Neurogenesis: Vol 2, Issue 2

Volume 2 Issue 2 Spring 2013

Copyright Š 2013

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Editorial Board Editors-in-Chief

Faculty Advisors

Rory Lubner Class of 2013 rory.lubner@duke.edu

Leonard White, Ph.D. Duke University School of Medicine Director of Education Duke Institute for Brain Sciences len.white@duke.edu

Kelly Ryan Murphy Class of 2013 kelly.murphy@duke.edu

Christina Williams, Ph.D. Professor Director of Undergraduate Studies Duke Institute for Brain Sciences williams@psych.duke.edu

Publishing Editor Biqi Zhang Class of 2014 biqi.zhang@duke.edu

Craig Roberts, Ph.D. Assistant Director of Education Duke Institute for Brain Sciences craig.roberts@duke.edu

Managing Editors Banafsheh Sharif-Askary Class of 2013 bs118@duke.edu Ha Tran Class of 2015 ha.tran@duke.edu

Ann Motten, Ph.D. Department of Chemistry ann.motten@duke.edu

Associate Editors

Design Editor Tiffany Chien Class of 2015 tiffany.chien@duke.edu

Online Editor Kyle Rand Class of 2014 kyle.rand@duke.edu

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Parth Chodavadia Clara Colombatto Michael Farruggia Anouska d’Abo Sheetal Hegde Keshov Sharma Andrea Tan Julie Yi

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Letter from the Editors Here’s to the future...

As the school year draws to a close, graduation festivities beg us to indulge in something other than, well, neuroscience. We are pulled into play—to interact with our peers, to engage our brains in social settings. Yet, the field of neuroscience calls us back, tricking us with the word “social” placed in front of it—to a point where we feel compelled to make social neuroscience the focus of this pre-graduation issue.

Undoubtedly, social neuroscience is much more intricate than human interaction and feelings. It digs deeper into how people think and why they act. It further examines the situations when thoughts, actions, and feelings are negatively altered by the disordered brain. These themes appear consistently in the pages before you—with articles on selective attention, mirror neurons, and second language acquisition—and then, with three articles on schizophrenia, we have an entire section dedicated to the disordered brain.

Our feature articles also take root in social neuroscience. While Cary Politzer looks at what drives us to addiction with his exploration of the insula, Jamie Stark examines a specific behavioral response involved in adolescent decision making. But most importantly, this issue marks the beginning of Neurogenesis going international. The articles from Auckland, New Zealand and London, United Kingdom bring us to a new age of sharing undergraduate research. We hope this is only the beginning of locations to come.

Having been involved with Neurogenesis for the past three years, it is with great pleasure that we publish our last issue before graduating. Let this be our adieu as we embrace the cognitive battles ahead. But before we do, we must thank the incoming Editors-in-Chief, Biqi Zhang and Kyle Rand, for accepting the challenge we leave them—to continue to improve and expand Neurogenesis.

Sincerely,

Rory Lubner & Kelly Ryan Murphy