dialectical transaction (Fine , Lumsden , & Blair , 2001). Clearly, no single factor or unitary theory is likely to adequately explain the severity and complexity of autism.
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ment of deliberate reasoning and intentional action. In M. Stamenov (Ed. Language structure, discourse, and the access to consciousness (pp. 113- 153). Amsterdam: John Benjamins. Zelazo , P. D. , Frye , D. , & Rapus , T. (1996). An age- related dissociation between knowing rules Cognitive Development
and using them.
, 37- 63.
Zelazo , P. , &Jacques , S. (1996). Children s rule use: Representation , reflection and cognitive control. In R. Vasta (Ed. Annals of child development (Vol. 12 , pp. 119- 176). London: Jessica Kingsley.
Zelazo , P. Jacques , S. , Burack j.A. , & Frye , D. (2002). The relation between theory of mind and rule use: Evidence from persons with autism- spectrum disorders. Infant and Child Development
, 171- 195.
Address ftr Correspondence:
Ellen Bialystok Department of Psychology York University 4700 Keele Street Toronto,
Ontario, M3J
Canada Email: ellenbr:yorku.
Authors ' Note: This research was supported by a grant (A2559) awarded to the first author from the Natural Sciences and Engineering Research Council of Canada (NSERC).
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Neuropathology and Alterations in the GABAergic System in Autism
Gene J. Blatt , Ph.
Abstract.
The neuropathology of autism primarily
involves limbic system and cerebellar
structures. The neurons of the dentate gyrus and stratum pyramidale in the hippocampal formation are smaller in size and are densely packed and some neurons in the CA sub fields, have reduced dendritic arbors. Research in our laboratory has ftcused on the
GABAergic system in
autism due to initial findings of a statistically signifcant reduction in the density of tHJflunitrazepam labeled benzodiazePine binding sites and of tHJ- muscimol labeled GABA receptors in high binding regions in the hippocampus. The ftrmer study was ftllowed up with a multiple concentration saturation binding study demonstrating a trend for a reduction in the number of benzodiazePine binding sites (change in the Bmax) but normal binding affnity (no change in the Kd). These results suggest possible changes in the modulation ofGABA receptors in the hiPpocampus and, that there may be more widespread effcts of altered GABAergic function in the autistic brain.
Introduction Consistent neuropathological findings in autism directly implicate limbic structures including the hippocampal formation , amygdala and basal forebrain and cerebellar structures including the cerebellar cortex , cerebellar nuclei and the infe-
rior olivary complex (Bauman and Kemper ,
1985 , 1994). Smaller
cell size and
increased cell packing density is found in the hippocampus and in the medial part of the amygdala whereas age- related changes (larger than normal size neurons in children; smaller than normal size neurons in adult) are found in the nucleus of the Diagonal band of Broca in the basal forebrain , cerebellar nuclei and the inferior olivary complex (Bauman and Kemper , 1985). Using the Golgi method , pyramidal cells from the CAI and CA4 hippocampal fields showed reduced complexity and extent of the dendritic arbors (Raymond et al. , 1996). Evidence that the GABAergic system is affected in autism emerged with the finding of decreased numbers of Purkinje cells in the cerebellum (Arin et al. , 1991). These key GABAergic neurons receive excitatory input from olivo cerebellar climbing fibers and parallel fiber input from granule cells and , project to the mostly GABAergic cerebellar nuclei. Despite this important finding of fewer Purkinje cells
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in the autistic brain , there is a paucity of information about the role of the GABAergic system in autism or whether the GABAergic system is altered in other parts of the autistic brain. Thus , our recent findings demonstrated statistically significant reductions in the density of (" H)- flunitrazepam labeled benzodiazepine binding sites and in H)- muscimollabeled GABA receptors in high binding regions of the hippocampal formation of autistic individuals (Blatt et al. , 2001). We further found that the alteration in (" H)- flunitrazepam labeled benzodiazepine binding sites showed a trend for
significance for a decrease in the number of binding sites but having normal affinity to bind the ligand (Blatt et al. , 2002; Guptil et al. , 2003 , submitted). The method and results of this study are summarized below. Taken together , the results from these
studies suggest a new direction in autism research.
Method
Brain Tissue
Brain tissue was obtained from the Harvard Brain Tissue
Resource Center
(HBTRC) in Belmont, Massachusetts. Seven blocks (four autistic and three control) from fresh , frozen hemispheres stored at , measuring 10- 5 mm were cut from the main body of the hippocampus , transported in dry ice to Boston University School of Medicine , and stored in a - C freezer. The study was conducted blind using coded case numbers. Detailed medical histories of every autistic case were on file at the HBTRC. A summary of the cases used in this study appears in Table
Table 1. Clinical Information of Subjects and History Case #
Group
Sex
B 1078
Autistic Autistic Autistic Autistic
Male Male Male Male Male Male Male
B1484 B1664 B2825 B4104 B4188 B4272
Control Control Control
Age
PMI
Cause of Death
14.
Asphyxia Burns Asphyxia Cardiac arrest GSW to chest GSW to Abdomen MVA
Abbreviations: GSW- Gun Shot Wound; MVA- Motor Vehicle Accident; PM 1- Post Mortem Interval , in hours
Saturation binding assay
Tissue was cut coronally at 30 pm on a Hacker/Brights motorized cryostat at
C and thaw
mounted onto 2x3 inch poly-
lysine coated glass slides.
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Hippocampal blocks were cut in rounds of 29 sections. Each round consisted of total" slides for receptor binding (incubation with tritiated ligand), an adjacent " nonspecific " slide (incubation of tritiated ligand with competitive displacer), one slide for Nissl staining, and six spare slides. For most cases two hippocampal sections were mounted per slide. After mounting on a slide , the sections were rapidly dried on a slide warmer , loaded in a slide box with desiccant and stored at - C until assay time.
Slides were separated into " total" and " nonspecific " groups and loaded into appropriate plastic slide racks. Two sections per case were incubated in one of seven concentrations (0. , 0.4 , 0.
, 1.6
, 9. 6
and 28. 8nM)
of 3 (H)- flunitrazepam (specific
activity: 82 Ci/mmol; New England Nuclear) in a 0.17M Tris- HCL buffer (pH 7.4) for 40 minutes at oo c. Nonspecific binding was measured by adding clonazepam (lpM) to the assay baths for the three highest concentrations of ('H)flunitrazepam (Shaw et al. , 1987; Dennis et al. , 1988). All slides for a specific concentration were run simul-
taneously in a single slide rack to ensure that all slides were exposed to the same assay conditions. After rinsing the slides in 50mM Tris- HCL (2xl min) and ddH, (lxlO seconds) at OO
, excess buffer or distiled water was removed by gently tapping
the slides on a paper towel and drying under a stream of cool air (Dennis et al. , 1988; Shaw et al. , 1987). Finally, the slides were placed overnight in a glass vessel contain-
ing desiccant. On the following day, the slides were loaded into x- rays cassettes with a tritium standard (Amersham) and apposed to tritium- sensitive film CH- Hyperfilm Amersham) (Geary & Wooten , 1983). The films were developed after 4 weeks with Kodak D19 developer (4 minutes), fixed with Kodak Rapidfix (3. 5 minutes) at room temperature and air- dried.
Data analysis and Statistics Images of the sections and standards were digitized into the autoradiographic image analysis program , Inquiry (Loats Associates), using a digital camera interface. The tritium standards were used to construct a calibration table for each film cassette and the images of all sections exposed in a x- ray cassette were tagged to a calibration table specific to that cassette. The optical density of specific architectonic regions or lamina in the hippocampal formation were sampled using the Inquiry system and converted , via the calibration table , to femtomoles bound per miligram (fmol/mg) of dry tissue protein. A total of 11 hippocampal lamina from six hippocampal subfields (dentate gyrus (DG), CA3 , CA2 , CAl , pro subiculum (Pros), and subiculum (Sub)) were sampled according to the descriptions of Rosene & Van Hoesen (1987). The eleven lamina sampled were chosen because they showed either statistically significant differences
or trends toward significance in the single concentration assay, or were high binding regions. The lamina sampled were: DG: granule cell layer , inner third of the molecular layer , outer two- thirds of the molecular layer; CA3: pyramidal cell layer;
CA2: pyramidal cell layer; CAl: pyramidal cell layer; Pros: pyramidal cell layer
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molecular layer; Sub: pyramidal cell layer , molecular layer. Plotting the nonspecific
data yielded a linear regression that was subtracted from the total binding measurements (femtomoles/mg tissue) to yield a " specific " binding measurement at each concentration.
The multiple concentration assay utilized a binding curve ilustrating ligand con3 (H)flunitrazepam centration (nM) vs. fmol/mg of tissue bound. Specific binding of to each of the regions studied from each subject was fitted independently with a hyperbolic binding equation to derive individual estimates of Kd and Bmax for each region. A two-way nested model , analysis of variance (AN OVA) was used to test statistical significance. ANOVA is an analysis in which the total variability of the data is partitioned into compartments attributed to experimental conditions (Freund , 1988). This analysis is followed up, when statistically significant differences were found with a posteriori between group comparisons test using the post- hoc Bonferroni test.
Results stratum 7000
6000
5000
4000
3000
2000
1000
Concentration (nM)
FIGURE 1. Mean 3 (H)- flunitrazepam binding of benzodiazepine binding sites in stratum pyramidale of the subiculum of 4 autistic and 3 control cases across seven concentrations of ligand. Note the reduction in the number of binding sites (Bmax) in the autistic group compared to sex- and age- matched controls. The binding affinity (Kd) showed no differences.
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stratum moleculare 7000
6000
5000
4000
3000
2000
1000
Concentration (nM)
3 (H)-
FIGURE 2. Mean flunitrazepam binding ofbenzodiazepine binding sites in stratum moleculare of the subiculum in 4 autistic and 3 control cases across seven concentrations of ligand. Note the reduction in the number of binding sites (Bmax) in the autistic group compared to sex- and age- matched controls. The binding affinity (Kd) showed no differences.
Results from the multiple concentration saturation binding study indicate that in ten out of the eleven hippocampal lamina measured , there was a reduction in the Bmax values in the autistic group compared to the sex- and age- matched controls. Two graphs in figures 1 and 2 ilustrate the 3 (H)- flunitrazepam binding in two hippocampal laminae (stratum pyramidale and stratum moleculare) in the subiculum
taken from the mean values from the 4 autistic and 3 control cases. The amount of femtomoleslmg of tissue , is plotted at each of the seven con-
binding, measured in
centrations of 3 (H)- flunitrazepam.
The binding curve for the autistic group falls below
that of the control group in both figures 1 and 2. Note the separation at the highest concentration at the right of the curve. Statistical tests showed a trend for significance for the reduction in Bmax values in the autistic group compared to controls suggesting a change in the number ofbenzodiazepine receptors. The Bmax values represent on average a 20.1 %
reduction in the autistic group for the
Will
hippocampal lamina
that show a decrease compared to control. The one laminae that shows virtually no difference is in stratum moleculare of CAl-there is a 2. 9% increase in Bmax value in the autistic group compared to the control group. The greatest difference is in stra-
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GENEJ. BLATT
tum moleculare in the subiculum demonstrating a 30. 2% reduction in Bmax value in the autistic group (Figure 2). In contrast , there were no differences by ANOVA in the binding affinity to "(H)- flunitrazepam (normal Kd values) between the two groups.
Discussion Neuropathological abnormalities in the hippocampal formation in autistic individuals revealed increased cell packing density and a decreased elaboration of the pyramidal cell dendritic tree in specific CA subfields (Bauman and Kemper , 1985; Raymond et al. , 1996). In the hippocampal formation , Blatt et al. (2001) conducted a survey of eight types of neurotransmitter receptors from four different systems including the serotonergic C(H)- 80H- DPAT ketanserin labeled 5- HT,
labeled 5-
receptors and 3 (H)-
receptors), cholinergic C(H)- pirenzepine labled Ml recep-
hemicholinium labeled high affinity choline uptake sites), glutamatergic (H)- MK801 labeled NMDA receptors and 3 (H)- kainate labeled kainate receptors) and GABAergic systems C(H)- flunitrazepam labeled benzodiazepine binding sites and 3 (H)- muscimollabeled GABA receptors). Data from these single concentration ligand binding studies indicated that despite the neuroanatomical abnormalities , only the two GABAergic receptor markers demonstrated a statistically significant reduction in high binding regions (for 3 (H)- flunitrazepam: stratum pyramidale of CA2 , prosubiculum and subiculum and stratum moleculare of the subiculum; for (H)- muscimol: stratum pyramidale of CAl; Blatt et al. , 2001). A subsequent multi-
tors and 3 (H)-
ple concentration saturation binding experiment, described here , further demonstrated a trend for significance that the number of 3 (H)- flunitrazepam labeled benzodiazepine binding sites were reduced in ten of eleven hippocampal laminae quantified (decreased Bmax) whereas the binding affinity for the ligand was normal (Kd) in all eleven laminae (Blatt et al. , 2002; Guptil et al. , 2003 , submitted). These results suggest that alterations in the GABAergic system are not restricted to the cerebellum and that information processing in the hippocampal formation is also altered in the autistic brain.
An interesting development in autism research with possible implications to the GABAergic system is the results from the South Carolina Autism Project that have
looked at chromosomal abnormalities in autism. Among the first 100 cases enrolled in this project, abnormalities of chromosome 15q 11- 13 have emerged as the single most common finding (about 4% of cases), and candidate genes include genes for three GABA receptor subunits , GABRa5 , GABR , and GABRy3 (Schroer et al. 1998). Correlating with neuropathology in the hippocampus of autistics , the a5fBy2 subunit combination of GABA receptors predominate on hippocampal pyramidal cells , making up 20% of the GABA receptor population on these cells (McKernan and Whiting, 1996; for review of GABA subunit combinations throughout the brain see Whiting et al. , 2000). An additional subunit combination of GABA receptors has a widespread distribution in the brain (approximately 50% of the total GABA receptor population) localized to GABA interneurons (al 2y2; Whiting et al. , 2000). It is
j.
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unclear whether any of these candidate genes are affected in cases with this chromosomal abnormality or in other cases of autism , but it is interesting to speculate , given the more widespread involvement of the GABAergic system , that subunit gene(s) for GABA receptors are likely target(s) in autism (e. , subunit switching at specific times during development possibly due to neuronal loss in specific subcortical or cortical nuclei). Interestingly, Pericak-Vance and colleagues (Shao et al. , 2003) applied
an innovative new statistical genetic approach to families whose children scored high on sameness " character trait (extreme difficulty with changes to their daily routine). These researchers discovered a strong link to the GABR )3 gene on chromosome 15q ll- q 13 in the study group. Thus , the GABAergic system represents a new directional approach to autism research. If there are changes in the availability of specific GABA subunit receptors during critical prenatal and/or early postnatal developmental periods , then the consequences may result in altered GABA receptor function and may seriously impact in the " insistence
the development of afferent- efferent
connectivity as well as the delicate excitatory-
inhibitory balance at the synaptic level.
References , Bauman , M. L. and Kemper , T.L. (1991) The distribution of Purkinje cell loss in the cerebellum in autism (abstract). Neurol. 41 307. Bauman , M. L. and Kemper , T.L. (1994) Neuroanatomic observations of the brain in autism in The Neurobiology of Autism (Bauman , M. L. and Kemper , T.L. , eds), pp. 119- 145.
Arin , D.
Johns Hopkins University Press , Baltimore. Bauman, M. L. and Kemper , T.L. (1985) Histoanatomic observations of the brain in early infantile autism. Neurol. 35 , 866- 874. Blatt, Gj., Fitzgerald , C. , Guptil , J.T. , Booker , A.B. , Kemper , T.L. and Bauman , M. (2001) Density and distribution of hippocampal neurotransmitter receptors in autism: an
auto radiographic study. J. Autism Dev. Disord. 31 , 537- 543. Blatt, Gj., Bauman , M. L. and Kemper , T.L. (2002) Reduced number ofbenzodiazepine binding sites and decreased density of GABA receptors in the hippocampal formation of autistic individuals. Forum of European Neuroscience Abstract 3:484. Dennis , T. , Dubois , A. , Benavides , J.and Scatton , B. (1988) Distribution of central Wj (benzodiazepine ) and w, (benzodiazepine2 ) receptor subtypes in the monkey and human
brain. An autoradiographic study with CH)flunitrazepam and the Wj selective ligand 247 , 309-322. CH)zolpidem. Pharmacal. Exp. Ther. Freund , T.F. and Antal , M. 1988. GABA- containing neurons in the septum control inhibitory interneurons in the hippocampus. Nature 336: 170- 173.
Geary, WA and Wooten , G. F. (1983) Quantitative fim autoradiography of opiate agonist and antagonist binding in rat brain. j. Pharmacal. Exp. Ther. 225 , 234-240. Guptil J.T. , Booker , A. , Gibbs , T. , Kemper , T.L. and Bauman M. L and Blatt, Gj. (2003) CH) flunitrazepam- Iabeled benzodiazepine binding sites in the hippocampal formation in autism. BioI. Psychiatry (Submitted). McKernan , R.M. and Whiting, P j. (1996) Which GABA receptor subtypes really occur in the brain? Trends in Neuroscience 19 139- 143. Raymond , G. , Bauman , M. L. and Kemper , T.L. (1996) Hippocampus in autism: a Golgi analysis. Acta Neuropathol. 91 , 117- 119.
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Rosene , D. L. and G. W Van Hoesen (1987) The hippocampal formation of the primate brain: A review of some comparitive aspects of cytoarchitecture and connections. In Cerebral Cortex , E. G. Jones and A. Peters (eds. ), Plenum Press , New York , vol. 6 pp. 345- 456. Schroer , RJ, Phelan , M. , Michaelis , RC. , Crawford , E. , Skinner , S. A. , Cuccaro , M. Simensen , RJ, Bishop, J., Skinner , C. , Fender , D. , & Stevenson , RE. 1998. Autism and maternally derived aberrations of chromosome 15q. American Journal of Medical Genetics 76:327-336. Shao , Y , Cuccaro , M. , Hauser , E. , Raiford , KL. , Menold , M. , Wolpert, C. , Ravan , Elston , L. , Decena , K , Donnelly, S. , Abramson , RK , Wright, H. , DeLong, , Golbert J.R and Pericak-Vance , M. A. (2003) Fine mapping of autistic disorder to American Journal of Human chromosome 15q ll- q 13 by use of phenotyic subtyes. 72: in press. Genetics Shaw , C. , Aoki , C. , Wilkinson , M. , Prusky, G. and Cynader , M. (1987) Benzodiazepine (CHJflunitrazepam) binding in cat visual cortex: ontogenesis of normal characteristics and the effects of dark rearing.
Dev. Brain Res.
, 67- 76.
Whiting, P J, Wafford , KA. , McKernan , RM. , 2000. Pharmacologic Subtyes of GABA Receptors Based on Subunit Composition , In: GABA in the Nervous System: The View at Fifty Years. edited by D. L. Martin and RW Olsen. Ch. 8. Pp.113- 126. Philadelphia: Lippincott Wiliams and Wilkens.
Acknowledgements This research was supported by NICHD lROl HD39459- 01 (Dr. Gene J. Blatt , P. L), NIH NINDS NS38975- 01Al (Dr. Margaret L. Bauman , P. L), the National Alliance for Autism Research (NAAR; Dr. Gene J. Blatt , P.I) and by The Autism Research Foundation (TARF). Brain tissue was
provided by the Harvard Brain Tissue
Resource Center (HBTRC) (Francine Benes , M. , PhD. , Director) and from the University of Miami and the University of Maryland Brain Banks. Mailing Address:
Gene Blatt,
Ph.
Neurobiology Department of Anatomy and Neurobiology Professor of Anatomy
Boston University School of Medicine 80 East Concord Street, R- 7003 Boston, MA 02778 gblattr:cajal- bu. edu
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THE TRIMODAL BRAIN AND READING A new synthesis and some predictions
Judith L. Lauter Ph.
This is the first of two articles offring a new theoretical approach to reading, 999a b). This general brain model posits a "neurotypology " of individual difrences created during prenatal development and influenced by conditions of exposure to sex hormones, impacting virtually every aspect of human behavior. As outlined in the current paper, specifc applications of the Trimodal Model to reading include: 7) characterization of certain sensorimotor abilities as fundamental skills for reading; 2) assignment of these skills to the two cerebral hemispheres according to a new approach to functional asymmetries, the EPIC model; and 3) description of individual dif ferences in reading ability as depending on difrences in degree of access to right- vs. left- brain skills. In the second paper (Lauter McKane, this volume), preliminary data testing the theory are provided. ABSTRACT.
based on the Trimodal Model of Brain Organization (Lauter, 7998a
INIODUCTION The history of dyslexia is notable above all for the consistency and intensity of controversy surrounding virtually every issue (cf. Duffy & Geschwind , 1985; Hulme & Snow ling, 1997; Bowan , 2002). Topics of concern have included: 1) how to classify
reading problems; 2) whether sensory processes or only higher- level cognitive functions are important; 3) if there are problems with sensory processing, whether these are predominantly visual or auditory; and 4) the ultimate cause of reading problems including the paradox of depressed reading ability in children who are otherwise of normal intelligence.
Recently we have proposed a new brain model known as the Trimodal Model of 1998a, 1999a b), which may offer a means of resolving many of these controversies , in the form of a new biologically-based synthesis which can accommodate and relate a wide variety of theories and observations. This paper wil provide an overview of the Trimodal Model , and outline specific predictions regarding its application to reading and reading problems. The second paper (Lauter & McKane , this volume) wil summarize some preliminary data collected to test these predictions. Brain Organization (Lauter ,
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I. TIE TRIMODAL MODEL OF BRAIN ORGANIZATION Two aspects of the Trimodal Model are particularly important for considering the
nature of reading: 1) a new conceptual approach to
and 2) a
functional asymmetries;
prediction regarding a new " neurotypology " for human beings , which may help explain , in specific cause- and- effect terms , what appears as the puzzling variety of individual difrences
in reading ability.
The Trimodal Model: Functional asymmetries . The Trimodal Model of Brain Organization draws on a new approach to functional asymmetries , known as the EPIC model. The acronym EPIC refers to the four domains which are used to clasA.
two cerebral
sify specializations of the
hemispheres- Extrapersonal space
Peripersonal space ,
Intrapersonal space , and Coordination. The EPIC model builds on current research recognizing that the right and left hemispheres are not " equal and opposite " in function. Rather , the right hemisphere is seen to be " polypotent that is , to have more functions , many of them basic to survival , than the left side (cf.
Table I).
First , under the EPIC model , the right hemisphere is believed to serve several kinds of executive function , including general attention (cf. Heilman , 1994), management of intra personal space (general metabolism , cardiac health , immune function coordination of right/left activities (such as binocular cooretc. cf. Wittling, 1994), and dination- d. Flowers , 1993). In keeping with this array of responsibilities , the right hemisphere begins developing during intrauterine life earlier than the left (cf. review in Geschwind & Galaburda , 1987), and there are many signs that the right side continues to serve as the " leader " in brain/body function during the first two years of postnatal life , which may have implications for the phenomenon of " regression " in
some cases of autism (cf. discussions in Lauter , 1998a , 1999b). Thus many aspects of everyday function can be seen as depending on the right hemisphere to provide the general coordinative " frame " within which left- hemisphere processing (to be discussed below) addresses a much more restricted " content" (cf. MacNeilage , 1987).
Table I. General categories
of functional
asymmetries according to the EPIC
model of fuctional
asymmetres Hemisphere responsible
Category of function Extrapersonal space (see Table II)
Peripersonal space (see Table II)
Right Left
Intrapersonal space (metabolism , cardiac & immune function , etc.
Right
Coordinating extra/peripersonal space processing
Right
General attention (left
and
right sides of space)
Right
Managing cortical/subcortical connections
Right
Coordinating righUleft functions at all levels
Right
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TRIMODAL BRAIN AND READING I
Second , with regard to complementary functions of the two sides of the brain , the
EPIC model considers the right hemisphere to be responsible extrapersonal space
for processing in
(for example , features of sounds and visual patterns which can per-
ceived at a distance from the body surface) while the left hemisphere specializes in peripersonal space (such as sounds and visual patterns which must
tasks performed in
be very close to the ear and eye to be perceived). This distinction is similar to one suggested by Heilman (1994), but the EPIC model extends this to posit analogues in
all four main somatic functional systems- auditory, visual , somatosensory and motor (Table II). The idea is that in most everyday tasks , the two sides of the brain , with their complementary abilities in extra- vs. peri- personal space , work together accomplish tasks which neither could do alone (for a more complete discussion , d. Lauter , 1999b). Laboratory research on asymmetries , which may focus on one side to the exclusion of the other , can lose sight of the bilateral nature of most behaviors. Third , as implied in Table the EPIC model does not consider these righUleft specializations in terms of abstractions (such as " holistic vs. analytic ), but as physiological cortical extensions of biophysical properties which are known to distinguish classes of sensory receptors and motor effectors at the body periphery (Lauter , 1987 1997 , 1999b). While there are currently no data documenting anatomical distinctions
in connectivity between , for example , Pacinian corpuscles in the skin and the right vs. the left hemisphere , there are a variety of known mechanisms for top-down selectivity, which could be ultimately reflected in functional (and physiological) differences in the coding of cell populations at the level of the cortex. It should be possible to document such physiological distinctions in humans by means of noninvasive brain imaging, as long as analysis focuses on individual brains , since averaging across subjects can readily obscure what can be very dramatic individual differences in asymmetric patterns of activation (cf. Lauter , 1982 , 1983 , 1984 , 1992; Lauter et al. 1985 ,
1988).
Given the EPIC characterization of functional asymmetries , the greater Trimodal Model makes two basic assumptions: 1) these principles of hemisphere specialization are essentially the same in all brains (barring frank neurological damage); and 2) the continuum of individual differences observed in many areas related to right/left function (including reading skils) reflects an underlying continuum of differences in
degree
of access to these specializations. Thus the model makes a kind of competence- performance distinction: it assumes that all brains are born with all the tools in place (and assigned in the same way to the two hemispheres), but not all brains have ready
access to all the tools. B.
The Trimodal Model: Individual differences. According to the model , these
sorts of individual differences are established during prenatal development under the
same type of hormonal influences (primarily related to testosterone exposure) which others have concluded are important for righUleft growth patterns (reviewed in
Nyborg, 1994). The Trimodal Model posits that a exposure
(from zero to high) results in a
continuum of prenatal testosterone continuum of right/left configurations character-
continuum of "salience of right- vs. left side specializations. For several biological and ethological reasons (cf. Lauter , 1998a , 1999b), the continuum is predicted ized by a
Motor
Somatosensory
Auditory
Visual
hemisPhere)
Fine motor control
Few muscle fibers small motor units
large motor units
Tiny- angle movements Manipulation
Postural control Many muscle fibers
Truncal & whole- limb movements Large- angle movements
tactile disks
Pacinian corpuscles
basal cochlea
aPical cochlea
Very small skin area Local , static Surface light touch
Quickly changing (AM , FM) Aperiodic Broad- band
Large skin area Movement across skin Deep pressure
High acoustic frequency
Slowly changing (AM , FM) Periodic Narrow- band
throwing a ball (RH) talking (RH + LH)
locating splinter (LH)
hugging (RH)
listening to orchestra ("
listening to speech (RH + LH)
parvocellular system
magnocellular system
Low acoustic frequency
recognizing faces ("
examples/set)
reading (RH + LH)
(2
Static properties
High spatial frequency
(Left
EVERYDAY EXAMPLES
High- resolution details Color
hemisPhere)
PERIPERSONAL SPAC
Low spatial frequency Properties of motion Characteristic " gestalt" shape Light & dark
(Right
EXTRAPERSONAL SPACE
(EPIC model of functional asymmetres)
Table II. Proposed dimensional and receptor/effector bases for hemispheric specializations
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TRIMODAL BRAIN AND READING I to be
trimodally distributed in the general population
with approximately one- third of
individuals having brains in which the right side is more salient, one- third favoring the left side , and one- third favoring neither side (" symmetric " brains)- cf. top panel of Fig. 1.
Given the " unequal" responsibilities of the right vs. left hemispheres mentioned above , plus the posited " disconnection " actions of prenatal testosterone (cf. Lauter 1998a , 1999b), it can be concluded that not all of these brains wil have equal access to all skils. However , the Trimodal Model suggests that all these brains should be normal from a biological point of view , since all would be equally considered to be adaptive for the types of societies in which mammalian brains developed for milions
of years. The underlying features of neural function which differ somewhat from brain to brain are expressed in a wide variety of individual characteristics , ranging from personality to constellations of skils (such as those required for reading) to susceptibility to a variety of clinical conditions. First , the Trimodal Model predicts that the brain which develops in a testosterone- free environment (thus predictably most typical of women) is the one in which the right hemisphere comes to be the more salient. (This may be indexed by the larger size of certain regions surrounding the right- side Sylvian fissure , areas which have been the focus of much recent research on anatomical asymmetries and learning disorders- d. Geschwind & Galaburda , 1987; Galaburda , 1994; Lewis &
Diamond , 1994; Hynd & Hiemenz , 1997). Due to the " polypotent" nature of the right hemisphere , these brains should have access to all skils-both those which are specializations of the right brain (processing in extrapersonal space , management of genleft- brain specialities for processing in eral health , neural coordination , etc. plus peripersonal space which are overseen and coordinated by the right side (cf. the skils profiles in the middle panel of Fig. 1). Thus the Trimodal Model refers to these brains as " polytropic " (many- skiled), or as " right brain/whole brain " types. With increasing testosterone exposure , this default pattern is gradually undermined , a state which may interfere with access to the skils of either side. As the relative salience of the two sides approaches a condition of symmetry, both categories of functional specializations may become relatively inaccessible , retaining only excellence for righUleft coordination of gross motor control , such as required for athletics. The Trimodal Model refers to these as " middle " brains , both because of their development under mid- range levels of testosterone exposure , and because of their symmetric anatomical and physiological properties. At increasingly higher testosterone levels , the left hemisphere may become overwhelmingly salient and actually depress growth of the right side. This can create " leftbrain " individuals who , while they may excel in one or more skils provided by the left side , such as fine motor control or phonemic awareness , at the same time may also suffer from diminished right-brain participation , expressed in different categories of il health , poor social skils , and a lack of motor coordination.
!,.
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JUDITH L. LAUTER The Trimo!!"l Brain: Hypothesized distribution of cerebral asymmetries
'" LHA
aHA
RHA". LaiJ!e" (1887)
increasing prenatal testosterone
PhohBrnic awarenes Pa-vo vi9.aI htlagno \Asual 2- eye coordif1ation Adltal ;rn q;ery
Degrees of access to fundamental skils for reading
FIGURE 1. Schematic ilustration of a new neurotypology for human brains entitled the Trimodal Model of Brain Organization (Lauter , 1998a, 1999 a b). The model posits that a continuum of brain types , based on the relative salience of the right vs. the left hemisphere , is created during prenatal development under the influence of a continuum of hormone exposure (primarly testosterone), and is trimodally distributed in the general population (upper panel). As shown in the figure , brain types range from those created under hormone- free conditions , that is , with virtually no prenatal testosterone exposure (right- hemisphere advantage RHA), through types undergoing moderate testosterone exposure (zero hemisphere advantage OHA), to those exposed
to high levels of exposure (left- hemisphere advantage LHA). The resulting individual differences are reflcted in different degrees of access to a library of functional asymmetries (see Tables I and II), with implications for a great variety of features ranging from height, coloration , and personality, to combinations of skils , to susceptibility for different types of disorders. Such skil profiles are indicated by the pie
charts in the middle panel of this figure - the right- most triangle represents rightbrain skils , the left- most triangle represents left-brain skils , and the middle triangle symbolizes abilities for bilateral gross- motor coordination. The " polytropic " brain type (right- most mode , in which the right hemisphere is the more salient) is predicted to have complete access to left- as well as right- side skils , the " middle " brain type is predicted to have moderate to limited access to right- as well as left- side skils (though excelling in whole- body motor performance), while the left- brain or " focal" brain type has access only to left-brain capabilities. Finally, (lower panel), the three brain
modes of the Trimodal Model have predicted differences in degree of access to a group of fundamental skils which are considered to be basic requirements for reading (for the neurological bases of these assignments , see Tables I - III).
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TRIMODAL BRAIN AND READING I
II. APPLICATIONS OF THE TRIMODAL BRAIN MODEL TO READING AND READING PROBLEMS Details of these two principal components of the Trimodal Model have obvious implications for the study of reading and the variety of differences observed among people who find it difficult to learn to read fluently. In sub- sections A and B below we wil see that the functional- asymmetries (EPIC) portion of the model provides a basis for classifying different fundamental skils crucial for reading in terms of right
vs. left hemisphere specializations (Table III). Sub- section C describes the way in which the distribution of individual differences in access to these skils predicted by the Trimodal Model can account for the size and heterogeneity of populations presenting with reading problems (Lauter 2000a , 2001 , 2002).
A. Functional asymmetries: Left-brain fundamental skils (1) Phonemic awareness. One fundamental skil required as a foundation for reading is the auditory ability known as phonemic awareness , which is defined within the EPIC and Trimodal models as the capacity to distinguish and separate the acoustic not cues for phonemes when embedded within syllables. (As used here , the term does refer to the ability to identify phonemes in isolation , or to learn to map them onto
alphabetic symbols ,
which virtually all brain types
can do. )
Acoustic cues for
since they are extremely difficult to discern if a listener is very far removed from the speaker. Current estimates suggest that approximately one- third (30- 40%) of the general population exhibits a lack of this skil (evidence reviewed in Lindamood et al. , 1997). Since a lack of phonemic awareness may impact on other skils , such as the ability to understand speech in a noisy background (the trademark of " central auditory processing disorder ), auditory attention , information retrieval using the auditory channel (via spoken or recorded instructions or lectures), and the acquisition of phoneme- level grammatical markers , many members of this relatively large segment of the population may present with a variety of other troubles in addition to reading, which compounds their problems in school (Lauter et al. , 1998; Lauter , 2000b). phonemes are definitely associated with processing in
(2) Visual acuity.
A second left-brain
peripersonal space
skil necessary for reading, particularly given
the font sizes which begin to be used toward the end of the elementary grades , is visual acuity. In this context , visual acuity refers not only to performance of the peripheral visual mechanism (cornea through retina), but also to posited specializations of the left hemisphere for processing small , static visual patterns captured on the foveal portion of the retina in peripersonal space. (As indicated in Table II ,
this
implicates the " parvocellular" component of the visual system , which has been identified as originating in foveal retinal cells , and extends through thalamus into the cortex. ) The relatively high ilumination typically used for reading represents an
additional factor demanding left-brain foveal processing, since the retinal cones which predominate at the fovea , respond well at high light intensity while the
syllable & sentence " rhythms
vibration of larynx for voiced sounds jaw open/close of syllabic " rhythm eye- movement coordination
Somatosensory
Motor
mental imagery
word shapes & lengths
Auditory
Visual
RIGHT HEMISPHERE
acoustic cues)
fine- motor kinesthetic feedback from speech articulation
local sensation for articulation targets (tongue tip, etc.)
phonemic awareness (within- syllable
letter shapes (especially small font sizes) visual function in bright light
LEFT HEMISPHERE
Table III. Skills related to readng & spellng provided by each hemisphere
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TRIMODAL BRAIN AND READING I
response of rods (which predominate in extrafoveal retina) falls off with higher lev-
els of ilumination. Experimental data regarding visual acuity of the " cortical" type , that is , individual differences over and above those which can be accounted for by differences in peripheral function alone , are represented primarily by studies on functional asymmetries related to visual spatial frequency (cf. Sergent 1983). Although some authors have concluded that research on processing asymmetries for spatial frequency is inconclusive (cf. Sergent , 1994), in general these findings do suggest that higher spatial frequencies (such as text printed in font sizes 12 pt or less) may be preferentially processed by the left brain.
It is notable that the font sizes used in elementary- school reading materials decrease dramatically from kindergarten to third grade. This suggests that some of the reading problems which " emerge " around third grade may be the expression of brains which simply do not have sufficient access to left-brain acuity to accomplish accurate identification of letters printed in 12- point type , particularly when presented in continuous text where identification must be very rapid. In fact, reading can be improved in some children simply by allowing them to read text printed in larger type (Cornelissen et al. , 1991). (It is possible that such problems may be exacerbated
by additional difficulties with eye movements, discussed in the next section.
B. Functional asymmetries: Right- brain fundamental skils (1) Mental imagery.
The importance of mental or " concept" imagery for reading
comprehension has been cited by many authors over the years (cf. Lindamood et al.
1997 for a review). For instance , these latter authors note that an excellent predictor of abilities for mental imagery and accomplished reading comprehension is a test of design reproduction , where an individual is required to hold the features of a geometric figure in mind and then redraw it from memory. Being able to create , retain and recall mental images is clearly related to abilities for identifying visual objects at a distance
, which we have previously suggested constitute a right-brain
specialty
(Lauter , 1997 , 1999b), since both types of task emphasize overall " gestalt" form based on details comprehended in an overall form , and object identification involving
movement instead of static properties. Ready access to mental imagery during reading may also be related to an individual's ability to remember the images of dreams. Some reading experts have noted that children whose reading comprehension is impaired by poor mental imagery often do not " remember " their dreams , and one of the most dramatic side- effects of training in imagery is that these individuals begin being able to report and describe dreams in great detail , starting with black and white images and progressing to color (Bell , personal communication). It has been known for some time that dreaming occurs primarily during rapid eye movement (REM) sleep (Foulkes , 1966; see next section) with higher activity over the right as opposed to the left hemisphere (Asenbaum et al. , 1995 , Benca et al. , 1999), findings that also seem to support
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JUDITH L. LAUTER
the Trimodal Model's categorization of mental imagery as a right- hemisphere specialization. (2) Eye movements.
The fact that no fewer than three of a mammal's twelve pairs
of cranial nerves are devoted to the extraocular muscles suggests that the ability to move the eyes has definite survival value. In everyday mammalian behavior , eye movements are clearly associated with extrapersonal space. Being able to move the eyes without turning the head (as for example , owls are forced to do) provides for greater ease in actively scanning the environment and also for following the movements of objects and animals at a distance. Thus the Trimodal Model assigns ultimate responsibility for eye movements to the right brain. The word ' ultimate ' is used here because although the frontal eye fields and eye- movement fields in posterior parietal cortex (PPC- cf. Stein & Walsh 1997) do occur on both sides of cortex- some of the extraocular muscles , like most skeletal muscles , exhibit contralateral representation-the Trimodal Model predicts that the right brain is primarily responsible for executive management of eye movements ,
including the coordination of right and left eyes- see below. In reading, the eyes are moved in a noncontinuous way. That is , the eyes make small jumps or " saccades " from point to point; at each point, they must remain very stil in a " fixation " during which time the image is held centered and static on the
fovea of the retina. The parvocellular part of the visual system mentioned above is employed during the fixations to capture the small , static visual image of a few letters on the foveal retina.
However , if only the parvo system were available , reading rates would have to since cells of this system are " slow- adapting, " that is , they take a long time to " lose " one image when confronted with a new one. If a reader moved the eyes quickly to a new image (a new string of letters), and had only the parvo system active , the impression would be of blurring, as the parvo system s trace of the old image gradually disappears and the new one is registered. (In some children with reading problems , this is exactly the percept reported , which has led to one theory of dyslexia , discussed below. However , there is another component of the visual system which seems to help out when a fairly rapid sequential series of fixations is required. This is the " magnocellular " system , where cells are " rapid- adapting, " that is , they have the property of being able to start and stop responding quite quickly. It has been suggested (ef. Breitmeyer & Ganz , 1976) that during fluent reading, the two systems work in tandem- that is , the parvo system is active during the static fixations , working to capture the image for transmission to the brain , while the magno system takes over during the subsequent saccade , working to " erase " the remains of the previous image in preparation for receiving the next one. A number of properties of the magnocellular visual system make it a candidate for right- brain specialization according to the Trimodal Brain model: 1) it seems to be very important for eye movements (cf. Eden et al. , 1995), which as we have said be extremely slow ,
are clearly adaptive for extrapersonal space perception (cf. Stein , 1989); 2) the magno
system arises from cells having fairly large receptive fields away from the fovea , thus
,"
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TRIMODAL BRAIN AND READING I
supporting wide- scan monitoring along with gestalt whole- form " perception; and 3) those cells depend primarily on rods , and are thus more sensitive to light/dark contrasts than to color , and are also active at low luminance , all very adaptive features for vision at a distance.
The fact that extrafoveal rods are much more reactive than foveal cones both at low luminance levels and in response to blue light (ef. the " blue-blind" fovea-Wilmer 1946) may account for the observation that atypical eye movements can sometimes be improved by the use of gray or blue filters (cf. Wiliams et al. , 1992; Solan et al. 1998), which presumably work by recruiting or " waking up " a relatively inactive magno system. (By the same logic , it is not surprising that red filters do NOT improve eye movements (cf. Wiliams et al. , 1992), since it is the parvo- system cells of the fovea , not the extrafoveal magno- system cells , which are stimulated by red. This and other signs of difficulties attributable to reduced magnocellular function
have led several researchers to posit that some reading problems are due to a " transient or magnocellular deficit " suggested as an actual neurological abnormality affecting this component of the visual pathways (cf. Stein & Walsh , 1997; Solan et al. 1998). In contrast , the Trimodal Model attributes such problems to a more dynamicand thus trainable- lack of access " to right-brain specializations , as wil be discussed
more below. (3) Eye- movement
coordination.
The large body ofresearch on eye movements dur-
ing reading also provides overwhelming evidence of the importance of
coordinated
functions in eye movements (Garzia & Sesma , 1993; Garzia & Peck , 1994). There are two categories of coordination, or synchronization , which are predictably overseen by the right brain. (3- a) Synchronization of right and left eyes. First , for accurate integration of images
captured by the right and left eyes , it is clearly necessary to ensure that both eyes move together , particularly in a demanding visual task such as reading. This type of synchronization is not an obligatory result of hard wiring- for instance , it shows a clear developmental time course (the right and left eyes of neonates very often move independently, though even in neonates they become more coordinated under lowluminance conditions , again implicating the magno system- Haith & Goodman 1982), and righUleft coordination requires active , waking " high- level" control (right not coordinated during REM sleep- Zhou & King, 1997). Other authors , drawing on data from normal as well as brain- injured individuals
and left eyes are
have concluded that stereoscopic vision ,
accomplished by the vergence system
depends on the right hemisphere (cf. comments in Eden et al. , 1995). The Trimodal Model agrees with this , and extends such a conclusion to include all aspects of twoeye coordination , as representing just another instance of bilateral motor coordination (analogous to coordinating right and left hands in bimanual tasks)- thus the model classifies two- eye coordination in general as a specialty of the right hemi-
sphere. Such an assignment is additionally supported by research on individuals with unilateral brain damage , where there are indications that eye movements are disrupted more , and in different ways , following right- side as opposed to left- side injury (Weinberg et al. , 1979 , Gordon et al. , 1985; Zihl , 1995).
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With regard to reading problems in non- neurological populations , observations in many individuals who experience such problems indicate that the two eyes in fact are often not coordinated (studies reviewed in Eden et al. , 1995), and that they may even move more or less independently, which can be observed during non- reading as well as reading tasks (Eden et al. ,
1994).
We have suggested Coordination of magnocellular and parvocellular systems. above that the magnocellular component of the visual system is ultimately controlled (3-b)
by the right hemisphere. The Trimodal Model also considers that the right brain is responsible for the second type of visual synchronization needed for reading, namely, temporal synchronization of the magno and parvo systems. Many authors have noted that this type of coordination may be crucial for fluent reading (cf. reviews in Stein & Walsh , 1997; Kulp & Schmidt , 1996; Demb et al. , 1998; and comments in Maples , 2003). The demands of such synchronization are very exacting. It involves the temporal interleaving of activation in parvo and magno systems with milisecond resolution , accomplished in parallel with the integration of sensory input from both eyes and both visual half- fields , along with accurately sequenced commands for motor
output to the extraocular muscles of each eye to maintain the " rhythm of reading. This type of highly complex sensorimotor behavior is a pre- requisite if a reader is to achieve rapid and accurate letter identification , word recognition , and ultimately, comprehension. Based on the Trimodal Model's characterization of the right brain as the general manager of the gestalt of whole-brain and whole-body behavior , this type of two- sided , multi- system , multi- level integration can only be accomplished by the right side of the brain.
c. Individual differences in access to
fundamental skils for reading
Given these very specific assignments of different skils and capabilities to the two cerebral hemispheres , it is easy to generate profiles of different possible subtypes of reading problems , which should not only account for all of the types previously observed , but also be highly predictable regarding how different combinations of problems may characterize specific individuals. Such a systematic " bottomapproach may lead to more objective and biologically- based guidelines for classifying and categorizing the different types of reading problems , which may prove useful for addressing clusters of features , designing and selecting remediation , and documenting treatment efficacy (cf. comments regarding the need for " appropriate tests " to address different populations in Stein & Walsh , 1997).
The Trimodal Model's suggestion that skil profiles arise from a trimodal distribution of brain types also suggests the biological origins of the kinds of numbers that have been associated with the incidence of reading problems- such as 20- 30% of public- school populations having severe difficulties with reading (Shankweiler & Liberman , 1989), 48% of the adult population being without functional literacy skils (National Center for Education Statistics , 1993), and 60% of the adult prison popula-
, "
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TRIMODAL BRAIN AND READING I
tion lacking everyday literacy skils (Conway, 1993). These numbers can seem overwhelmingly large if we continue to think of reading difficulties as signs of neurological abnormality-but , in fact, the size of these incidence statistics suggests rather that these are signs of normal variation just as predicted by the Trimodal Model (Lauter 2000a, 2001 , 2002). As we wil see , the Trimodal Brain approach to reading also helps us come a little closer to grasping the origins of the different reading profiles together with their co- morbidities , which lacking such a context can be difficult to understand.
The possible subtypes of reading problems suggested by this outline include difanyone of the skils listed above , or the lack of difrent combinations of skils- two , three , four , etc. all of which should result in very different behavioral profiles , pointing to very different patterns of access to cerebral specialficulties arising from a lack of
izations. By way of ilustration , consider again the neurological categories from the top panels of Fig. 1 , together with the notations regarding the right vs. left- brain skils we have just discussed ,
summarized in the bottom panel. (1) Right- brain/Whole- brain individuals (right side of Fig. 1). These individuals are considered to be those who develop in a testosterone- free intrauterine environment. They are characterized as having excellent access to the specializations of both sides of the brain , and are therefore predicted to have no difficulties at all in reading. These are the " natural readers " who " catch on quickly " when first shown the correlation between phonemes and alphabetic symbols , who " see pictures in their head" when they read , naturally visualize words to be spelled , and continue to enjoy reading as a lifelong entertainment. Their phonemic awareness wil follow or progress ahead of the developmental course predicted by current norms (such as those established for the Lindamood Auditory Conceptualization (LAC) Test- cf. Lindamood et al. , 1992 , 1997), and thus achieve an adult level for nonsense sequences of four phonemes before or no later than 7th grade. They wil exhibit vivid and accurate mental imagery, and their eyemovement coordination , in terms of both two- eye synchronization and rhythmic eye tracking, should progress along the expected developmental course (for instance according to norms collected with the Visagraph II system- d. Colby et al. , 1998). (2) Left- brain individuals (left side of graph). The Trimodal Model suggests that these individuals ,
who are assumed to develop under the highest levels of exposure
to prenatal testosterone
, wil be limited primarily to left-brain skils such as phone-
however , they may show in a very advanced
hyperlexic form. (This may be seen in children with left- brain conditions such as Asperger Syndrome- Lauter et al. , Submitted). However , their diminished access to right- brain skils should result in the disastrous combination of poor to absent mental imagery and extremely irregular eye movements , which wil not develop in a normal way and wil continue to impede reading performance so that it remains well below that premic awareness-which ,
dicted for their age.
Note that their abnormal eye movements should include a lack of coordination primary signs of a of the two eyes plus signs of irregular tracking-both interpreted as lack of access to right-brain abilities. (Since parvo-visual function should be intact in
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JUDITH L. LAUTER these individuals , their eye- tracking features may show inconsistent abnormalities very short fixation time combined with very many regressions , etc. ) This profile of
eye- movement problems should distinguish them from certain middle- brain types (see next section), in whom the two eyes are well synchronized , but eye tracking is disturbed in a consistent way (long fixation times and multiple regressions , etc. ), thus interpreted as a secondary result of poor access to left- brain skils for parvo- system function. The left-brain types should be those who are most helped by the use of gray or blue filters , which predictably act by " turning up " the magno visual system , which may be said to be " sleeping " (due to the diminished access to right-brain participa-
tion) in this type of brain. Some authors have reported that eye movements can be improved through the use of blue filters- in some cases , improving performance in as many as 70- 80% of reading- disordered subjects (cf. Lovegrove , 1993; Demb et al. , 1998; Iovino et al. 1998; Solan et al. , 1998; Robinson & Foreman , 1999). Such a high proportion may be accounted for by the fact that, in some studies (such as Solan et al. , 1998) children with " significant decoding problems " (i. , poor phonemic awareness , or what we would predict are " poor- parvo " children) were screened out of the study, thus creating a study population which should have a very high proportion of " poor- magno " (i. blue- responding) children. Left- brain individuals may be able to obtain meaning from text by rote memorization of word definitions and laborious re- reading, and may depend heavily on assistance from ilustrations and other extra- text cues to meaning, which they cannot
obtain for themselves given their lack of mental imagery. These characteristics of their reading performance should appear in combination with other features which the Trimodal Model associates with the left- brain type , such as strong right- handedness for fine motor tasks , poor ' motor planning ' skils , diminished social skils and empathy, inappropriate or monotonal speech " melody, " and a primitive sense of humor (these are the children who often " don t get the joke They wil also be characterized by " released" brainstem activity combined with poor skils for maintaining attention , leading to versions of attention deficit, sensory hypersensitivity, and/or motor hyperactivity (cf. Lauter , 1998b , 1999a b)- thus these may represent the " dyslexia- plus " children described by Denckla (1985) and others. They may also show depressed immune function , with associated conditions such as chronic otitis media and allergies; and exhibit signs of poorly managed internal body
functions , such as erratic upset, and headaches. (3) Middle- brain
sleep cycles , poor eating habits , frequent gastrointestinal
individuals
(middle panel of Fig. 1). These individuals , exposed to
moderate amounts of prenatal testosterone (whether they are XY or XX) should together represent a continuum of diminished access to skils of both sides. For example , those on the right side of middle may retain quite good access to right-brain skils such as imagery and two- eye synchronization , but lack phonemic awareness. Eyetracking movements during reading may be perturbed
secondary
to their impaired
access to parvo-visual functions- thus in these individuals , eye- movement abnormal-
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ity may be the result of diminished activity in the parvo system , and not a cause of reading problems in and of itself. Their reduced (parvo- system) ability for rapid recognition of letters during visual fixation may lead to eye tracks with a high number of fixations (" one fixation per letter ), long fixation times (" what IS that letter?" ), and multiple regressions (" going back to look again ). Note that such features of eye tracking predicted for these chil-
dren (considered neurologically normal according to the Trimodal Model) resemble those observed in adults subsequent to left-brain damage (e. , Zihl , 1995).
It may even be possible that as these types of children move through the early school grades , their lack of phonemic awareness conflicting with classroom demands
may result in an actual degradation of eye movements. This could account for the observation that by third grade , the incidence of children with perturbed eye movements is often higher than that measured in children two years younger (McKane
unpublished data). In general , these " right- middle " individuals may exhibit the type of reading difficulty referred to as " dysphonetic " with phonemic awareness the overriding lack.
Due to diminished access to left-brain skils in general , reduced phonemic aware-
ness wil predictably be accompanied by other signs of reduced left-brain
access
such as ambiguous hand dominance for fine- motor control tasks (thus these individuals may be ambidextrous to mildly left- handed) or generally impaired fine motor control. A lack of fine- motor sensitivity may also result in a lack of awareness of the
position of the speech articulators (resulting from poor feedback from muscle and joint receptors), as has been observed in dysphonetic children (cf. comments by Heilman et al. , 1996 and Lindamood et al. , 1997). An additional failure based on lack of access to left- brain abilities , in this case for fine somatosensory perception (cf.
Table II), may result in such individuals having a poor sense of touch on the skin around the mouth (such as from particles of food), as has also been noted (ef. Heilman et al. , 1996). middle ofmiddle might have diminOn the other hand , individuals more in the ished access to the specializations of
both
sides , resulting in a plethora of difficulties
with reading. For these individuals (perhaps those sometimes called " dysphoneidetics cf. Stein & Walsh , 1997 , or " dyslexia pure Denckla , 1985), both phonemic and all aspects of eye movements may be well below grade level (cf. a subset of children studied by Eden et al. , 1994), and there may be little or no experience of mental imagery. They should be more or less ambidextrous (with a variety of types of " left- handedness ), and may actually excel at whole-body movements involving awareness
coordination of both sides of the body, but should have relatively poor fine motor control of any body part, including either hand. They should exhibit relatively low susceptibility to " left- brain ils " such as hyperactivity and psychiatric or immune- system problems , but may be fairly vulnerable to weight gain and associated conditions
such as heart problems , though these wil be of somewhat different types
than those
experienced by left brains. left of middle should have even more diminished access side skils , combined with a " warming up " of left-brain skils. Their phone-
Finally, individuals to the
to right-
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JUDITH L. LAUTER
mic awareness may not be as limited as is true for other types of " middle brains " but their eye movements should resemble the pattern we have suggested wil pertain in left brains , that is a combination of poor two- eye synchronization plus irregular eye track patterns which cannot be accounted for by a consistent problem with parvovisual function (this may be the condition sometimes referred to as " dyseidesia As a result of the incomplete nature of their access to left-brain skils , these people may also be those who exhibit developmental stuttering which persists beyond childhood (eye- movement problems have been seen in some stutterers- d. Brutten et al. , 1984), and they may also be prone to develop certain types of psychiatric prob-
lems such as schizophrenia and depression. It is notable that there is a considerable literature on perturbed eye movements in schizophrenia (reviewed in Zahn , 1986), which is controversial in that these problems do not occur in all schizophrenics. However , this is not a surprising outcome if this psychiatric condition in fact is represented , as predicted in the Trimodal Model , along a restricted range of the braintype continuum (perhaps bridging between left- middle and left), with associated variations in accuracy of eye- movement control.
SUMMAY In this paper we have suggested that a new approach to understanding individual differences in access to right- vs. left-brain skils , the Trimodal Model of Brain
Organization , offers new insights into the biological origins of reading problems. In addition , the " neurotypology " outlined by the Model also gives us a basis for predicting which children wil have which types of reading difficulties-whether none at all (polytropic- brain types), different combinations of problems (middle- brain types), or skils limited to those supported by the left hemisphere only (left- brain types). Based on the trimodal distribution of these brain types posited by the model , the general conclusion is that reading may in fact be " unnatural" for approximately 2/3 of the population- adults as well as children (Lauter 2000a, 2001 , 2002). Although this may seem daunting, there is also a hopeful side to this picture- namely, the posited neurobiological bases of these difficulties , that is , that they are problems of access rather than " missing modules. " As a result , intensive neurorehabilitation training programs specifically targeting undeveloped skils can be used to " wake up " access to the skils , and add them to an individual's repertoire. Such possibilities wil be discussed briefly in the second paper (Lauter & McKane , this volume). As a theory, the Trimodal Model may offer a useful means of bringing together and triangulating details from many areas of dyslexia research. At the same time from an empirical standpoint, the Trimodal Model is descriptive , highly predictive and eminently testable. The companion paper (Lauter & McKane , this volume) presents preliminary data testing one prediction regarding the co- occurrence of a pair of fundamental abilities needed for reading-the left- brain skil of phonemic awareness (PA) and eye- movement
coordination (EMC), a right-brain specialty. Specifically, the
prediction is that four general populations of children can be defined , representing
),
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),
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TRIMODAL BRAIN AND READING I
the Trimodal continuum of brain types: 1) grade- appropriate performance in both of " natural readers ); 2) intact EMC but poor PA (middle brains toward the right of that distribution , representing one category of dyslexia); 3) these skils (poly tropics- the
intact PA but poor EMC (left brains , who present with another kind of reading problem); and 4) deficits in both (middle- of- middle brains , who should find reading extremely difficult for a variety of reasons).
REFERENCES Asenbaum , S. , Zeithofer , J., Saletu , B. , Frey, R , Brucke , T. , Podreka , I. Deecke , L. (1995). Technetium- 99m- HMPAO SPECT imaging of cerebral blood flow during REM sleep in narcoleptics.
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Benca , RM. , Obermeyer , W. , Larson , C. , Yun , B. , Dolski , I. , Kleist, KD. , Weber , S. Davidson , RJ. (1999). EEG alpha power and alpha power asymmetry in sleep and wakefulness. Psychophysiology, , 430-436. Bowan , M. D. (2002). Learning disabilities , dyslexia , and vision: a subject review. Optometry, 73
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Missouri Reader 28-30. Conway, J. (1993). A solution to the iliteracy crisis. Cornelissen , P., Bradley, L. , Fowler , S., Stein J. (1991). What children see affects how they read. Developmental Medicine and Child Neurology, , 755- 762. Demb J.B. , Boynton , G. , Best, M. , et al. (1998). Psychophysical evidence for a magnocellular deficit in dyslexia.
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Denckla , M. B. (1985). Motor coordination in dyslexic children: Theoretical and clinical implications. In F.H. Duffy & N. Geschwind (Eds. Dyslexia: A neuroscientifc approach to clinical evaluation (pp. 187- 195). Boston: Little , Brown & Co. Duffy, F.H. & Geschwind , N. (Eds. ) (1985). Dyslexia: A neuroscientifc approach to clinical evaluation. Boston: Little , Brown & Co. Eden , G. , Stein , J.F. , Wood , H. , Wood , F.B. (1994). Differences in eye movements and , 1345- 1358. Vision Research , Wood , F.B. (1995). Verbal and visual problems in reading disability. , 272- 290. Journal of Learning Disabilities Flowers , D. L. (1993). Brain basis for dyslexia: A summary of work in progress. Journal of Learning Disabilities , 575- 582. Foulkes , D. (1966). The psychology of sleep. NY: Scribners. reading problems in dyslexic and normal children.
Eden , G. , Stein J.F. , Wood , M.
Galaburda , A.M. (1994). Anatomic basis of cerebral dominance. In RJ. Davidson & K (pp. 51- 73). Cambridge MA: MIT Press. Hugdahl (Eds. Brain asymmetry Garzia , RP. & Sesma, M. A. (1993). Vision and reading. I. Neuroanatomy and electrophysiology. Journal of Optometry and Visual Development , 4- 51. Garzia , RP. & Peck , C. (1994). Vision and reading. II. Eye movements. Journal of Optometry and Visual Development , 4- 37.
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Geschwind , N. & Galaburda , A.M. (1987). Cerebrallaterali2Jtion: Biological mechanisms, associations, and pathology. Cambridge MA: MIT Press. Gordon , W. , Hibbard , M. , Egelko , S. (1985). Perceptual remediation in patients with right Archives of Physical Medicine and Rehabilitation
brain damage: A comprehensive program.
, 353-359. Haith , M. M. & Goodman , G. S. (1982). Eye- movement control in newborns in darkness and in unstructured light. , 974- 977 Child Development Heilman , K (1994). Attentional asymmetries. In RJ. Davidson & Hugdahl , K (Eds. Brain asymmetry (pp. 217-234). Cambridge MA: MIT Press. Heilman , K , Voeller , K , Alexander , A.W. (1996) Developmental dyslexia: a motor- articulatory feedback hypothesis. Annals of Neurology, , 407- 412. Hulme , C. & Snow ling, M. (Eds. ) (1997). Dyslexia: Biology, cognition and intervention. London: Whurr Publishers. Hynd , G. W. & Hiemenz j.R. (1997). Dyslexia and gyral morphology variation. In C. Hulme (pp. 38-58). London: & M. Snowling (Eds. Dyslexia: Biology, cognition and intervention Whurr Publishers. Iovino , 1. , Fletcher j.M. , Breitmeyer , B. , et al. (1998). Colored overlays for visual pereption deficits in children with reading disability and attention deficiUhyperactivity disorder: are they differentially effective?
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791- 806. Kulp, M.T. & Schmidt , P. P. (1996). Effect of oculomotor and other visual skils on reading performance: A literature review. , 283- 292. Optometry and Vision Science Lauter j.L. (1982). Dichotic identification of complex sounds: absolute and relative ear advantages.
Journal of the Acoustical Society of America
, 701- 707.
Lauter j.L. (1983). Stimulus characteristics and relative ear advantages: a new look at old data. Journal of the Acoustical Society of America
, 1- 17.
Lauter j.L. (1984). Contralateral interference and ear advantages for identification of three- eleBrain and Cognition
ment patterns.
Lauter
j.L. (1987).
, 259- 280.
Dimensions of asymmetry: A multimodal perspective. Invited presentation
to Symposium on Complex Perception of Nonspeech Stimuli , Chicago IL.
Lauter j.L. (1992). Processing asymmetries for complex sounds: Comparisons between behavioral ear advantages and electrophysiological asymmetries based on quantitative electroencephalography (qEEG). Brain and Cognition , 1-20.
Lauter j.L. (1997). Dimensional bases of functional asymmetries: A view from above the central sulcus. Invited presentation to First Annual Conference on Developmental and Learning Disorders , Washington DC. Lauter j.L. (1998a). Neuroimaging and the Trimodal Brain: Applications for developmental Folia Phoniatrica et Logopedia , 118- 145. Neurophysiological self- control: Modulation in all things. Journal of , 543- 549. Communication Disorders Lauter , j.L. (1999a). The Handshaking Model of Brain Function: Notes toward a theory. Medical Hypotheses , 435-445. communication neuroscience.
Lauter ,
Lauter
j.L. (1998b)
j.L. (1999b). Functional
opmental disorders.
asymmetries and the Trimodal Brain: Applications to devel-
Journal of Developmental and Learning Disorders
, 181- 260.
Lauter , j.L. (2000a). The brain and reading: Neural bases for a new perspective on reading skils assessment and training. Invited presentation to Idaho State Conference on Reading and Learning, Boise ID.
Lauter , j.L. (2000b). A new approach to CAP and CAPD. (1) Putting central auditory processing at your fingertips: The AXS Test Battery. (2) Neuro- audiological rehabilitation: Expanding your scope of practice. (3) 21st century CAPD: Throwing away the crutches. Invited presentation to
Symposium on Central Auditory Processing Disorders in
Children: Perspectives in Assessment & Management, Cleveland 0 H.
Cleveland Clinic Foundation
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TRIMODAL BRAIN AND READING I j.L. (2001). Is reading ' unnatural' for 2/3 of our children? - Right brain , left brain , and the " missing link" skils for reading and learning. Invited keynote presentation to
Lauter
SouthWest and Rocky Mountain division of American Association for the Advancement of Science , Denton TX. Lauter , j.L. (2002). Is reading ' unnatural' for 2/3 of children and adults? Presented to American Speech- Language- Hearing Association , Atlanta GA Lauter , j.L. , Herscovitch , P. , Formby, C. , Raichle , M. E. (1985). Tonotopic organization in human auditory cortex revealed by positron emission tomography. Hearing Research, 20 199-205. Lauter j.L. , Herscovitch , P. , Raichle , M. E. (1988). Human auditory physiology studied with positron emission tomography. Inj. Syka and RB. Masterton (Eds. Auditory Pathway (pp. 313- 317). NY: Plenum. Lauter , j.L. , Richey, H. , Gilmore , S., Lynch , O. (1998). Putting the " central" back in central auditory processing. , 51- 106. Journal of Developmental and Learning Disorders Lauter , j.L. , Richey, H. , Giddens , C. Culbertson (Submitted). Neurological profie of Asperger Syndrome: A case study. Lewis , D. W & Diamond , M. C. (1994). The influence of gonadal steroids on the asymmetry of the cerebral cortex. In RJ. Davidson & K. Hugdahl (Eds. Brain asymmetry (pp. 31-50). Cambridge , MA: MIT Press. Lindamood , P. , Bell , N. , Lindamood , P. (1992). Issues in phonological awareness assessment. Annals of Dyslexia , 242-259. Lindamood , P. , Bell , N. , Lindamood , P. (1997). Sensory- cognitive factors in the controversy over reading instruction.
Journal of Developmental and Learning Disorders
, 143- 182.
Lovegrove , W. (1993). Do dyslexics have a visual deficit? In S. F. Wright & R Groner (Eds. Facets of dyslexia and its
(pp. 33- 49). Amsterdam: Elsevier
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Publishers. MacNeilage , P. F. (1987). The evolution of handedness in primates. In D. Ottoson (Ed. Duality and unity of the brain (pp. 100- 113). NY: Plenum. Maples , W. C. (2003). Visual factors that significantly impact academic performance. Optometry,
, 35- 49. National Center for Education Statistics (1993). NCES.
National Adult Literacy Survey.
Washington DC:
(1994). Hormones, sex and society. Westport CN: Praeger. Robinson , G. L. and Foreman , PJ. (1999). Scotopic sensitivity/Irlen syndrome and the use of coloured filters: a long- term placebo controlled and masked study of reading achievement and perception of ability. Perceptual and Motor Skills , 83- 113. Psychology Bulletin Sergent j. (1983). The role of the input in visual hemispheric asymmetries. 481-512. Sergent, j. (1994). Hemispheric contribution to face processing: Patterns of convergence and
Nyborg, H.
divergence. In RJ.
Davidson & K. Hugdahl (Eds.
Brain asymmetry
(pp. 157- 181).
Cambridge , MA: MIT Press. Shankweiler , D. & Liberman , LY. (1989). Phonology and reading disability. Ann Arbor: Univof Michigan Press. Solan , H. , Ficarra , A , Brannan j.R , Rucker , F. (1998). Eye movement effciency in normal and reading disabled elementary school children: Effects of varying luminance and wavelength. , 455-464. Journal of the American Optometric Association Stein
j.F. (1989). Representation of egocentric space in the posterior parietal cortex. Journal of Experimental Physiology,
, 583- 606.
QJarterly
Stein , j.L. & Walsh , V. (1997). To see but not to read: The magnocellular theory of dyslexia. Trends in Neuroscience
, 147- 152.
Weinberg, j., Diler , L. , Gordon , W. , Gerstman , LJ., Lieberman , A. , Lakin , P. , Hodges , G. Ezrachi , O. (1979). Training sensory organization in people with right brain damage. Archives of Physical Medicine and Rehabilitation , 491-496.
(pp.
), ),
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Wiliams , M. disability.
, Lecluyse , K. , Rock- Faucheux , A. (1992). Effective interventions for reading Journal of the American Optometric Association
, 411- 417.
Wilmer , E. N. (1946). Retinal structure and colour vision. Cambridge: Cambridge Univ. Press. Wittling, W (1994). Brain asymmetry in the control of autonomic- physiologic activity. In RJ. Davidson & K. Hugdahl (Eds. Brain asymmetry (pp. 305- 357). Cambridge , MA: MIT Press.
Zahn , T.P. (1986). Psychophysiological approaches to psychopathology. In M. H. Coles , E. Donchin , S. W. Porges (Eds. Psychophysiology: Systems, processes, and applications 508- 610). NY: Guilford Press. Zhou , W. & King, WM. (1997). Binocular eye movements not coordinated during REM sleep. Experimental Brain Research 117 ,
Zihl
153- 160.
j. (1995). Eye movement patterns in hemianopic dyslexia.
Brain 118 891-912.
Mailing Address:
Judith L. Lauter, Ph. Professor Director, Human Neuroscience Laboratory Dept. of Human Services, Box 73079 SFA Station Stephen F Austin State University, Nacogdoches TX 75962 jlauterr:sfasu. edu/936- 468- 7252/FAX 936- 468- 7096
An audio- visual overview of some of these issues (Trimodal Brain model , the AXS Test Battery, applications to reading) is provided in: J.L. Lauter (2002)
How Understanding Individual Difrences Can
Improve Your Clinical Practice.
Neuroimaging: (3- hr edu-
cational video with manual) Rockvile , MD: American Speech- Language- Hearing Association. Available from ASHA professional catalog (1- 888- 496- 6699), item 0112397.
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THE TRIMODAL BRAIN AND READING II: Preliminary data on the co-occurrence of problems in phonemic awareness and eye-movement coordination
Judith L. Lauter Ph. D.
and P. Frank McKane Ph.
ABSTRACT. This paper reports the results of an exploratory study designed to test some of the predictions of the Trimodal Model of Brain Organization (Lauter, 7998a, 7999a
, this
volume). This general brain model posits a "neurotypology " of individual difrences created
during prenatal development and influenced by conditions of exposure to sex hormones, impacting virtually every aspect of human behavior. As outlined in the fturth article referenced above (Lauter, this volume), applications of the Trimodal Model to reading include: 7) characterization of certain sensorimotor abilities as fundamental skills ftr reading; 2) assignment of these skills to the two cerebral hemispheres according to a new approach to functional asymmetries the EPIC model; and 3) description of individual difrences in reading ability as depending on difrences in degree of access to right- vs. left- brain skills. In this article, preliminary data testing the theory are provided.
INIODUCTION The synthesis offered in the previous paper (Lauter , this volume) provides a means of resolving a number of current theories and observations about reading and
reading problems. However , the predictions of that model remain to be tested empirically. To some extent, this can be done through reviews of previous data , some of which were mentioned in that paper. Additionally, the approach generates a great many highly testable predictions , particularly regarding the clustering of skils , which promises to lead to a more biologically- based classification of the variety of reading problems. We have begun testing a few of these predictions. For instance , preliminary data documenting positive correlations between performance on a test of ness
phonemic aware-
(the Lindamood Auditory Conceptualization (LAC) Test- cf. Lindamood et al.
1997) and a measure of predicted by the Trimodal Model to fine motor control- both be left-brain skils-have been reported (Lauter , 1999a). Testing has also provided
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initial confirmation (Lauter , awareness
1998a , 1999a) of the prediction that
(as assessed with the LAC) is correlated with a condition of
phonemic good hemispheric phys-
side is favored (Lauter , 1999a). In this article we report for the first time test results in children who were examined both for phonemic awareness using the LAC Test , and for eye movements with the Visagraph II (Taylor Associates; cf. Colby et al. , 1998). These test instruments were selected in the interest of employing tools which are reliable , show good subject acceptance , have established norms , and are also sufficiently inexpensive to encouriological (qEEG) asymmetry-whichever
age replication of these preliminary data as well as practical applications in clinics and schools.
TESTING THE THEORY: PRELIMINARY DATA Design and goals of the survey. The results reported here are based on a prelim-
inary survey made in response to requests from school principals at three elementary
schools in Oklahoma. The three schools represented somewhat different demographic and socio- economic status areas from the state of Oklahoma. School A was a rural school located in a small Oklahoma town , but because of its proximity to a metropolitan area , drew on a population which included a high proportion of families in which both parents were career professionals; School B was located in a relatively poor , primarily Caucasian neighborhood of a major metropolitan area in Oklahoma; and School C was another urban school from a different major metro-
politan area of Oklahoma. The principal of School C had invited all schools in her district to send children of 3rd- grade age who were having problems in school (in spite of intact auditory, visual , and general motor function); thus the set of Schoolchildren represented a mixed and somewhat unusual population , with special needs. Most of these children were from families which were lower socioeconomic status (SES) and African- American. In each case ,
we tested
all
the children in that school's third- grade
population
who were judged by their teachers as having problems with reading. At one school (School A) for a within- survey comparison , we also tested a subset of children judged by the same teachers to be " high average " readers , three from each of the school's six third- grade classes.
It should be emphasized that this survey was not designed as a rigorous experiment , that is , with a formal experimental group vs. control group structure , nor was there any effort to " match" groups according to features such as age , handedness gender , SES etc. Also , subjects were accepted into the survey based on informal teacher judgements of reading delay, rather than formal test scores. For this first step,
we were interested simply in determining how performance on the LAC vs. the Visagraph II (each interpreted against the grade- level norms provided for that test) would compare , in children who had previously been identified by their classroom teachers as having difficulty with reading. a total of 131 children ranging in age from 7 11 to Subjects . As shown in Table 3 participated in testing- 67 (49 reading- delayed plus 18 high- average) from
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Table I. Number of chldren per school, with
age,
gender and handedness summares testd reportd* mean age (range) #female/male #R/-handed School A (NR)
7 (8
(RD) School B (RD) School C (RD)
5 (8
TOTALS
6 (7
1111-
0 (7
11-
5 (8
131
116
11)
8/9
14/3
18/26 5/19 17/14
36/8 20/4 22/9
48/68
92/24
NR = Normal Reading; RD = Reading- delayed (by teacher report) after omission of individuals for whom Visagraph II readings were not interpretable (due to excessive head movement during reading, interference from eyeglasses , etc.); the following age , gender , handedness values relate to only these 116 children
School A , 27 from School B , and 37 from School C. As indicated in the table , there were 15 instances of data drop- outs due to uninterpretable Visagraph II results (excessive head movements during reading, interference from eyeglasses , etc. ), and results from the final total of 116 children wil be reported here. Details comparing age , gender and handedness of each of the groups are provided in Table I. Procedures . Each school obtained informed consent from parents for this testing to be done , with the understanding that the results would be made available both to the parents and for inclusion in the child' s school record. At each school , two separate and quiet testing rooms were identified , so that both types of tests could be done in parallel- the LAC (along with a simple handedness questionnaire , both conducted by JLL) and the Visagraph (conducted by PFM). Working in tandem in this way, we were able to complete testing on approximately 20 children per each school day.
Results. A. Phonemic awareness (LAC Test). Performance on the LAC test by these children is summarized in Fig. 1. All 17 children in the high- average- reader group from School
A received scores that were above the recommended minimum for third grade; in fact , LAC scores for 83% of those children were above the recommended minimum for fourth grade. This result is in keeping with their reported good reading performance. In the School A reading- delayed (RD) children , scores for 64% were below the recommended minimum for third grade , 6% received scores in the 3rd grade- 4th grade range , and scores for 30% were above the recommended minimum for fourth grade. Thus for the latter 30% , something other than poor phonemic awareness must account for their poor reading skils. For the RD children from School B , 67% received LAC scores below the recommended minimum for the beginning of third grade , 20% had LAC scores in the 3rd
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Phonemic awareness: summary for four groups of JOO
ii LAC
3rd
ii LAC
= 3-4lh
ii LAC" 4th 'Ii
normals (A)
school
FIGURE 1. Summary of performance on a test of phonemic awareness (the Lindamood Auditory Conceptualization (LAC) Test) for children in four groups from three schools: 17 high- average readers and 44 reading- delayed
children from School , 24 reading- delayed children from School B , and 31 reading- delayed children from
School C.
grade range , while scores for 13% of these children were above the recommended minimum for fourth grade. Finally, of the School- C RD children , 68% had LAC scores below the recommended minimum , while 6% had scores in the 3rd grade- 4th grade range , and 26% had scores above this. Thus for all three schools (in spite of their ethnic and SES differences), approxi-
grade- 4th
mately two- thirds of the reading- delayed children exhibited below- grade
level
phonemic awareness abilities (cf. a similar proportion reported by Eden et al. 1994 1995), while one- third showed phonemic awareness abilities at or above this. Note that some of these reading- delayed third- graders were even performing at a 7thgrade (adult) level on this test. Thus phonemic awareness alone is clearly not sufficient to account for reading problems in all these children- it may not even entirely account for the reading difficulty experienced by the two- thirds with below- grade phonemic awareness , since at least some of them may be additionally hampered by undeveloped skils in another of the areas listed in Table III of the previous article (Lauter , this volume).
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TRIMODAL BRAIN AND READING II B.
Eye- movement
coordination (Visagraph II).
Visagraph scores for the same sets of
children are summarized in Fig. 2. It should be noted here that correlation coefficients comparing the two sets of grade level values were all below . 01 and non- significant. The lack of correlation between the two sets of scores suggests that the two
tests are indeed independent , and assess different types of abilities- perhaps as difIII of the previous article (Lauter , this volume). The lack of correlation also underlines the variferent as predicted by the hemispheric specialization designations of Table
ety of individual differences presented by children in the classroom. Clearly neither the concept that one curriculum fits all , nor the designation of a homogeneous phenomenon of " dyslexia " can be intelligently defended in the face of such observations. As shown in Fig. 2 , the above- average readers from School A included 18% with eye- movement coordination scores below the third- grade level according to norms
for this test; 6% performed in the 3rd grade- 4th
grade range ,
and 76% performed
above grade level. The RD children from School A included 80% with below- grade
performance , 9% were at grade level , and 11% were above grade level. For School B 58% of the RD children had eye- movement scores that were below grade level , 17% were at grade level , and 25% were above grade level. Eye- movement scores for 100% of the RD children from School C were below grade level. Note that for two of the schools (A and C), even larger numbers of children exhibited below- grade- level eye-
for
Eye-movement coordination: summary of children 100
::J) ,1.
normals (A) school
FIGURE 2. Summary of eye- movement coordination performance , measured with for the same four groups of children as in Fig.
the Visagraph
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movement scores than was true for phonemic awareness-yet eye movement coordination is not routinely tested in public schools.
is clear from Figs. 1 and 2 that for all these C. Skill combinations-sub-populations?It groups of children , even the high- average readers , different combinations of skils are represented. These combinations are summarized in Fig. 3 , presenting the percentage of children from each school who exhibited difrent combinations of grade- level performance on the two tests. The upper panel considers only those children in whom phonemic awareness was below the recommended minimum. The graph plots the percentage of these children from each school who had Visagraph scores which were: a) also below the 3rd- grade minimum; b) between 3rd grade and 4th grade; or c) above the 4th- grade minimum. As the graph makes clear , in all three schools the most common combination in RD children is below-grade- level ment coordination:
perfrmance on both phonemic awareness and eye- move51 % of the RD children from School A show this pattern , 42% from
School B , and 68% from School C. (The Trimodal Model would predict that this pat-
tern of performance should be found in at least some individuals of the " middlebrain " type , characterized by blocked access to both right- and left- hemisphere skils. The center panel makes the same comparisons for those children in whom phonemic awareness was between the 3rd- and 4th- grade minimum recommended scores. Few children are represented in these categories , since few of the RD children had grade- level phonemic awareness.
The bottom panel ilustrates the combinations scores that were
based on phonemic awareness
above the minimum recommended for the beginning of 4th grade.
the next most common pattern for all three sets of reading- delayed children is above-grade- level phonemic awareness combined with below-grade- level eye move-
This panel ilustrates that
ments. The prominence of such a pattern in these data may support the prediction of the Trimodal Model that these particular children are of the " left-brain " type , characterized by good access to left-brain skils such as phonemic awareness , but relatively blocked access to right-brain abilities represented here by eye- movement coordination , and also perhaps extending to poor mental imagery. Thus it may be important to distinguish between children whose phonemic awareness is at grade level (center panel) vs. those who have the skil in an advanced form (bottom panel).
As indicated by the data for the latter groups of children phonemic awareness that is well above grade level may in some cases actually indicate a brain that has reduced access right- brain specializations. D. Importance of other skills?There is a third and somewhat more puzzling pattern ilustrated in Fig. 3- at least some of the reading- delayed children (10% from School A and 4% from School B) have both phonemic awareness and eye- movement coordination scores that are
at or above grade level.
The obvious question is: " Why
do
these
children stil have reading problems?" As noted in Table
III
of the previous article (Lauter , this volume), there are other
skils that predictably contribute to reading but were not formally assessed in this survey. For instance , mental imagery has been related both to performance on a design reproduction test and to elementary- school math skils (Lindamood et al. , 1997). Our
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TRIMODAL BRAIN AND READING II 100
a) phonemic awareness -( 3rd grade
nurmaJs (A)
;choul 100
b) phonemic awareness = 3rd - 4th grade
Hannah (A)
school 100
c) phonemic awareness;o 4th grade
Sf)
school FIGURE
3. Summary of the combined performances on phonemic- awareness and
eye- movement coordination for the four groups of children from Figs. 1-
,"
, "
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survey did not provide time for assessing imagery, but further work along these lines
might shed some light on how imagery interacts with these other skils to support reading abilities.
These very preliminary findings suggest that by assessing a constellation of these fundamental skils , we can characterize each and every child in a specific and generative way. Such an approach should be " generative " not only with regard to a better understanding of the combination of abilities and lacks presented in each child , but also an objective foundation for the design of customized training to ensure that all children in a classroom are supplied with essentially the same toolbox of fundamental skils , with clear importance for all areas of learning, not reading alone.
IMPLICATIONS FOR SKILLS IMPROVEMENT
TIROUGH TRANING
The results of this preliminary survey suggest that it is possible to document individually- specific degrees of development of each of several fundamental skils related to reading and to learning in general , and that this can be done using relatively inexpensive testing methods. As noted in the previous paper (Lauter , this volume), the Trimodal Brain model considers that virtually all brains , representing whatever point along the posited continuum , are born with the " hard-wiring" or " neural modules " for all of these fundamental skils in place and intact. According to the model , observed differences in reading ability from person to person , such as those documented in this report , are attributed not to loss of the modules , or damage to them , but to difrences in degree of access to the modules which characterize the brains of different individuals. This approach thus stresses a dynamic organizational" model for brain function rather than a static lesion- oriented" one. It suggests that when fundamental skils such as phonemic awareness or mental imagery are not evident in a child , it should be assumed that those capabilities are present but latent , unexpressed , and that with the proper training, the skils can be " waked up " and made available for use in a bootstrap " way, for that child to build on and become an independent learner.
With regard to reading
problems
describe these brains as " sleeping"
, it may be biologically more accurate to
with regard to one skil or another ,
rather than
disordered. " One would not say that a student who can t reliably hit a baseball when he first comes to try out for the team is disordered- he may just need coaching and training, tailored to his presenting level of skill. Treatment" or " remediation of reading skils can then be better understood as a training, analogous to athletic training, in which an individual who does not express a skil " naturally " (as in a " natural athlete ) can stil be rendered competitive
type of
, by means of customized , intensive behavioral training procedures. Surely with all the tools for individually- specific profiling that we have at our disposal , we can learn to become as objective and systematic in our observations of individual differences in reading, as coaches have become in their ability to identify in that skil
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TRIMODAL BRAIN AND READING II
exactly what program of training is best to help any particular individual become a star lineman or gymnast or basketball player.
There are already a number of programs which have been used successfully, some of them for many years , to improve fundamental skils for reading and learning in a variety of types of individuals. Examples include: 1) for phonemic awareness the Lindamood Phoneme Sequencing (LiPS) program (formerly Auditory Discrimination in Depth- cf. Lindamood et al. , 1997); 2) for mental imagery, the Visualizing/Verbalizing Program (V IV - cf. Lindamood et al. , 1997); 3) for eye movement coordination , the training programs used by developmental optometrists known as Visual Training (cf. descriptions by Heath et al. , 1976 , Solan 1985 , Atzmon 1985; Cohen , 1988; Sigler & Wylie , 1994; Major & Kudija , 1994; Ciuffreda , 2002); and the computer- based programs offered by Taylor Associates , based on the Visagraph II; and 4) for general sensorimotor training, which may " tune up " a system to better respond to these other types of training, exercises for whole- body motor control and multisensory
integration such as the MI- 2000 program (cf. Fadigan.
1998) and NeuroNet (designed by Nancy Rowe , cf. www. neuronetonline. com).
Each of these programs is available in versions appropriate for classroom
use
and research has been done documenting effectiveness. For instance , one study using
a classroom version of Visual Training (the protocol recommended by the COVD Optometric Guidelines for School Consultancy- d. Hellerstein et al. , 2001) was recently conducted with children from one of the three schools (School C) mentioned above (McKane et al. , 2001). Twenty- nine children with reading problems were recruited and divided into an experimental and a control group. During three and a half months of the spring semester , both groups received a combination of programs designed to improve their auditory-verbal performance (including the LiPS and V /V programs- d. Lindamood et al. , 1997). In addition , the experimental group was treated with the COVD program implemented by a board- certified optometrist and administered by school personnel , on a daily basis for 30 min/day. In a comparison of measures taken at the beginning and end of the semester , both groups showed significant improvement in reading scores on the Wide Range Achievement Test (WRAT), but eye movements during reading showed significant improvement only in the group which received the Visual Training.
Of course , behavioral changes with training need to be correlated with information about the underlying biology. In order to identify individually- specific characteristics related to the Trimodal Model , and to document changes in the central
nervous system associated with training, it is not necessary to use high- cost brain imaging technologies such as functional magnetic resonance imaging (fMRI) or positron emission tomography (PET). In fact, a combination of relatively inexpensive techniques such as otoacoustic emissions , auditory brainstem response testing, and small- array quantitative EEG (cf. Lauter , 1992), combined in a coordinated testing design, such as employed in the Auditory Cross- Section (AXS) Test Battery (Lauter , 1998b , 1999c , 2000a , 2002a , 2003) can serve not only to generate " neurological fingerprints " of individuals , characterizing each person in terms of dynamic relations along all three body/brain axes (Lauter 1998b , 2000a), but also to document
, "
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neurobiological changes in each individual tested associated with interventions such as treatment with medications (e. , meclizine hydrochloride , Lauter et al. , 1999; Ritalin , Lauter , 2000a), as well as behavioral interventions such as the training programs listed above. As we learn more about the neurobiology of individual differences in access to fundamental skils , and the capacity for change in children who undergo training, we may come to see that in the case of reading problems disorder " may be more a sociological than a biological term. It is certainly true that a lack of reading skils can be extremely maladaptive in our current (and in that way, historically unusual) soci-
ety. But we wil approach individualized assessment and training programs very differently- and may only be able to persuade our educational system to make the revisions required-if we entertain the possibility that reading may be easy and " natonly a minority of human beings (Lauter , 2000b , 2001 , 2002b). If experiments similar to the one described here continue to find that a very large
ural" for
number of children in our schools do not have complete access to all these fundamental skils , and that different levels of access can exist in entirely normal brains then we wil be motivated to find ways to include assessment and training in these skils in the earliest stages of education. Of course , resources are important, but given that the question is one of degrees of access , not levels of pathology, it is predictable that such training wil benefit all children , much as physical education is generally accepted as beneficial for improving sensorimotor coordination and strength in all children. If so , we may be able to devote more resources to training than to assessment , and simply make training in
these fundamental skils part of the standard kindergarten and first- grade
school
experience. If the predictions of the Trimodal Model continue to be borne out, we wil not be able to go on assuming that all children have equal access to all the required fundamental skils , or that the deficiencies we observe arise only from abstract higherlevel" functions such as language. We can no longer refer to " dyslexia " as though it were a homogeneous condition , or persist in considering reading problems as signs of a damaged brain. We may need to internalize the lesson that the nervous system is more diverse than we thought, and that our children come into the world with a rainbow of abilities , not all stamped from the same mold. At the same time , as long as our society continues to deny an equally diverse set of options for lifelong contribution and fulfilment , we need to take the steps to ensure that all children are trained in that particular set of skils which wil enable them to flourish in our increasingly hyperliterate society.
REFERENCES Atzmon , D (1985). Positive effect of improving relative fusion vergences on reading and learning disabilities.
Binocular Vision
, 39- 43.
Ciuffreda , KJ. (2002). The scientific basis for and effcacy of optometric vision therapy in nonstrabismic accommodative and vergence disorders. , 735- 762. Optometry,
, j. 085- 096
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Cohen ,
A.H. (1988). Special report: The effcacy of optometric vision therapy. Journal of the American Optometric Association , 95- 105. Colby, D. , Laukkanen , H. , Yolton , RL. (1998). Use of the Taylor Visagraph II system to evaluate eye movements made during reading. Journal of the American Optometric Association , 22- 32. Eden , G. , Stein , j.F. , Wood , H. , Wood , F.B. (1994). Differences in eye movements and reading problems in dyslexic and normal children. , 1345- 1358. Vision Research Eden , G. , Stein j.F. , Wood , M. , Wood , F.B. (1995). Verbal and visual problems in reading disability.
Fadigan
Journal of Learning Disabilities
, 272- 290.
assessment and MI- 2000 and high- school students.
(1998). Effectiveness of the Structure of Intellect (SOl)
training program used with 760 inner- city
middle- school
Unpublished report available from Learning Point , 6355 Metro West Blvd. Suite 455 Orlando FL 32835.
Heath , EJ., Cook ,
P. ,
O' Dell , N. (1976). Eye exercises
, 435. Hellerstein , L.F. , Danner , R , Maples , W.
and reading efficiency.
Journal of
Academic Therapy,
guidelines for school consulting.
, Press , L. ,
Schnee beck ,
j. (2001).
Journal of Optometric Vision Development
Optometric , 56- 75.
Lauter j.L. (1992). Processing asymmetries for complex sounds: Comparisons between behavioral ear advantages and electrophysiological asymmetries based on quantitative electroencephalography (qEEG). Brain and Cognition , 1-20.
Lauter
j.L. (1998a).
Neuroimaging and the Trimodal Brain: Applications for developmental
Folia Phoniatrica et Logopedia , 118- 145. Neurophysiological self- control: Modulation in all things. , 543- 549. Communication Disorders
communication neuroscience.
Lauter ,
j.L. (1998b).
Journal of
Lauter , j.L. (1999a). Functional asymmetries and the Trimodal Brain: Applications to developmental disorders. Journal of Developmental and Learning Disorders , 181- 260. Lauter , j.L. (1999b). The Handshaking Model of Brain Function: Notes toward a theory. Medical Hypotheses , 435-445. Lauter j.L. (1999c). The AXS Battery: Promise for Communication Neuroscience. Presented to American Speech- Language- Hearing Association , San Francisco CA. Lauter , j.L. (2000a). The AXS Battery: Meeting the challenge of individual differences in human brain/behavior relations.
Behavioral Research Methods, Instruments and Computers
, 180- 190.
Lauter , j.L. (2000b). The brain and reading: Neural bases for a new perspective on reading skils assessment and training. Invited presentation to Idaho State Conference on Reading and Learning, Boise ID. j.L. (2001). Is reading ' unnatural' for 2/3 of our children?- Right
Lauter
brain ,
left brain , and
the " missing link" skils for reading and learning. Invited keynote presentation to SouthWest and Rocky Mountain division of American Association for the Advancement of Science , Denton TX. Lauter j.L. (2002a). The Auditory Cross- Section (AXS) Test Battery: A new way to study afferenUefferent relations linking ear , brainstem , and cortex. Presented to Acoustical Society of America , Pittsburgh P A. Abstract: Journal of the Acoustical Society of America 211 , 2338. Lauter , j.L. (2002b). Is reading ' unnatural' for 2/3 of children and adults? Presented to American Speech- Language- Hearing Association , Atlanta GA. Lauter , j.L. (2003). Otoacoustic emissions and the ' set of the center: ' a new test battery and new statistical treatment. Presented to Acoustical Society of America , Nashvile TN. Abstract:
Journal of the Acoustical Society of America 113 , 2198.
Lauter , j.L. , Wood , S., Lynch , 0. , Schoeffler , L. (1999). Behavioral and neurophysiological effects of meclizine in young adults , measured with otoacoustic emissions , REPs/ ABR qEEG , and a computerized test of eye- hand coordination. Perceptual and Motor Skills, 88 707- 732.
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Lindamood , P. , Bell , N. , Lindamood , P. (1997). Sensory- cognitive factors in the controversy over reading instruction.
McKane ,
P.
, Maples , W.
, 143- 182. P. , McNeil , M. (2001). A comparison of auditory/lan-
Journal of Developmental and Learning Disorders , Sellars ,
guage therapy with school visual support procedures in a
Optometric Vision Development
school setting.
Journal of
, 83-92.
Major , D. L. & Kudija , K.R. (1994). Positive effects of optometric vision therapy on reading scores , behavior , and recidivism among delinquent youth. Optometry and Vision Science 71 (Suppl), 105- 106. Sigler , G. & Wylie , D. T. (1994). The effect of vision therapy on reading rate: A pilot study. Journal of Behavioral Optometry,
, 99- 102.
Solan , H. A. (1985). Deficient eye- movement patterns in achieving high school students: Three case histories.
Journal of Learning Disabilities
, 66- 70.
Mailing Addresses:
Judith L. Lauter, Ph. Professor Director, Human Neuroscience Laboratory Dept. of Human Services, Box 73079 SFA Station Stephen F Austin State University, Nacogdoches, TX 75962 jlauterr:sfasu. edu/936- 468- 7252/FAX 936- 468- 7096
P Frank McKane, Ph. Director, Center ftr Study of Literacy Oklahoma Literacy Clearinghouse Northeastern State University
Trhlequah, OK 74464
An audio- visual overview of some of these issues (Trimodal Brain model , the AXS Test Battery, applications to reading) is provided in: J.L. Lauter (2002)
How Understanding Individual Difrences Can
Improve Your Clinical Practice.
Neuroimaging: (3- hr edu-
cational video with manual) Rockvile , MD: American Speech- Language- Hearing Association. Available from ASHA professional catalog (1- 888- 498- 6699), item #0112397.
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Technology s Role in Encouraging Social and Cognitive Development in Children with Autism
Daniel R. Gilette, Ed.
Abstract.
In this article,
the author discusses
why using technology is a critical component to
human development, why it should be included in developmentally based educational programs
for children with autism and how to avoid common setbacks when including technology in such programs. Also given is the case study of "Alice a child with severe autism who made great strides after a new technological artifact was introduced to the culture that included Alice and her caregivers.
Introduction Many parents and caregivers of those with autism have noticed how technologyoften in the form of computers , mechanical toys and electronic games- has a powerful impact on their children. Often children are able to attend for longer periods of time , are more inquisitive and more active. In some cases , a child with poor proprioception may have better motor control when controlling a cursor via a mouse than by pointing with her own finger. Though , in such situations , technology can be quite powerful , it may come at a cost , such as the child becoming lost in the virtual world some technology affords , or using the tool or toy exclusively for self- stimulating behavior , or stimming. For these reasons , technology often is not incorporated fully into most education plans for children with autism. Additionally, some technologies may stifle natural social interactions , further adding to the concern that social skils may suffer at the hands of technology. Stil , as this article wil discuss , technology not only has a critical role to play in the development of children , but also can support other educational goals. This article is broken into two parts. The first section discusses why including technology in a developmentally based education program is important and provides suggestions to ease the inclusion of technology in such a curriculum. The second section is a case study that provides how including technology in an education plan can lead to unanticipated but positive results. lThis is a phenomena many parents and teachers have pointed out to me. It is possible that this " move-
ment by proxy " is easier for those with proprioceptive problems because attention is focused on moving another object , such as a computer cursor , instead of on moving one s own body.
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A Developmenta Perspective on Technology To explore the use of technology as a possible component of a comprehensive skils program for a child with autism , one must first be able to comprehend the reach
of technology in everyday life. The word technology does not only represent the trains we take to and from work or the computers we use there , but also pencils paper , sports equipment , kitchen utensils and many other often overlooked artifacts. In fact
, the majority of human artifacts incorporate technology of some sort.
Creating and using technology is a very human trait,
with only a few other
species capable of creating tools. Technology is also a collective record , with iterations , proposed settings for use and methods of utilization (technique) acting as an account of society' s concerns , ambitions , aesthetic , economy, politics and social structure-what types of tools are made for what kinds of sensibilities to solve what problems and for whom? One cannot escape technology, for if she were to try, she would find herself constructing technological artifacts of her own simply to survive. For these reasons ,
incorporating technology into a skils program is critical not just
when it makes delivery of treatment easier or less expensive , but if total human development is the goal.
Think for a moment what we typically ask technology to do for us. Technology is often used to accomplish the following: . Attend to
basic needs such as the production and maintenance of shelter , food
and clothing . Augment our
physical capabilities in the form of
tools and transportation
products
cognitive abilities with memory and computation aids , such as books , film , calculators and computers Extend our ability to communicate through multiple forms of media , including print , television , telephone , email and the Internet Express creativity through the use of musical instruments; brushes and paints;
. Augment our . .
smelters; etc
If one were to list some of the obstacles facing those with severe autism , on the list would probably be the very things for which we most employ technology. Also
for those with autism many technological artifacts ,
due to their refined and pre-
dictable nature , may be more entertaining; easier to comprehend or study; represent adequate solutions to problems; and easier to interact with than humans. But technology that is so provocative and powerful may also be difficult to compete with for attention , causing caregivers to limit how much such tools are used. Additionally, it seems that the more magical and powerful the tool , such as computers , the more compelling it is to children with ASD , but that very power can be difficult to comprehend and harness in a therapeutic setting. Stil , with proper selection and planning, high technology, such as computers and video games , can play an important role in psycho- educational plans for children with autism.
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Computer Use in a Social Context Often parents and teachers are faced with the situation where a child is very motivated by working with a computer , but while interacting with the machine , the child may not be receptive to the social overtures of others. This either plays out as ignor-
ing others or becoming agitated when someone else attempts to join in with the play. Often these behaviors are attributed to the hold the technology has on the child- suggesting that he is being " sucked in " or mesmerized by the computer. As discussed earlier , this may be somewhat true. After all , who hasn t fallen entranced to the repetitiveness , order and unwavering presence of the computer after too many hours working with the tool? More likely, the child is just responding to the computer in
contextually appropriate manner. When one uses a pen , remote control or hammer , the focus is on the object to be acted upon- the pad , the television or the nail. When we use such tools , we work through them. Computers are different. When one uses a computer to create or interact with an object, except in specialized situations such as semi- automated factory work , the objects we are working with are virtual and reside in the computer. We seldom work through computers , but on them; the computer becomes the target of our attention. For this reason , computers pull at our energy and attention the way a halfclosed door into an unknown room beckons us to explore. Additionally, entering into the workroom of the computer environment, it becomes difficult to interact with those back on the other side of the proverbial looking glass. This is exacerbated by the fact that we do not fully enter the virtual work environment, but straddle the edge between the real and virtual. Socially, this is problematic , because it requires one to focus most of his attention on the virtual workspace while also needing to attend to the social cues of others located in the tangible world. Though much of the software written for computers is intended for use by a single person , many educational and multimedia software is either neutral in this regard or actually meant to be used in a collaborative way. Stil , even when using collaboratively focused software , interpersonal interactions tend to falter when we gather around a single computer. Though blame is often rightfully rested on the shoulders of the software engineers and designers , the main impediments are rooted in the tangible computing objects , the hardware. If a teacher and child wish to have a collaborative experience that includes using a computer , many physical problems stand in their way. The following lists the most common problems I have observed when people try to use computers in a social manner:
.
Desktop and laptop computers require that both parties physically orient themselves in the same direction , looking toward the screen. This makes it difficult to cue to communicative gesture or judge attentional focus. Standard computers have one set of controls , such as keyboard and mouse meaning that though both parties can passively experience the computer at the same time ,
only one person can actively engage with the device at any
given moment. Also , since these tools tend to be awkward to reposition and
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require a specific physical orientation for use (that of being positioned squarely
in front of the screen and controls), turn taking requires a dance that is difficult to master. As a result, turn taking ceases to be spontaneous and becomes somewhat scripted. Turn taking occurs at the end of a software- defined interaction or when something goes wrong, not when the overarching social context dictates.
. The available hardware interface tools (mice , keyboards , trackballs , displays
etc. ) may not be suitable to the motor and cognitive profile of the child.
Traditional computers are difficult to position in a way that is socially appropriate. Desktop computers are mostly immobile , and laptops , though portable are stil not that flexible in terms of where we put them in a room. The result is that computers are generally used in locations that are selected based on the needs of the computer , versus the needs and goals of those wishing to use the computer. This often means leaving an area of comfort, support (in terms of
computer space. The result is that it is either computer time or not, again giving focus to the tool , not the related goals. Inversely, if the computer area becomes the place of comfort and security for the child , problems may arise in that such an area is seldom suitable for other tasks. available physical resources) and security and transitioning to a
Though the " movement- by- proxy " aspects of the virtual computer interface- the way in which our movements play out as the movements of another object , such as in how movement of the mouse controls the computer cursor- may actually be help-
ful for some people with autism , it has its own inherent problems in a collaborative context. Since the tools for controlling the objects on the screen are fixed in our real world (i. e. the mouse), but the objects they control (the cursor , buttons , etc. ) are situated in the virtual world , the rules that dictate how collaborators share virtual tools are complicated. When sharing crayons , most of our attention can be vested on the social interaction that leads to crayon exchanges. When sharing virtual tools , we must juggle multiple contexts-what some would deem as multiple realities (a virtual and a real one)- on top of dealing with social requests and appropriate responses. For instance , if a teacher attempts a virtual crayon exchange in a coloring application should he ask for the crayon in the virtual environment , or for a turn at the mouse in the real environment? More vexing is trying to determine what the child really gets out of this exchange: a lesson in social interactions or in metaphysics? At this point the reader may view the situation of using a computer in a socially
supportive manner as near hopeless. Actually, it does not take much to resolve the majority of these problems.
Preparng to Use Technology in a Developmentay Based Education Program Though technology, especially that which wil be used in a manner unintended by its creators , usually leaves us wanting, shortcomings can be overcome by properly
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101
designing the use of technology into the education program. When considering what types of technology should be included in a developmentally based psycho- educational program , there are key areas that need to be addressed. Technology should not be used as a one- size- fits all solution or seen as appropriate for all situations , which means there are no hard and fast rules for deciding when and which technology should be used. Some reasons for using technology as part of a developmentally focused education program are: . To provide improved access ,
both physical and cognitive , to the environment
(mobility aids , home automation , sensory aids), communication/social settings (augmentative communication devices and computer access devices that allow virtual communities), information (schedulers , computer access devices to the Internet and media translators , such as text to speech systems or Braile printers) and other technologies (alternative computer input devices).
. To
.
.
.
create an environment where certain content and skils training can be
delivered more effectively, such as computer games that provide an opportunity for the child to practice skils required for escaping a burning building (for examples , see http://www. dotolearn. com/). To provide a highly consistent representation of information and skils training (recorded speech libraries that pronounce words exactly the same each time they are uttered). To provide a fun and rewarding experience (video games , videos , toys and music players). To train a specific skil so more complex tools may be used in the future.
. To
track user actions for later analysis (computer administered proficiency
tests or electronic counters).
Often we use technology in ways unintended by their creators , which makes sense , since much of technology can be best described as tools , and when working with tools , one must work with what is available to get the job done , even if the avail-
able tools are technically inappropriate for the task at hand. Therefore , we cannot and should not rely on the marketing of technology to fully inform how it should be used. Instead ,
each piece of available technology
should
be considered in context of
how , where and by whom it might be used. Here are some questions to ponder to assist in making well informed technology decisions: . What are the goals of the program unit: Without having a clear main goal , one
cannot pick appropriate tools to assist in that goal. . What are the skils being targeted: Technology should be chosen so it supports
instead of negating the educational goals.
be employed in the unit: Since using technology for its own sake is seldom a goal in a socially based program , one should choose technology in regard to how it supports other pieces of the puzzle. Even when teaching a tech- specific skil , a social component should be involved. . What technology is available or can be made available in the environment: . What methods wil
Does it make sense to make do with what is available or to seek out a new
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tool? If seeking out a new tool , how close should its intended use be to the way it wil be utilized in the program? Also , are the costs and familiarization process reasonable in relation to the need? . What is the operational models) of the technology to be used: Consider how one must orient herself, both physically and attentionally, to use the technology. Also , be aware of environmental limitations of the technology that might be a factor , such as , resistance to liquid spils or being dropped. Additionally, physical access (how does one physically control the device) should be probed in regard to the motor and cognitive abilities of the child. . Why is each piece of technology being introduced: Surprisingly, this may be
the least investigated question when introducing technology into an educational plan , but by clarifying such a motivation , a mindset is encouraged that wil prevent many missteps. To avoid using technology simply for its own sake , a contextual focus on tool use instead of focusing first on the tools available , makes sense. To ilustrate , a contextual focus would yield the statement: to build a chair , one could use a saw , a hammer
nails and glue. A tool- oriented focus would look like this: a hammer can be used to put nails into wood , pull nails out of wood and to break plaster. When a tool-based focus is applied , there is a tendency to use the tool in question even if such a tool is not required or contributes to learning in a meaningful way. When a contextual approach to tool selection is taken , it is much more likely that selected tools wil be used in service of the main curricular goals , versus being presented simply due to availability.
Tool Use to Encourage Problem Solving, Experimentation Creativity and Social Interaction By using technology, one must become a problem solver. On one level , the conbe understood , as do the
text of the problem- the reason for needing a tool- must
capabilities afforded by available tools. Then the merits of various tools must be weighed and a tool or set of tools selected. On another level , problem solving occurs when trying to figure out how to use a given tool in a specific context. By using tools children inherently become problem solvers. Additionally, to gain proficiency with a tool , experimentation and practice is required. To ilustrate , think about the experience of renting a car. Even though there are labels on all the knobs , dials , etc. (except
the most standard , such as gas and brake), some experimentation must occur to fully discern their functions. Further , a calibration must take place in regard to the use of the car s controls , such as testing the responsiveness of the gas and brake pedals. Inherent in this exploration is a reciprocal interaction with the machine: the driver provides cause , say by pushing on the accelerator , and the car reciprocates with the effect of moving forward. But there is also a contextual component in this relation-
ship, since the car must not be in park for the request for movement (pushing the accelerator) to have the intended outcome.
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I do not wish to anthropomorphize technology, but it is important to recognize that all tools do , in a way, train us in how to use and interact with them-we learn from the experience of using tools much like we learn from collaboration with others. As a result, using tools teaches skils that should be possible to generalize to social contexts. In fact, I have found that when working with learning disabled clients with
profound skew to the concrete nature of information and the world , relating social settings to equations or machines can be quite helpful , especially when exploring
how different contexts vary outcomes.
Alce: An Anecdote Last year , I had the opportunity to witness how a new piece of technology led to positive outcomes for a child with severe autism. The ways in which the technology played its role was somewhat unexpected , impacting not only the child directly, but also reshaping the culture the child was a part of. The tool was a prototype voice out-
put communication aid (VOCA) that my colleagues and I were designing for Archimedes Access and Research and Technology, Inc. , made possible by a grant from Cure Autism Now. The design team consisted of Neil Scott, James True , Nina Paley, Heather Clare , Kevin Gil and myself. This early prototype , while promising, was stil quite embryonic and had a tendency to be a little quirky and unpredictable. The VOCA consisted of a picture- based software application that allowed for the collection of icons whose corresponding words would be spoken aloud by the device. The hardware was a somewhat dated pen computer (it was slow) that accepted
presses by a stylus or finger nail on the screen as its main form of control (this replaced the need for a mouse). What follows is an anecdotal account of one of the children , Alice , involved in a usability study of the prototype VOCA.
Alice (a pseudonym), was a six year old girl with severe , regressive autism. While quick to smile and apparently a generally happy child , at the beginning of the study
Alice had almost no communicative skil , aside from tugging on sleeves or reaching for people and objects. Alice s ability to visually discriminate objects was at an almost non- existent level in typical educational settings; she had no functional pencil grip; showed little to no awareness of cause and effect; had no interest in computers; and attended to auditory stimuli but showed no consistent interest in visual stimuli. Alice s skils building had slowed dramatically in the year leading up to the study, even with an intensive , multifaceted program. Twelve weeks after the study began Alice was choosing the stylus in her attempts to control the VOCA , even though she had finger pointers fashioned out of plastic guitar fingerpicks and a grown fingernail that allowed for more direct control; was experimenting and problem solving in her
environment; could visually discriminate between around 20 objects; chose to work with a caregiver on the VOCA to request objects instead of simply grabbing them;
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and most significantly, was not only making decipherable (by familiars) attempts at speech , but doing so in a contextually appropriate manner. It was a startling change. Though Alice was almost rejected for participation in the study because she did not possess skils at the level deemed appropriate for inclusion , she taught me the most. In the year since this study, my gaze turns to the intersection of how the VOCA was made part of the social activities involving Alice and how it supported experimentation in emerging skils in such a setting. While my colleagues and I would be more than happy to take credit for Alice s improvements , there was no evidence to suggest that the VOCA had by itself led to most of her improvement, aside from some strides in motor skils. Alice had a change in medication a few months earlier but that also was unlikely to account completely for the observed changes in her behavior and abilities. It is clear to me that how the VOCA became a focus of social interaction had as much to do with Alice s improvement (if not more) than any other factor. To understand how the VOCA set the stage for a change in the culture surrounding Alice , we first must look at how the tools were chosen and introduced.
Selection The decision to use a tablet computer was never doubted by the VOCA design team. There was some interest in using smaller pen-based computers , such as palm-
sized PDAs (personal digital assistants), but early design research suggested that such a form factor was less than optimal if the ultimate goal was communication via the device at a close to normal pace , since the smaller screens made it more difficult find and manipulate icons. There were limitations with the tablets that were readily available at the time and in the range of the project budget-limitations of speed , battery life and display quality-but the tablets were quite durable and in general fit the bill. I learned through earlier study that social interaction was more natural when using the tablet , versus the desktop computers used in previous studies of mock- ups
primarily due to the fact that the tablets can be positioned and shared like a pad of paper or a book. Stil , for Alice , this software and a tablet computer posed some problems.
Though the VOCA software
being tested provided natural speech output
(recorded voice instead of computer synthesized), which was expected to be of value to Alice , the interface for selecting and using words was almost exclusively graphical which played upon some of Alice s greatest weaknesses. Also , to use the device , Alice
would need to be able to point at , tap and drag objects on the computer screen another weak area. Though alternative access methods could have been employed none seemed any more appropriate , and if Alice could learn the skils for operating
the VOCA , primarily pointing, then the door to most other forms
of technology
would be opened (pointing, when combined with another action , is the most common method for interacting with technology, be it triggering a power switch , chang-
ing a channel on a remote control or typing). As part of a holistic skils program , the VOCA would serve a role well beyond its intended design of facilitating communi-
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cation; it was expected to be a medium for the acquisition of skils that could be generalized to other situations.
Introducing the Tool
Alice had no real interest in computers and had a tendency not to attend to visual stimuli , so it was unclear how Alice would take to the VOCA. When first introduced to the device ,
Alice showed little interest and was easily distracted. Though she seemed curious about the speech output of the device , it wasn t enough on its own to hold Alice s attention. Alice actually did not attend to the device for a sustained period until there was a group made up of myself, her parents and one of her aides all playing with the tool and being social around it , sharing our discoveries and collaboratively exploring the capabilities of the machine. It was in this setting that Alice approached the device and cocked an ear to the aural output. If the device had not been put into a social context, Alice probably would not have spent enough time with it to get hooked by the speech output she so much appreciated. Using the VOCA in a social context became the key for Alice to learn the features and intended purpose of the device.
Gaining Skils in a Social Context Alice needed to acquire the following skils to use the VOCA to communicate: . Visually
discriminate between objects
. Point at objects
screen with either a fingernail , finger pointer or stylus across the screen . Order screen objects to create phrases . Understand the cause and effect all of her actions had on the device . Tap on the
. Drag items
In general , all of these skils were already part of Alice s education plan , though paper and caregivers acted in place of the tablet. Historically, when working on these skils , Alice would attend for a few minutes and then lose focus. Alice was somewhat easy to involve in activities , but had difficulty staying on track. Alice seldom worked for a reward , so activities needed to be intrinsically rewarding. Though her caregivers made noble attempts to make her skil building sessions more engaging, there was little in the physical world that Alice was interested in. It was expected that there would be similar difficulties in teaching Alice how to work with the VOCA , but over time Alice was able to attend more and more to sessions that included the device , and by experimenting with the device , Alice made significant strides. For instance , Alice began to put her head near the computer screen while dragging the stylus across the screen , which caused the cursor to follow. Alice spent a good amount of time experimenting and observing the cursor/stylus relationship. A few days after this experi-
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mentation began , Alice s mother observed her problem solving in the environment for the first memorable time. Alice was asked to bring a bunch of potatoes from one part of the kitchen to the other. Instead of following her usual routine of moving one at a time , she placed the potatoes in a bag and moved them en- mass. Was there a
direct link between experimentation with the VOCA and this behavior? It is hard to say, but Alice s caregivers suggest that she began to do more and more physical problem solving after the VOCA was introduced to her. The reasons why Alice was able or more wiling to attend to sessions that
involved the VOCA are not clear , but the following seemed to contribute to her interest: . The intrinsic value of the aural output ,
both in that it produced sound and that Alice had a skew to the auditory, and that the device spoke , which was something Alice very much wanted to do , as witnessed by her regular attempts to produce words
device was not introduced at first as a communication tool but just as a new interactive object; as a result, it was something to engage in play with and explore Since the device was new to the entire culture that grew up around Alice , she was not the only " true " investigator , which made the playful investigation more of a sincere collaboration where Alice was as likely to show her caregivers a feature as they were to model for her The device could not be rushed in its response and did not " time out" in interactions , but simply stood ready for the next interaction , meaning that Alice had as much time as she needed to prompt the device and the response of that prompting was never truncated
. The
.
.
I believe that though all of these points may have been significant , the intrinsic payoff for Alice of the device speaking, as well as the true collaborative environment were what helped Alice the most to attend to both the VOCA and her collaborators. The speech output may also have driven home the idea that the device had a role in communication , since that is how all of her caregivers communicated , and was also one of the ways Alice communicated before autism stole her voice. At around the fourth week of the VOCA being available , Alice started to stand next to the device when she wanted to ask for something, even though she was yet able to operate the device on her own or had been taught to start communication attempts by going to
the VOCA; Alice had figured out that the VOCA was a way to communicate.
One of the interesting outcomes in three of the five children who were involved in this study was that
afterward they were reported to be more proficient in the use of picture communication books than before , even when previous attempts to use PECS had failed to lead to any noticeable improvements in communication. Though the reason for such an outcome is rather elusive , it is my belief that for these children the concept of using pictures to communicate didn t click when using picture- only strategies , but after using the VOCA , which gave pictures speech , that connection became more clear. Additionally, the way others responded to VOCA use may have been more socially appropriate since the speech output was more natural , and the response of others reinforced the meaning and value of the VOCA.
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Positive Side Effects When a new technological artifact is introduced to a child with autism , generally it is first introduced to the child' s caregivers. After all , it is the caregivers who set up
early sessions and provide modeling and explicit training as to the workings and purpose of the artifact. In the case of introducing the VOCA , the caregivers were expected to allow Alice to investigate the device s features on her own , but also to do extensive modeling, training and reinforce VOCA use. To accomplish this , the caregivers themselves had to investigate and play with the VOCA. Mostly, this caregiver play went on in front of Alice and added to the social buzz around the device. Also caregivers were asked to conduct sessions where they augmented their normal communication by communicating through the device in addition to their existing strategies. The caregivers own use of the VOCA was the first way that the device shaped caregiver behavior by adding another layer to their communication with Alice , but this was minor compared to what would ripple through the care team later. As stated earlier , Alice had very little facility in the skils required to operate the VOCA. As a result, she needed a lot of help using the device. For instance , Alice slowly began to point to objects she wanted but had trouble tapping the screen or dragging the object across the screen to a sentence staging area. In such cases , handover , or under , facilitation was used to complete the process. One outcome of this
was that the attention of the caregiver was very much focused on the interaction between Alice and the device. This seemed to give rise to a renewed investigation into Alice s sensory and motor abilities. Some of Alice s caregivers commented during end- of- study debriefings on how they were struck by the calmness of the device due to the soft and metered oral out-
put; how Alice tended to listen intently and wait for the device when it would operate slowly (in this early version , on this old hardware , the device had a tendency to bog down during longer sessions); and most critically, how the device would wait for Alice. Such descriptions are telling: the caregivers , though always aware of the mechanistic nature of the VOCA , did tend to see Alice s interaction with the tool as somewhat social. This often emerged in discussions about Alice s use of the device and the amount of social metaphor that was used , ilustrated by reports of the machine " waiting for her " or being " calm. " This played subconsciously on the caregivers in a most interesting way.
Over the course of the study, the two caregivers most linked to Alice s VOCA use (her mother and her school and home aide) appeared to have subconsciously modified their interaction style. At the beginning of the study, it was common for Alice to be queried repeatedly at the beginning of a social interaction. Often , the first phrase uttered by the caregiver would be pronounced twice , first in an alerting tone and prosody, and then again with proper contextual inflection. This was a habit that
the caregivers unwittingly had fallen into and probably arose in response to the fact that Alice usually would have rather delayed and subtle response to oral overtures. This likely instiled the belief that Alice needed to be alerted to the start point of verbal interactions. In time , the content of the first utterance became semantically irrel-
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evant, and instead was simply an alert to action. Also , since Alice s responses were usually delayed , subtle and non-verbal , caregivers had a tendency to query again or move on when Alice did not respond in within the natural timing window that was opened (Alice was observed to subtly and appropriately respond to queries 10seconds after a circle of communication was opened , but by that time , she often no longer had the caregiver s attention). After spending time with Alice making attempts to operate the VOCA , the interaction style of caregivers changed , sans-VOCA. Over the course of the study, the caregivers that were involved adopted a similar communication style , characterized by the following: all utterances were calm and metered; repeating of utterances stopped in the majority of interactions; and there seemed to be a near infinite patience in waiting for Alice to respond. The verbal style of the caregivers became that of the VOCA. The VOCA acted the way it did because it was a machine and could only respond when asked- it had no mechanism to evaluate whether or not its output had registered on the user and therefore had to wait for the next input. I can only hypothesize what caused the change in caregiver behavior , but I suspect that it was a combination of falling into the rhythmic interaction style the device encouraged and seeing Alice s response to prolonged pauses. The outgrowth of this change in interaction style was:
now was required to complete her turn in the social dance freedom she needed to complete her turn Caregiver speech was dramatically slowed , which may have allowed Alice to
. Alice
. Alice was given the time and
.
better process the sounds or meaning of words
of caregiver speech was now either contextually appro, the first utterance no longer being made ambiguous by an
. The tone and prosody priate or neutral
alerting tone . By requiring the VOCA be used as part of Alice s spontaneous queries (often for objects
, such as food), more of her social interactions became circular
instead of simply " point
and get"
It is my current belief that the strides Alice made in speech , gestural communication , problem solving and visual processing happened because of the more social
and consistent interaction with her caregivers. I suspect that the VOCA provided verbal modeling that Alice was able to mimic and that the device was a platform on which internally developing skils could be externalized , though many of the these elements did occur at other times in Alice s lie-it took the confluence of social (caregiver change) and environmental (the introduction of the VOCA) factors for Alice to make the progress she made. It was also the curricular notion that the VOCA could be used as a learning tool in a variety of domains , instead of seeing the device as singularly purposed for communication.
Conclusion The example of Alice shows the significant role technology can play in a developmentally focused education program. If Alice and her caregivers had immediately
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attempted using the VOCA for communication , not only would there have been profound frustration due to not knowing how to use the tool , but many opportunities for discreet skil building would also have been missed. More importantly, if the caregivers and Alice had not collaboratively explored the device s features , and instead simply took discreet turns with the tool , not only would their VOCA related skils have developed at a slower rate , but the wonderful social effects witnessed would not have played out , even if Alice did not require social activity to motivate her to play with the tool. Not only did the social focus of the curriculum help motivate Alice , it also provided a setting for the care team to further develop their skils and relationship with her. As this case ilustrates , with proper planning and focus , incorporating technology into a skil building program can encourage social growth instead of impeding it. Mailing Address:
Daniel Gillette, Ed. IDEA LAB, CalState TEACH California State University at Monterey Bay 700
Campus Center, Bldg. 78
Seaside, CA 93955 mail: dangilletter:mindspring. com
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PERCEIVING SPEECH BY EAR AND EYE:
Multimodal Integration by Children with Autism
Dominic W. Massaro, Ph. D.
and Alexis Bosseler
UT tested whether children with autism integrate information from multiple sensory modalities in speech identifcation of spoken syllables. An expanded factorial design was
Abstract.
used in which inftrmation from the fllee and voice was presented either unimodally or
bimodally, and either consistent with one another or not. After training the children speechreading to enhance the influence of visible speech from the face, we repeated the identifcation task. Children behaved similarly in the two replications, except for a larger influence of the visible speech after training in speechreading. The fuz; logical model of perception (FLMP) was contrasted with a single- channel model (SCM) because they represent comparable integration and non integration models, respectively. The model descriptions revealed that the FLMP gave a signifcantly better description of performance than the SCM, supporting the interpretation that children with autism integrate vocal and facial inftrmation in speech perception. Given these
positive findings, we propose multimodal environments for learning language.
The goal of the present research is to gain some understanding of speech perception in individuals with autism. Autism is a pervasive developmental disorder , which apparently has increased from affecting approximately 1 in every 500 children (Cowley, 2000) to 1 in 300 (M. I.N. D. Institute , University of California , Davis http://www. dds. ca. gov/ Autism/ Autism main. cfm). Although the etiology of autism varies, individuals diagnosed with autism must exhibit a) delayed or deviant language and communication , b) impaired social and reciprocal social interactions , and 3) restricted interests and repetitive behaviors (American Psychiatric Association 1994). The language and communicative deficits are particularly salient, with large
individual variations in the degree to which autistic children develop the fundamental lexical , semantic , syntactic , phonological , and pragmatic components of language (Tager- Flusberg, 1999). For the roughly one- half of the autistic population who develop some form of functional language (Tager- Flusberg, 2000; Lord , Rutter LeCouteur , 1994; Prizant, 1983), the onset and rate at which the children pass through linguistic milestones are often delayed (e. g. no single words by age 2 years no communicative phrases by age 3; American Psychiatric Association , 1994). Given their limitations in language processing, a better understanding of their speech perception should be particularly valuable. We begin with our extant view of the psy111
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chological processes involved in speech perception , followed by a consideration of how children with autism might be at a disadvantage in this domain.
Speech Perception We define speech perception as the process of imposing a meaningful perceptual experience on an otherwise meaningless speech input. The empirical and theoretical investigation of speech perception has blossomed into an active interdisciplinary
endeavor , including the fields of psychophysics , neurophysiology, sensory perception , psycholinguistics , linguistics , artificial intelligence , and sociolinguistics. In any domain of perception , one goal is to determine the stimulus properties responsible
for perception and recognition of the objects in that domain. The study of speech perception promises to be even more challenging than other domains of perception because it crosses all of these disciplines.
Our perception and understanding of speech is a multimodal process , influenced by what we hear (the sound of the speakers voice) and what we see of the face and accompanying gestures (Massaro , 1998). Research has repeatedly shown that pairing the auditory speech with visual speech from the face produces a percept that is more accurate and less ambiguous relative to presenting either of these modalities alone (Massaro , 1984; Summerfield and McGrath , 1984). Viewing the speaker s face increases the intelligibility of what is being said , especially when the auditory information is degraded by noise (Sumby & Pollack , 1954) or hearing loss (Erber , 1969). For example , viewing the speaker s face can improve intelligibility of the spoken message as much as 15 dB in the speech to noise ratio (Sumby & Pollack , 1954). Viewing the speaker s face to augment the spoken message is not limited to situations in which the auditory input is degraded. Perhaps the most compelling demonstration of the impact of visible speech on perception of the spoken message is the McGurk effect (McGurk & Macdonald , 1976). In this classic demonstration , participants were presented a film of a young woman saying /aga/ that was dubbed with the sound /abal. The participants often reported hearing /ada/ , putatively a fusion of the place of articulation features of /aga/ and the manner and voicing features of /bal
(we provide an alternative explanation after our theoretical framework is developed).
When the dubbing process was reversed (an auditory /agal dubbed onto /abal lip movements) participants sometimes reported hearing /abga/ , a combination of the two syllables. Similar results were found with /pa/ and /ka/. This McGurk effect provides evidence that speech perception is a bimodal process , influenced by both the sight and sound of the speaker. A theoretical account of bimodal speech perception must describe how each source of information is evaluated , whether or how the sources are combined or integrated , and how classification decisions are made.
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The Fuzzy Logical Model of Perception (FLMP) In the course of our research ,
we have found that the Fuzzy Logical Model of
Perception (FLMP) to be a universal principle of perceptual cognitive performance that accurately models human pattern recognition (Massaro , 1998). People are influenced by multiple sources of information in a diverse set of situations. These sources of information are often ambiguous and any particular source alone does not usually specify completely the appropriate interpretation.
The three processes involved in perceptual recognition are ilustrated in Figure and include evaluation , integration , and decision. These processes make use of prototypes stored in long- term memory. The evaluation process transforms these sources of information into psychological values , which are then integrated to give an over-
all degree of support for each speech alternative. The decision operation maps the outputs of integration into some response alternative. The response can take the form
FIGURE 1. Schematic representation of the three processes involved in perceptual recognition. The three processes are shown to proceed left to right in time to ilustrate their necessarily successive but overlapping processing. These processes make use of prototypes stored in long- term memory. The sources of information are represented by uppercase letters. Auditory information is represented by A and visual information by V . The evaluation process transforms these sources of information into psychological values (indicated by lowercase letters a, and vJ These sources are then integrated to give an overall degree of support , Se, for each speech alternative k. The decision operation maps the outputs of integration into some response alternative , Re. The response can take the form of a discrete decision or a rating of the degree to which the alternative is likely. The feedback is assumed to tune the prototypical values of the features used by the evaluation process.
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of a discrete decision or a rating of the degree to which the alternative is likely. The
assumptions central to the model are: 1) each source of information is evaluated to determine the continuous degree to which that source specifies various alternatives 2) the sources of information are evaluated independently of one another , 3) the sources are integrated to provide an overall continuous degree of support for each alternative , and 4) perceptual identification and interpretation follows the relative degree of support among the alternatives.
Although speech perception has traditionally been viewed as a unimodal process
it appears to be a prototypical case of multimodal perception. As described in the introduction , experiments in face- to- face communication have revealed conclusively that our perception and understanding are influenced by a speaker s face , as well as the actual sound of the speech (Massaro , 1998). Research has shown that the results are well- described by the FLMP , which is an optimal integration of the two sources of information (Massaro , 1998). A perceiver s recognition of an auditory- visual syllable reflects the contribution of both sound and sight. For example , if the ambiguous auditory sentence, My bab pop me poo brive is paired with the visible sentence My gag kok me koo grive the perceiver is likely to hear My dad taught me to drive. Two ambiguous sources of information are combined to create a meaningful interpretation (Massaro , 1998).
Development of Bimodal Speech Perception The multimodal nature of speech perception has been observed across development and aging. Young infants have been shown to be sensitive to the correspondence between the auditory and visual speech (Kuhl & Meltzoff, 1982; Rosenblum Schmuckler , &Johnson , 1997). Nonetheless , several studies reveal that the perceptual judgments of young children show less of a visual influence when compared to adults (Massaro , 1984; Massaro , Thompson , Barron , & Laren , 1986; McGurk & McDonald 1976). Massaro (1984) compared performance of preschool children to college students and found that the major difference between the two groups was the overall
contribution of the visual speech: the adults showed a greater visual influence relative to the children. Even though the preschool children were less influenced by the visible speech , they appeared to integrate the audible and visible speech in the same manner as adults. For both groups , the FLMP gave a significantly better description of performance than a nonintegration model. Given this support for integration in young children , it is valuable to ask whether autistic children also integrate audible
and visible speech in speech perception.
Multimoda Integration in Children with Autism A critical assumption of the FLMP is that perceivers integrate information from the face and the voice in speech perception. It has long been suggested , however , that
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individuals with autism are impaired in both their face processing (Dawson et. aI 2002; Rogers & Pennington , 1991; Wiliams et al. , 2001), and their ability to integrate information across modalities (i. e. Bryson , 1970; de Gelder , Vrooman , & Van der Heide , 1991; Lelord , Laffont , Jusseaume , & Stephant , 1973; Martineau , Garreau Roux , & Lelord , 1987; Waterhouse , Fein , & Modahl , 1996). However , the exact nature of these impairments has not been specified and the evidence is limited. For
example , children with autism tend to avoid the face to face contact with others required by shared attention (Happe , 1996) and , therefore , would naturally have less experience with visual information from the face. It follows that we would expect autistic children to be less influenced by the face in bimodal speech perception but it is possible that they integrate the two sources in the same manner as normallydeveloping children.
It is therefore essential to distinguish between how much information is obtained from a sensory input and how information from multiple inputs is processed. Given the FLMP framework , we make a formal distinction between " information " and information processing. " The sources of information from the auditory and visual channels make contact with the perceiver at the evaluation stage of processing. The reduction in uncertainty affected by each source is defined as information. In the description given by the FLMP , for example , the degrees of support for each alternative from each modality correspond to information. These values represent how informative each source of information is. Information processing, on the other hand refers to how the sources of information are processed. In the FLMP , this processing is described by the evaluation , integration , and decision stages (see Figure 1). Fortunately, there is an ideal experimental paradigm and theoretical analysis that allow us to distinguish information from information processing, and to determine whether integration occurs. The experiment involves the independent manipulation of two sources of information in an expanded factorial design. It allows an assessment of the influence of the many potentially functional cues , and whether or how these cues are combined to achieve speech perception (Massaro , 1998). This systematic variation of the properties of the speech signal and quantitative tests of models of speech perception test how different sources of information are evaluated and how they are actually used.
The goal of the present investigation was to assess speech processing abilities in children with autism. We asked whether any observed differences are the consequence of information or information processing. This distinction allows us to deter-
mine whether any decrement in performance is the result of an impairment in crossmodal integration (information processing) or the inability to discern and utilize the auditory and visual information (information). To address these questions our experimental design was carried out in three stages. We began with an identification test, utilizing an expanded factorial design. Given that the children appeared to integrate crossmodally but were influenced only somewhat by the visual speech , we carried out a training regiment in which the children were trained in speechreading. We then repeated the identification task. We predicted that this training would result in
an increase in the influence of visible speech in the identification experiment , and that their crossmodal integration would not change.
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Method Participants Seven children diagnosed with autism , 1 female , 6 males , ranging in age from 7 to 11 (M= 9. 87; SD=1.6) years were recruited from two different day programs for children with autism in Santa Cruz County. Prior to the start of our investigation , we requested parent permission from all of the children enrolled in the two school programs. Out of 12 children , permissions were given for these 7 children. Six of the children were native speakers of American English; one child was a native speaker Spanish , but spoke English fluently. Four of the children attended a private school and the other three attended a special day program at a local public school in the
Santa Cruz area. All 7 of the participants were familiar with the experimenter (the junior author) prior to our investigation and were unaware of the goals of the study. Six of the seven children were capable of speech. The Appendix gives a detailed description of each child.
Identication in the Expanded Factorial Design
Stimuli All stimuli were presented by our computer- animated talking head , Baldi. Baldi' speech and emotion are generated by a parametrically controlled polygon topology (Massaro , 1998). The advantage of using the talking head derives from its ability to mimic natural speech , by incorporating co articulation and being trained by natural speech measurements (Massaro , 1998; Ouni et al. , 2003). The stimuli were the consonant- vowel
Ibil
(CV) syllables
and
Idil
and the vowel (V) syllable
iii.
The syn-
thetic visible speech was controlled and aligned with the synthetic audible speech (Black & Taylor , for
iii
be noted that
Idil
Ibi/ 385 ms The intensity of the syllables was 64.4 dB-A. It should look very similar in visible speech.
1997). The duration of the test syllables was 472 ms for Idi/.
and 448 ms for and
iii
Figure 2 gives a diagram of the expanded factorial design used in this experi-
ment. The synthetic auditory and visual stimuli were presented unimodally and bimodally in an expanded factorial combination , giving a total of 15 conditions. There were 3 auditory conditions , 3 visual conditions and 3 x 3 or 9 bimodal condi-
tions. Each of the 15 conditions was sampled randomly without replacement in a block of trials. The identification task was presented before and after training in speech reading. In the Pre- training test , there were 2 blocks across 5 days for a total of 10 observations under each of the 15 conditions. In the Post- training test, there were 4 blocks across 5 days for a total of 20 observations under each of the 15 conditions.
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Iii
Visual
Ibil
Idil
None
Ibil
Auditory
Iii
Idil
None FIGURE 2. Expanded factorial design used in the Pre- training and Post- training identification task. The auditory and visual stimuli were /bi/ /iI and Idi/ presented unimodally or bimodally. All stimuli was developed on a 600 MHz Pentium III with 128 MB memory and running a Gforce 256 AGP-V6800 DDR graphics board running Microsoft Windows NT 4 and a Graphic Series view Sonic 20" monitor. The Pre- training task was run on the machine just described , whereas Training and Post- training tasks were run on a Toshiba Satellite 5005- S504 laptop which has a 1 GHz Pentium III with 512 MB memory and Nvidia GeForce2Go graphics running Microsoft Windows 2000 professional. The auditory speech was delivered via Harman/Kardon internal speakers or Plantronics PC Headset model SR1. Each student had the option to respond with either an external mouse (Logitech M- CAA42) or a touch screen (KEYTEC Magic Touch). Each child used the same response method throughout the experiment. All sessions occurred at a computer workstation located in each school during Pre- training. Both Training and Post- training sessions were conducted individually at the stu-
dent's desk.
Procedure The children were tested individually at their school. They were instructed to listen and watch Baldi on the screen , and to identify the consonant of the syllable " that the speaker said" as either B or D. The participants made their responses by clicking
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on a labeled area on the screen directly below the test window. The experiment was
participant driven: the computer waited for the child to make a response before proceeding to the next trial. The investigator sat to the left of the child during the duration of the experiment, redirecting the child' s attention to the task if the child became distracted and to supply uninformative motivational rewards for responses throughout the investigation.
Training in Speechreadng Stimuli (CV) syllables Idi/ , lvii Figure 3 shows a view of Baldi at the onset of the articulation for each
Baldi was also used to generate the consonant- vowel
/zi/
or
Ibil.
of the four syllables.
Procedure Training in speechreading began with a bimodal presentation of each syllable. The intensity of the auditory speech was programmed by a Text-To- Speech (TTS) graphical editor (GUI) for SABLE , which is currently supported via mark up com-
mands. The auditory intensity used during training was based on the student's performance during the previous training session. If the student attained a passing score in a given training session ,
the level of auditory input would be reduced in the next session , whereas the auditory input was increased if the student did not pass. The intensity of the auditory speech was set at one of 9 levels in which the intensity
FIGURE 3. Ilustration of the four syllables speechreading training task
at the onset of articulation in the
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varied between 0 (no auditory information) and 1 (the auditory speech at 64.4 dB- A). Table 1 gives the auditory levels used at each stage of training. The students were instructed to watch Baldi and indicate the syllable that was spoken. A 200 ms beep sounded prior to the presentation of the test stimulus to indi-
cate the start of each trial. Following the test presentation , response buttons appeared in the upper left hand corner of the screen. Responses were made by activating a button labeled B , D , V , or Z presented in a 2 by 2 configuration , using the mouse or touch screen. Placement of the labels was randomized across trials. Immediately fol-
lowing the student's response the buttons were removed and the next trial began. Feedback was given for correct responses in the form of " stickers " and verbal praise given by Baldi.
Before each training session , a test session was presented. Each syllable was presented visually without sound in 3 blocks of trials , generating a total of 12 trials (3 observations for each of the four syllables). Following completion of the 12 test trials an accuracy score was calculated. If the student attained 100% identification accuracy during the assessment, the student was congratulated and the program automatically exited. If the student did not reach this criterion of 100% , then the program progressed to training (see Figure 4). The criterion level during training was 80% , which
had to be met for the child to advance to the reduced level of auditory input. Students were given the option to select the color of Baldi after every 3 blocks (12
training trials). The students completed 3 sessions per week , which lasted approximately 30 minutes each. The students were given a 3- minute break between training sessions. A " choice board" would appear on the screen and the student selected from a variety activities and/or food items. Upon completion of the break , the experimenter would resume the training session. Training occurred for approximately weeks or until the student was able to identify all stimuli with 100% accuracy on the assessment test (without sound) for 2 consecutive sessions.
Table 1. The auditory traiing levels across the 9 stages of traiing. Training stage
Auditory level
10%
20% 30% 40% 50% 100%
dB-
39. 41.9 42. 48. 50. 52. 54.4 64.4
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FIGURE 4. Ilustration of the procedure used in the training of speechreading.
Results and Discussion
Expanded Factorial Design: Pre- training
Test
An identification judgment for each stimulus was recorded. The mean observed proportion of identifications was computed for each participant for the unimodal and bimodal conditions by pooling across all 10 replications of each condition. The proportion of /di/ responses for each of the trial types was computed for each participant. The top panel of Figure 5 gives the observed (points) proportion of /di/ judgments as a function of the auditory and visual stimuli in the unimodal and bimodal conditions. The children were clearly influenced by both the auditory and
visual speech in both the unimodal and bimodal conditions. Six of the points are circled in the top panel of Figure 5. The top three points correspond to the conditions
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FIGURE
121
5. Predicted (lines) and observed (points) proportion of /di/ judgments as
a function of the auditory and visual stimuli in the unimodal and bimodal conditions.
The Pre- training and Post- training identification conditions are given in the top and bottom panels , respectively. auditory /di/ , visual /di/ , and bimodal /di/. The outcome that the proportion of /di/ responses was higher in the consistent bimodal condition than in the two corresponding unimodal conditions is strong evidence that the children were integrating the auditory and visual speech (see Massaro , 1998). If only a single source of information
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were being used on bimodal trials , the proportion of judgments could not be more
extreme than either of the unimodal proportions. The more extreme judgments could only result from some combination (integration) of the two modalities. The Ibil
same interpretation can be given for the bottom three points for the syllable Idil
proportion of /bil judgments is simply one minus the proportion of
(the
judgments
in this two alternative task). These conclusions are supported by separate analyses of variance carried out on the visual , auditory, and bimodal conditions. Under the unimodal conditions , there was a significant effect for the auditory factor F(2 , 12 ) = 12. 277 , P ~ 0. 01 and the visual factor F(2 , 12) = 33. 879 , P ~ . 01 for the auditory and visual conditions , respectively. In the bimodal condition , there were significant main effects for both the auditory factor , F(2 , 12) = 14. , P ~ . , and the visual factor , F(2 , 12) = 6. , P ~ . 01. However , the interaction between the two variables in the auditory- visual condition did not reach statistical significance , F(4 , 24) = 0. 941 , P = 0. 54.
Training in Speechreading One possible explanation for the small visual effect is a difficulty in speechreading. This hypothesis coincides with previous findings that for children in general , the auditory input provides more information than the visual input (see Massaro , 1984; Massaro et al. , 1986). Recall that Massaro (1984) found that children were not as proficient as adults in their abilities to accurately identify the visual information under the unimodal visual conditions and the children were also less influenced by the visual information in the bimodal conditions. Thus , the ability to process visible speech (and auditory speech) must be accounted for in order to address the question of whether individuals with autism integrate information from these two modalities. Previous findings show an improvement in speechreading through training. Our
question was whether children with autism could be trained to speechread more accurately. We developed and implemented a computer-based speech reading lesson focused on the visible aspects of speech using the consonant-vowel syllables /bi/ Idi/ , lvii and /zi/. These CV syllables were selected because they are reasonably distinctive from one another and because /bil and
Idil
corresponded to the syllables
used in our experiment addressing the integration question. Assessment data were captured daily for each student and continued until the student was able to maintain 100% identification accuracy across 2 consecutive days of assessments or 15 weeks of training. Other differences in the number of training sessions across students are the result of absences and availability. Given these differences in the number of training sessions across students , we pooled the data across sessions to give an equal number of training blocks across the 7 children. Student 6 reached the passing criterion (100% identification accuracy on the assessment for two consecutive sessions) in 7 training sessions , and data for the remainder of the students was pooled into 7 blocks.
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Figure 6 shows the average identification accuracy across the 7 blocks of trials. As can be seen in the figure , identification accuracy improved systematically across
blocks. An analysis of variance with the proportion of correct identification as the dependent variable and the block as the independent variable revealed that this increase was significant , F(6 , 36) = 17.079 , P ~ . 01. Overall the students made substantial gains from block 1 (M = . 37. , SD = . 09) to block 7 (M = . , SD = .14), F(l , 6)= 30. 624 , P ~ . 01. A second AN OVA , comparing the proportion of correct identifications in block 1 (M = . 37) to block 2 , revealed an 18% increase in accuracy and that this increase was significant, F (1 , 6) = 12. 862 , P ~ 0. 01. This result indicates that the children made substantial gains in speech reading performance after just one block of training. assess gains after the initial block of training, we conducted an additional AN OVA in which block 1 was eliminated from the analysis , revealing that the improvement across blocks remained significant, F (5 , 30) = 13. 214 , P ~ 0. 01. These results indicate that accuracy continued to increase as a function of training. Table 2 gives the individual performance for each student. As can be seen in the table , each student showed a substantial improvement in speechreading across the training sessions. We then assessed accuracy for each syllable and its change as a function of training. As shown in Table 3 , accuracy increased for all syllables and the identification of /bi/ and /vi/ was almost perfect by the end of training. The syllables /di/ and hi/ showed less improvement. These differences are reasonable because the syllable /bi/
Traing Identifcation Accuracy
0.5
0.4
-- 4 syllbles
3 syllbles
Block
FIGURE 6. Accuracy of identification in the training experiment across blocks. The two curves correspond to accuracy computed for 3 and 4 alternatives , respectively.
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Table 2. Average proporton correct across the syllables Izil
/hi/, ldi/, lvii,
and
for each of the seven blocks of training. Student
Block
0.42
0.17
0.44 0.42
0.43 0.48
0.42 1.00 1.00
Table 3. Average proporton correct for each of the syllables across the seven blocks of training. Syllable Block
/bi/
/di/
0.49
0.14
/vi/
/zi/ 0.42
0.41
0.40 0.49
Ivil by the bottom lip tuck whereas are very similar in visible speech except for duration (see Figure 3). Given the similarity between Idil and /zi/ we also scored accuracy when Idil and /zil were treated as one category. As shown in Figure 6 , this pooling increased the overall level of performance , F(l , 6) = 37.890 , P ~ 0. , producing almost perfect performance by Block can be distinguished by the closing of the lips and
the syllables
Idil
and
/zil
Expanded Factorial Design: Post- training As in the Pre- training task , recorded and the mean observed proportion of
Test
an identification judgment for each Idil
stimulus was
identifications was computed for
each participant for the unimodal and bimodal conditions by pooling across all 20 replications of each condition. The bottom panel of Figure (points) proportion of
Idil
5 gives the observed
judgments as a function of the auditory and visual stimuli
in the unimodal and bimodal conditions. As in the Pre- training task , the children were influenced by both the auditory and visual speech in both the unimodal and bimodal conditions. One can also observe that the visual influence was much larger
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training. The six points circled in the bottom panel of Figure 5 ilustrate integration of the auditory and visual speech , following the same logic we gave for the Pre- training task. As in the Pre- training task , separate analyses of variance were carried out on the auditory, visual , and bimodal conditions. Under the unimodal conditions , our results revealed a significant effect for the auditory factor (2 , 12) = 19.410 , P ~ 0. 01 and the in the Post- training than in the Pre-
visual factor F (2 , 12) = 188. 647 , P ~ 0. 01 for the auditory and visual conditions
respectively. Auditory-visual performance reveled significant main effects for both the auditory factor and the visual factor , F(2 , 12) = 20. , P ~ . 001 , F(2 , 12) = 20. P ~ . , respectively. However , the interaction between the two variables in the bimodal condition did not reach statistical significance , F(4 , 24) = 1.091 , P = 0. 38.
Pre- training versus Factorial Design
Post- training
Performance in the Expanded
A combined analysis across the Pre- training
and Post- training
conditions was car-
ried out to determine if there were any differences attributable to training. For the unimodal auditory condition , there was a main effect for the auditory factor , F(2 , 12) = 36. 690 , P ~ 0. , but this did not interact with training, F (2 , 12) = 0.165 , P = 0. 84. For the unimodal visual condition , there was a main effect for the visual factor , F (2 12) = 324. 277 , P ~ 0. , and a significant interaction with training, F (2 12) = 17.678 P ~ 0. 01. As can be seen in Figure 5 , the proportion of correct visual identifications for the syllable /bi/ and / di/ increased respectively from . 66 and. 70 in Pre- training to . 90 and . 82 in Post-Training. For the bimodal trials , both the auditory and visual information had significant effects on performance , F (2 , 12) = 29.415 , P ~ 0. , for the auditory and , F (2 , 12) = 98. 229 , P ~ 0. , for the visual. There was an interaction between experiment and the visual factor , F (2 , 12) = 6. 280 , P ~ 0. , but not for the auditory factor , F (2 , 12) P = 0. 34. The analysis also revealed that there was no interaction between the auditory and visual factors , F(4 , 24) = 1.05 , P = 0. 377 , or for the three- way interaction of auditory factor , visual factor , and experiment, F (4 , 24) = 0. 843 , P = 0. 513.
= 1.505 ,
Model Tests of Integration: The FLMP We now derive the predictions of integration and nonintegration models in order
to test whether the autistic children integrated the auditory and visual
speech.
Consider a simplified situation in which perceivers are given either or both auditory
and visual speech information , and asked to decide whether the speaker said /bi/ or situation , information from each modality is assumed provide independent and continuous support for these two response alternatives. It is assumed that the perceivers have prototypes corresponding to /bi/ and /di/ , and evaluate the incoming signals in terms of these prototypes. For simplicity,
/di/. Applying the FLMP to this
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dil in terms of
we specify the prototypical features representing auditory /bil and
), whereas the prototypical features are given in terms of the amount of lip closure at
the onset of the second and third formants (F, representing visual /bil and
Idil
the onset of the syllable. Following this description ,
/bil and
Idil
are represented in
memory as Idi/:
falling F,
/bi/: rising F,
F" and lips apart F" and lips closed
At the evaluation stage of processing, the input from each modality is evaluated independently to determine to what extent it matches the prototype descriptions. Independence means that the value assigned to one modality is independent of the value assigned to the other. The degree of match is represented in terms of truth values in fuzzy logic , which can vary continuously between 0 (false) and 1 (true). For example , an apple , a date , and an olive would be good , ambiguous , and relatively poor members of the category fruit. To ilustrate the predictions with just two response alternatives , rising F, F, can be represented as (I- falling F, ) and lips closed as (I- lips apart). Assume that the audi-
tory input matches falling F, F, to degree . 8 and the visual input matches lips apart to degree .4. Given just the auditory input, only the degree of match to the auditory feature would be relevant. Idi/: falling F, F, = .
/bi/: (I- slightly
falling F, - F,
Given the relative goodness for response ,
the probability of a
Idil
response would be
81(. 8+. 2) the probability of a dil response would be .4. Given both of these auditory and visual inputs , then we have Idi/: falling F, F, and lips apart = . 8 and .4 /bi/: (I- slightly falling F, ) + lips closed = . 2 and . The integration stage of processing involves multiplying the truth values determined at the evaluation stage for each prototype. In this example , the total support for the two alternatives would be Idi/: 8 * .4 = .
Analogously, given just the visual input,
/bi/: . 2 * . 6
= .12
The decision stage , leading to perceptual identification and interpretation , is based on the relative degree of support between these two alternatives. In this case , P(!di/) is equal to the support for Idil divided by the sum of the support for Idil and Ibil. Thus , the probability of a Idil response , P(!di/) is equal to P(!di/) =
321(. 32
+ .12) =
32/.44
As can be seen in our example , both sources contribute to perceptual identification , but the degree of influence depends on the relative degree of ambiguity of each source. The auditory support for Idil is less ambiguous than the visual support for /bil and , therefore , the auditory source has a larger influence. Consider another example in which the two sources of information are relatively dil to degree. 7 , while the consistent: assume that the visual source now supports auditory support remains at .
+.
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8 * .7 = .
Idi/:
/bi/: . 2 * . 3 = . Using the relative goodness rule , the predicted P(!di/) = 561(. 56 06) = . 56/.62 = . We see that the predicted probability of a
Idil
probability of a
Idil
response is
response is larger in the bimodal con-
dition than in either unimodal condition. More generally, the FLMP is formalized in terms of the following equations. In task with /bil and dil alternatives , the degree of auditory support can be represented by a. and the support for /bil by (1 - a.). Similarly, the degree of visual support for dil can be represented by Vj' and the support for Ibil
a two- alternative for
Idil
by (1 - vJ The probability of a response to the unimodal stimulus is simply equal to the feature value. For unimodal auditory trials , the predicted probability of a response , P(! di/) is equal to (1)
P(!dil)
a,)
+(l
For unimodal visual trials , the predicted probability of a response , P(!di/) is equal to (2)
P(!dil) +(l
For bimodal trials , the predicted probability of a response , P(!di/) is equal to (3)
P(!dil) +(l
a,)
(1 -
These equations wil be implemented in the test of the FLMP against the current results.
Single Channel Model (SCM) Given that previous research has been interpreted in terms of the lack of integration in children with autism (see Discussion Section , Previous Research), it is worthwhile to consider how this lack of integration would play out in bimodal speech perception. According to non- integration models , the categorization of a speech event is the result of a single influence (Massaro , 1998). Given a perceptual event in
which multiple sources of information are available , pattern recognition is determined by only one of these sources. If, indeed , children with autism do not integrate auditory and visual speech , then a non- integration model should give a better description of their performance. We formalize a nonintegration model that provides
a fair contrast with the FLMP in terms of their a priori ability to adequately predict results from this type of experiment (see Massaro et al. , 2001). The Single Channel Model (SCM) assumes that only one source of information received from the two modalities is used on any trial. This model predicts that given
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a bimodal auditory- visual speech event , the participant wil use the auditory information with the probability p and the visual information with the probability (1 - p).
Given our earlier example with auditory and visual input and /bi/ and /di/ alternatives , we can derive the probability of identification under the different conditions. In the application of the SCM , it is assumed that the perceiver always uses the appro-
priate modality when only a single modality is presented. Assume that the probability of a /di/ identification , P(!di/), given a specific auditory event is used is . 8. The predicted P(!di/) is also . 8 on unimodal auditory trials because it is assumed that the perceiver always uses the appropriate modality when only a single modality is presented. Similarly, assume that that P(!di/), given a specific visual event is used is .4. The predicted P(!di/) is also .4 on unimodal visual trials because it is assumed that the perceiver always uses the appropriate modality when only a single modality presented. On bimodal trials , the response is determined by the probability of using one modality rather than the other. The value of p varies between 0 and 1 and cor-
responds to the probability of using the auditory modality. The probability of using the visual modality is simply 1 - p. If we assume p = . 7 in our example , the predicted P(!di/) would be equal to the probability of using the auditory modality times the probability of a /di/ identification of the auditory modality plus the probability of using the visual modality times the probability of a /di/ identification of the visual
modality.
P(!di/) = . 7 * . 8 + . 3 * .4 = . More generally, P(!di/) = pa + (1 - p)V (4) where p is the probability of using the auditory modality, a is the probability of a / di/ identification of the auditory modality, (1 - p) is the probability of using the visual modality, and Vj is the probability of a /di/ identification of the visual modality. On any trial , pattern recognition of a multimodal event is a consequence of only one of the modalities (Massaro , 1987 , 1998).
Model Tests To test auditory visual integration in speech perception , we tested the FLMP and the SCM against each of the individual participant's results. As described in Massaro (1998 , Chapter 2), the FLMP requires 6 free parameters: three parameters for each auditory and visual stimulus to fit the 15 data points of the 3 x 3 expanded factorial design. These parameters symbolize of the degree to which these modalities match a
prototypical /di/. The SCM requires 6 analogous parameters and a seventh corresponding to the probability of using the auditory modality. The two models were fit results and to the mean results across the seven participants.
to the individual
Separate fits were carried out for the Pre- training and Post- training tasks. The program STEPIT (Chandler , 1962) determined the quantitative predictions of the models. Each model is represented as a set of unknown parameters and prediction equations. STEPIT adjusts the parameter values of the model iteratively, min-
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imizing the root mean squared deviation (RMSD) between the predicted and observed points. The RMSD provides an index of each model's goodness- of- fit (Massaro , 1998). In the Pre- training task , the RMSDs of the FLMP ranged from . 07 to .12 , with an average RMSD of . 09. The fit of the mean participant gave an RSMD of . 03. The RSMD of the SCM ranged from . 08 to .16 , an average of . , and the mean participant RMSD of . 05. In the Post- training fit , the RMSD of the FLMP ranged from . 04 to . , with an average of . 06. The fit of the mean participant gave an RMSD of . 04. The RMSD of the SCM ranged from . 04 to .1 , gave an average of . , and the mean participant RMSD of . 04. The lines in Figure 5 give the average predictions of the FLMP. As can be seen in the figure , the integration model is able to describe the results fairly accurately. The three circled points in each of the panels show that the results and the model's predictions both show a benefit of having consistent auditory and visual speech relative to either source presented alone. Figure 7 gives the individual RMSDs for the FLMP plotted as a function of the individual RMSDs for the SCM for both the Pre- training and Post- training tasks. The points that fall below the diagonal line show a better fit of the FLMP over the SCM. An analysis of variance was carried out on these RMSD values , with Pre- training and Post- training and Model as independent variables. The FLMP gave a significantly better fit of individual performance than did the SCM , F( 1 , 6) = 7.368 , P ~ . 05. Given that the FLMP and SCM represent integration and nonintegration models , respectively, we can tentatively conclude that the children were integrating auditory and visual speech. The RMSDs were significantly smaller in the Post- training than in the Pre- training task , F(1 6) = 8.135 , P ~ . 05. The reason for this difference is primarily due to having twice than number of observations in Post- training than in Pre- training (Massaro 1998 , Chapter 10). Sampling variability decreases with increases in the number observations. Although the fit of the models were better for Post- training than Pretraining, the advantage of the FLMP did not interact with training, F(1 6) = 0. 362
P = . 57.
General Discussion
Our experiments provide some evidence that children with autism are influenced to some extent by speech information in the face , can be taught to improve their sensitivity to visible speech , and do integrate cross- modally in speech perception. We tested an integration model (the FLMP) against a non- integration model (the SCM) against the identification results from an expanded- factorial design in which the auditory and visual speech were presented alone or together. Although the influence of visible speech was relatively small in the first Pre- training test , we succeeded in training the children to speechread to allow a stronger test of integration when there was
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FIGURE 7. RMSD values for the fit of the FLMP as a function of the RMSD values for the SCM for each of the seven children in the Pre- training (Experiment and Post- training (Experiment 2) tasks. The diagonal line gives equivalent RMSD values for the two models. a larger influence of visible speech. The FLMP gave a significantly better fit than the SCM across these two replications of the expanded- factorial design. A possible limitation of our investigation is the absence of a control group. Even though we did not test normally- developing children in the current study, however there is an existing literature that makes such comparisons possible. Our question in the present study was whether children with autism integrate auditory and visual information in a speech perception task. Having now answered this question in the affirmative , we can ask how this outcome compares with that of normally- developing children. Our previous research (Massaro , 1987 , Chapter 8) found that the FLMP gave a significantly better description of performance than the SCM across a wide range of development (3. 5 to 9. 5 years). Thus , the current results taken in conjunc-
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tion with previous research indicate that both autistic children and normally- developing children integrate auditory and visual speech as described by the FLMP. Thus , we believe that we were able to address the integration question without a control group. Our tests of the FLMP and SCM allowed us to determine whether children with autism do integrate. The outcome of the model tests showed that the FLMP better described the results than the SCM , a non- integration model. Given this outcome , a working hypothesis is that children with autism do integrate the auditory and visual speech in the bimodal condition. Future work should increase the family of models that are tested , and to employ other measures of goodness- of- fit (Massaro et al. 2001). Other non- integration models , such as an Auditory Dominance Model (ADM), might adequately describe the results. We did not test the ADM in the present study because it would have required almost as many free parameters (13) as independent data points (15), making its test essentially invalid (Massaro , 1998). In addition , RMSD is a relative measure of goodness- of- fit of a model , and it can be
supplemented with an absolute benchmark measure (Massaro , 1998). The benchmark measure provides a goodness of fit measure that should be expected if indeed the model is correct. Other more complex techniques of model selection are being developed and used (Myung & Pitt, 2003). Future work should employ these more
sophisticated techniques as much as possible to refine tests of the integration question. We appreciate the fact that the results to date are stil not definitive. Given the difficulty of testing children with autism in a task with many trials , the data are stil somewhat limited. Also , the large spectrum of behaviors across the diagnosis of autism makes it somewhat difficult to generalize across this population. With respect to speechreading skil , we know that the overall performance accuracy would be lower for our children than for normally- developing age- matched controls. We observed a fairly small influence of visible speech in the Pre- training identification task. We know from our previous research that age- matched controls would be more accurate in speechreading than were our children. Our children whose average age was 9 years 8 months identified a visual /bil and
Idil
correctly
66% and 70% in the Pre- training task. In previous work, we found that normallydeveloping fourth- grade children at the same age identified visual /bal and Idal 99% and 97% of the time , respectively (Massaro , 1987 , Chapter 8). Thus we see that our children began the study as much poorer speechreaders than their age- matched controls. Consistent with previous training studies (Massaro , Cohen and Gesi , 1993; Walden , Prosek , Montgomery, Scherr , &Jones , 1977), our autistic children became better speechreaders with training. After training, the accuracy of identifying visible speech of our 7 students improved significantly (90% and 82%) in the Post- training task. This improvement stil fell a little short of that previously found for normallydeveloping children at this age level (Massaro , 1987 , Chapter 8). We also found in previous work that pre- schoolers , with an average age of 3. years correctly identified visual /bal and
Idal
at rates of 81
% and 57%. Experienced
pre- schoolers , having had practiced identifying visible speech without feedback and with an average age of 4. 75 years , correctly identified visual /bal and Ida! at rates of 90% and 82% (Massaro , 1987 , Chapter 8). Therefore , our children appear to be in
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the range of competent preschoolers in their ability to speechread. Ideally, if multimodal integration in autistic children is compared to normally- developing controls then they should be matched at about the same level of speechreading ability.
Previous Literature
One of our conclusions is that children with autism , although somewhat limited in their ability to use information from the face , integrate facial and vocal information in speech perception. This conclusion appears to contrast with the previous literature. We review this literature and describe how the previous results either do not
address the issue of integration or can be more appropriately interpreted as a deficit in processing facial information rather than a lack of integration.
Crossmodal influences have been studied using auditory evoked responses (AERs) in a cross- modal association paradigm in which a sound is paired with a strong visual stimulus , such as a flash of light (Martineau , Roux , Adrien , Garreau Barthelemy, & Lelord , 1992). For instance , LeLord and colleagues (1973) discovered that the occipital region of normal children showed an increase in amplitude of the AER when a sound was preceded by a flash of light , whereas children with autism showed no such increase. However , the differences that were observed might simply be due to differences in AERs without visual information rather than how the two modalities interact. Martineau and colleagues (1987) found that the AERs for children with autism were consistently smaller than children with normal intelligence but larger than children with mental retardation. Martineau et al. (1992) found that children with autism showed a great deal of variability in the AER and classified the performance into three groups: below normal activation , activation comparable to controls , and above normal activation. Moreover , the magnitude of the AER was positively correlated with level of functioning. Although measurements of AER might eventually prove informative , the research to date does not provide evidence for non- integration across modalities.
Research supporting the hypothesis that the perceptual deficit results from inte-
gration difficulties is ostensibly supported in studies designed to measure associations between auditory and visual information. Bryson (1970) found that the performance of children with autism was lower when required to match auditory- to-visual and visual- to-vocal events compared to auditory- to-vocal and visual- to- visual events. Autistic children might perform poorer in this task simply because they have less information about the visual and/or auditory events. More importantly, comparing events across two modalities does not require an integration process. It simply
requires the perceiver to evaluate the relationship between the events from the two modalities. Evidence suggesting that children with autism are able to match infor-
mation cross- modally (Boucher , Lewis , & Collis , 1998 , 2000; Walker- Andrews Haviland , Huffman , & Toci , 1994) does not address the issue of integration. In the
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framework of the FLMP , the integration process is not necessary to perform the matching task successfully.
De Gelder et al. (1996) compared bimodal speech perception of children with autism to normal developing children matched for mental age. The investigators used an expanded factorial design in which the children were presented with bimodal , auditory- only, and visual- only speech segments. The children were presented with vowel- consonant- vowel
Id/ , Im/
speech segments: the consonants
Ip/ , /b/ , It/
The children were instructed to watch and listen to the speaker and identify the segments by repeating back what they thought the speaker said. The influence of the visual speech on bimodal trials was measured according to the proportion of " fused" or " combination " responses. Fused responses were defined as those in which the place of articulation (visual speech) and the auditory speech resulted in a single " fused" percept, such as identifying the combination Inl as Im/. of a visual /bl and auditory Combination responses were defined as those producing a combination of the syllables , such as identifying a visual /bl and auditory Idl as /bdl. It appeared that the children with autism showed less influence of the visual speech than the controls: the proportions of fused and blended responses were .19 and . 51 for the children with and without autism , respectively. The authors attributed this smaller visual influence on autistic children as an inability to integrate the auditory and visual information. However , a smaller visual effect found in the bimodal condition does not necessarily establish a lack of integration. Given the FLMP framework , we are able to make a distinction between information " and " information processing. " The sources of information from the auditory and visual channels make contact with the perceiver at the evaluation stage of processing. The reduction in uncertainty produced by each source is defined as information. In the fit of the FLMP , for example , the parameter values indicating the degree of support for each alternative from each modality correspond to information. These parameter values represent how informative each source of information is. Information processing, on the other hand , refers to how the sources of information are processed. In the FLMP, this processing is described by the evaluation , integration , and decision stages. or
Inl
paired with the vowel
Ia!.
Given this framework , we are able to analyze the information and information-
processing differences between the two groups in the De Gelder et al. (1996) study. Perceivers with hearing loss obviously have less auditory information , for example but we can also ask whether they differ in terms of information processing. Similarly, we can ask whether the integration process works the same way for children with autism as for matched controls. According to the FLMP , the degree of influence is a direct function of the information in the auditory and visual modalities. The proportions of correct responses in the unimodal conditions for the children with autism were . 97 and. 74 for the auditory and visual sources , respectively. We see that these children were very good at identifying the auditory segments , but not so good at identifying the visual segments. Thus , the FLMP would predict the contribution of the auditory source of information would exert a greater influence than the visual source in the autistic children s perceptual judgments of bimodal speech. The pro-
, "
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portions of correct identifications for the control group were . 90 and . , respectively for the unimodal auditory and visual conditions. These children were roughly equally adept at identifying both the auditory and visual information. Thus , the FLMP would predict that the two sources of information would influence performance in the bimodal condition roughly to the same degree. This analysis shows that the FLMP can explain how observable behavior can differ without necessitating a
difference in the underlying information processing on bimodal trials. The FLMP can predict that the children with autism were less influenced by the visible speech than the matched controls , even though both groups of children integrated the two
sources of information in a similar fashion. When the results of de Gelder et al. (1996) are analyzed in the framework of the FLMP , the outcomes for both the autistic children and the control children are consistent with a process of integration of the auditory and visible speech.
As pointed out by a reader of this article a potentially more parsimonious account would say that autistic children are insensitive to emotions , social cues , and face movements in part because they can t integrate them as well as normally developing children. " Lack of integration , however , should not necessarily lead to an insensitivity of the cues within a given modality. Some individuals are required to function unimodally (e. , the nonsighted in the perception of speech) and all of us have unimodal inputs at least some of the time (e. , talking on the telephone). What the results of the expanded factorial design make clear that small influence of visible
speech in the bimodal condition is a direct consequence of its small influence in the unimodal condition. We carried out training in speechreading to enhance the impact of the visual information and were successful in improving the children s speechreading, which resulted in a larger impact of visible speech in bimodal speech perception. Visual information from the face in speech perception is only one example of many in which face perception plays an important role. Although the FLMP describes speech perception , person identity and emotion may be processed analoinformation necgously (Schwarzer , & Massaro , 2001). While it is understood that the essary for person identification and emotion differ from that for speech perception recent research suggests that the information processes involved are identical (e. , & Massaro , 2001; Massaro , 1998 Campbell , Schwarzer , Chapters 7 & 8). Thus , it would be interesting to repeat the expanded- factorial design in tasks that manipulate auditory and visual cues to these distinctions. These experiments would address the question of integration abilities of autistic children in other domains that have also been viewed as difficult for children with autism (Happe , 1996).
Applying the Curent Findings in Treatment Given that there is reasonable evidence that children with autism do evaluate and integrate information from multiple modalities , we advocate multimedia learning
environments for them. One instantiation
of this approach is a Language
Wizard/Player that we have been using to teach vocabulary and grammar to children
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FIGURE 8. A prototypical computer screen from the Language Wizard/Player ilustrating the format of the tutors. Each application contains Baldi , the vocabulary items and written text and captioning (optional), and " stickers . In this application the students learn to identify shapes. For example , Baldi says " Click on the rectangle . The student clicks on the appropriate region and visual feedback in the form of stickers (the happy and sad faces) are given for each response. The outlined region indicates the student's selection.
(Bosseler & Massaro , in press). Our Language Wizard and Player (described in Bosseler & Massaro , in press) encompass and implement developments
with autism
in the pedagogy of how language is learned , remembered ,
and used. Education
research has shown that children can be taught new word meanings by using dril and practice methods. It has also been convincingly demonstrated that direct teaching of vocabulary by computer software is possible and that an interactive multimedia environment is ideally suited for this learning (Berninger & Richards , 2002; Wood , 2001). Following this logic , many aspects of our lessons enhance and reinforce learning. For example , the existing program makes it possible for the students to Observe the words being spoken by a realistic talking interlocutor (Baldi), 2) See the word as spoken as well as written , 3) See visual images of referents of the words , 4) Click on or point to the referent or its spelling, 5) Hear themselves say the word , fol-
lowed by a correct pronunciation , and 6) Spell the word by typing, and 7) Observe and respond to the word used in context (see Figure 8). Other benefits of our program include the ability to seamlessly meld spoken and written language , provide a semblance of a game- playing experience while actually learning, and to lead the child along a growth path that always bridges his or her cur-
rent " zone of proximal development." The Wizard allows the coach to exploit this zone with individualized lessons , and with lessons that can bypass repetitive training when student responses indicate that material is mastered.
The Bosseler and Massaro (in press) study consisted of two phases. Phase measured vocabulary acquisition and retention. Phase 2 tested whether vocabulary
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acquisition was due to the Language Player or outside sources and whether the acquired words could be generalized to new images. Vocabulary lessons were constructed , consisting of vocabulary items selected from the curriculum of two schools (Bosseler & Massaro , in press). The participants were eight children diagnosed with autism , ranging in age from 7- 11 years- the same 7 children from the current study and an eighth child. As noted earlier , all of the students exhibit delays in all areas of academics , particularly in the areas of language and adaptive functioning, and seven of the children were capable of speech. The average results indicated that the children learned many new words , grammatical constructions and concepts , proving that the Language Player provided a valuable learning environment for these children. In addition , a delayed test given more than 30 days after the learning sessions took place showed that the children retained many of the words they learned. This learning and retention of new vocabu-
lary, grammar , and language use is a significant accomplishment for autistic children.
Although all of the children demonstrated learning from initial assessment to final reassessment , it is possible that the children were learning the words outside of
our learning program (for example , from speech therapists or in their school curriculum). Furthermore , it is important to know whether the vocabulary knowledge would generalize to new pictorial instances of the words , and outside of the learning environment. To address these questions , a second investigation used the single subject multiple baseline design (Anderson & Kim , 2003). Once a student achieved 100% correct , generalization tests and training were carried out with novel images. The placement of the images relative to one another was also random in each lesson. Assessment and training continued until the student was able to accurately identify at least 5 out of 6 vocabulary items across four unique sets of images. The students identified significantly more words following implementation of training compared to pre- training performance , showing that the program was responsible for learning. Accuracy averaged about . , indicating that the learning extended to new images in random locations. Most importantly, the children used this vocabulary knowledge when tested outside of the Language Player environment by another teacher. These results show that our learning program is effective for children with autism , as it is for children with a hearing loss (Massaro & Light , in press). In summary, although autistic children tend to be less influenced by the face , they appear to integrate vocal and facial information in speech perception. These findings in conjunction with previous evidence for integration in normally developing children and adults , support a universal principle in which individuals optimally use multiple sources of information in pattern recognition.
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Appendi Diagnostic information for the eight children. The primary diagnosis for all of the children is autism. The chart contains additional diagnoses , chronological age (C.A.), non- verbal I.Q or measure of cognitive functioning (C. F.), level of adaptive functioning, educational program, and reading level for each student. Student
Additional Diagnoses
C.A
Mentally Retarded
10: 6
ing level
11: 1
9:11
N.A rade
Mentally
11: 1
94**
38***
Beginning First grade
9:4
38****
57***
Beginning Kindergarten
retarded *
12:5
ten
*Information provided in next section **Wechsler Intelligence Scale for Children-Third
Edition (Wechsler , 1989).
***Vineland Adaptive Behavior Scales (Sparrow ,
Balla , & Cicchetti , 1984).
****Psychoeducational Profile Revised (PEP- R)
Schopler , Reichler , Bashford , Lansing, &
Marcus (1990). This score represents the developmental age equivalent (in months).
g. " 111- 144
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Student 1 Standardized Assessments:
determined at last testing. Clinician determined that he fell within the range of mental retardation. His expressive language was so low that all other scores were altered.
Both verbal and non- verbal I.Q: could not be conclusively
Social interactions and Language Use: Tends to avoid social interactions. He wil occasionally request attention while watching a video or while playing (e. look at that" ). Language use is rare and centers around his immediate needs and desires. He has very little spontaneous speech. Does not engage in reciprocal conversation with peers.
Non- adaptive/Non- functional behavior: Unintelligible non- functional vocalizations and occasional hand flapping. This child engages in repetitive activities. Throwing hands up over head and yelling " or " Oh no " and looking at desired objects with only one eye open , peripheral gazing, and finger picking (until bleeding).
Aggression: Does not exhibit any observed aggressive behaviors toward others.
Student 2 Standardized Assessments:
See chart above
Social Interactions and Language Use: This child is aware of others , often seeking attention and praise of adults. He does not use speech spontaneously, initiating conversation only if prompted or in limited , scripted situations. He can construct sentences up to 7 words.
Non adaptive/non functional behavior Rocking, non- functional vocalizations (repetitive sounds , for example , ba, ba, ba but , but , but, or laughing), inappropriate touching, repetitive touching (finger to mouth to " wipe away " something that is not there , rubbing arm or fingers , etc.
Aggression: This child wil aggress towards self and others: pinching, hitting, screaming,
pulling hair , and scratching. Aggression is frequent (0- 5 ally occurs to escape a difficult or undesired task.
times a day) and gener-
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Student 3 Standardized Assessments:
Unable to obtain standard scores on either verbal or nonverbal standardized tests due to non- compliance and disruptive behaviors.
Social Interactions and Language Use: This child has very little spontaneous
speech
interacting with others when
requesting or seeking a desired object or activity.
Non adaptive/non functional behavior Non- functional vocalizations (including vocalizations that are not true words and
words repeated from a book , video , or song), frequent crying, whining, whimpering and screaming, frequent hand flapping, rocking, tensing body and hands responding in an inappropriate speaking voice ,
and " running off" suddenly.
Aggression: Aggressive behaviors/tantrums are observed 0- 5 times a day, including kicking, hitting, and head butting. These behaviors are typically observed when he is required to complete an undesired task , unable to engage in desired activity, or
when leaving reinforcing items/activities.
Student 4 Standardized Assessments:
See chart above
Social Interactions and Language Use: This child has very little spontaneous speech , interacting with others only when requesting or seeking a desired object or activity.
Social Interactions and Language Use: vocalizations , non- compliance , crying, non- functional hand movements and throwing self on the floor. Frequently seeks negative attention from adults , for example , making intentional errors and prompt the adult to say, Don t click on the wrong thing, you need to click on the right thing.
Non- functional
Aggression: Does not aggress toward others.
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Student 5 Standardized assessments:
See chart above There is a large discrepancy in his I.Q; non- verbal I.Q is average (94), while his verbal I.Q is 48 , placing him in the range of mentally retarded.
Social interactions and Language use: He wil typically interact with others. He uses speech spontaneously to direct another s attention to an object or activity. He is very competitive in all areas of academics , games , and sports. If he is unable to be first in line or is unable to
answer a question of any sort he wil tantrum. According to his instructor , he is reluctant to attempt to learn new subject matter. He frequently tantrums when beginning a new task not yet understood or mastered. Fear of failure results in emotional outbursts. He can construct simple sentences containing up to 4 words.
Non adaptive/non functional behaviors: Repetitive non- functional vocalizations , pacing a room , hitting self on the head with fists , and hitting/pushing others in the room. Aggressive Behavior:
Hitting, punching, screaming,
scratching, and kicking. Aggression generally
occurs to escape a difficult or undesired task and occurs frequently (more than 5 aggressive episodes per day).
Student 6 Standardized Assessments:
See chart above
Social interactions and Language Use: He is limited in his attempts to interact with peers and adults. Social play level
at parallel developmental stage in school environment , although he becomes highly frustrated in peer interactions and has difficulty cooperating in group situations (tries inappropriately to control group activities). Language use is limited in social interactions/activities , typically directed towards own needs and desires. He is beginning to share his own experiences with others by directing adult's attention toward his focus of attention (i. e. " look" ). He does not follow speaker direction of attention unless specifically instructed to do so. Shows empathy toward others and can identify and display appropriate emotion.
(pp.
).
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Non adaptive behaviors: Non- functional speech (e. g. repeating phrases from books and movies), repeatedly hitting self and throwing self on the floor and participating in repetitive routines.
Aggression: Engages frequently in aggressive behaviors (more than 5 aggressive episodes per day). Displays non- compliance and aggressive behaviors directed toward others. Aggression directed towards self and others , pinching, hitting, screaming, kicking, and scratching generally occur during non- structured activities , new activities , difficult tasks , and transitions from one activity to another to escape/avoid a non- desired activity transition and , during academic activities.
Student 7 Standardized Assessments:
According to the student's records , the severity of disability prohibits successful participation in standardized testing.
Social Interactions and Language Use: Primary form of communication is through picture/word exchange system , visual symbols , American Sign Language , and some non-word vocalizations. He is expressively limited , both verbally and through sign language and wil not initiate interactions with others. Using sign language , his sentence length is one sign; he does not string signs together to form sentences. He typically relies on body language/gestures. Many of the signs he uses are made-up. He frequently tantrums during transitions or social interactions (pinching hitting).
Non-Adaptive/non- functional behavior: Non- functional
vocalizations ,
hand flapping, and engaging in repetitive activities
Aggression: Hitting, kicking, pushing, and pinching. Aggression is frequent (5- 10
episodes a
day) and typically occurs during transitions from one activity to another.
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Black , A. & Taylor , P. (1997). Festival speech synthesis system: System documentation (1.1.), Human Communication Research Centre Technical Report HCRC/TREdinburgh. Bosseler , A , & Massaro , D. W. (in press). Development and Evaluation of a ComputerAnimated Tutor for Vocabulary and Language Learning for Children with Autism. Under review. http://mambo. ucsc. edu/ Journal of Autism and Developmental Disorders.
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Language Learning
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Mailing Address:
Dr. Dominic W Massaro Department of Psychology
University of Califrnia Santa Cruz, CA 95064 USA Work: 837- 459- 2330
837 - 459- 3579 email: massaror:fUzz. ucsc. edu http://mambo. ucsc. edulpsl/dwm/ URL:
FAX
ACKNOWLEDGEMENT The research and writing of the paper were supported by grants from National
Science Foundation (Grant No. CDA- 9726363 , Grant No. BCS- 9905176 , Grant No. IIS- 0086107), Public Health Service (Grant No. PHS ROI DC00236), a Cure Autism Now Foundation Innovative Technology Award , and the University of California Santa Cruz. The authors would like to thank the teachers and staff at the schools and the parents and children for their cooperation; Michael M. Cohen , Rashid Clark , and Karl Young for their help at all stages of the research; and Justin Wiliams and Patricia Lindamood for helpful comments on the paper.
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Book Review:
Robert A. Naseef , Ph.
You re Going to Love this Kid!:
Teaching Students with Autism in the Inclusive Classroom Paula Kluth , Ph.
, Brookes Publishing, 2003
A book dedicated to guiding the teaching of students classroom is long overdue. in the Inclusive Classroom
You
with autism in the inclusive
re Going to Love this Kid!: Teaching Students with Autism
is a landmark work by Paula Kluth , Ph.
, an Assistant
Professor in the Department of Teaching and Leadership at Syracuse University. She
has been a special educator and inclusion facilitator and currently consults with school districts across the country. In her book , she provides ready- to- use strategies for including students with autism in both primary and secondary school classrooms. First- person accounts of students autism give readers insight into the experience of
having autism and show educators how to adapt classrooms to support student participation in class work , school routines , social activities and more. This volume is unique in many ways in the world of teacher education. It focuses exclusively on inclusive education as both ideology and pedagogy. Communication
behavior , and learning problems are understood in context and within relationships. Useful strategies for teachers , administrators , therapists , counselors , etc. are included. In addition , the voices of students with autism spectrum disorders are featured in a sensitive and enlightening fashion. As the author notes ... these students are often a catalyst for change and creativity. Specifically, including students with autism may help teachers think more carefully about the choices offered to students: the design of the lesson; the ways in which students can participate in teaching and learning; and the comfort, engagement , and opportunities for all." (p. 31) Kluth shows educators how to adapt their classrooms to support student participation in classwork , as well as school routines and social activities. The author skilfully weaves relevant research with lessons learned from her teaching experience to give readers a comprehensive approach with specific ideas that are both pragmatic and creative for: values , and actions that support inclusive schooling connecting, communicating, and collaborating effectively with families
. understanding the attitudes ,
145
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literacy by adapting reading materials , using visuals , and tapping in to student interests planning challenging, multidimensional lessons that encourage all students to participate and help students reach their individual goals supporting student behavior in sensitive , positive ways fostering friendships and social relationships between students with and with-
. enhancing . .
out autism
. adapting
the physical environment for students with autism who may have
heightened sensitivity to factors like temperature , sounds , and smells
Meeting students " where they are " at every turn makes Kid!
philosophically compatible with the concepts
You
re Going to Love this
of " Floortime "
and the
DIR
model. Furthermore , the language and practices of inclusive education go a long way towards responding to the diversity that exists in every classroom. The weakness for this reader is the incomplete treatment of how to handle the nonverbal child with autism who does not have a reliable communication system and whose behaviors
can be extremely challenging and even disruptive to the classroom as a whole. One
gets the impression that all specialized settings and self- contained
classrooms are
obsolete. Another stumbling block that needs more consideration is the resistance to accepting inclusive education in a school culture that is often competitive , individualistic , and authoritative. As we can see all too clearly in the world around us , culture changes slowly and only with respect and patience for the other s point of view. On the whole , Kluth' s book is a dynamic and absorbing read that gives educators a humanistic perspective on understanding students with autism - and helping them participate as fully as possible in every aspect of classroom life. The author aspirations encompass the whole classroom- that all learners feel safe , comfortable and capable. Towards this objective , Kluth provides astute guidance in preparing teachers and students for inclusive schooling. Learner- centered , multi- dimensional perspectives for effectively educating kids with autism , their peers and their teams come to life. Paula Kluth intelligently embraces the full spectrum of team , family, and learning perspectives.
While the primary audience for this book is classroom teachers , parents and other professionals working in partnership on a child' s team wil find this volume comprehensive and extremely valuable. Mailing Address:
Robert A. Naseef Ph. 574 S. Street
Philadelphia, PA 79747 Voice: 275- 592- 7333 Fax: 267- 200- 0806 www. sbecialjmilies. com
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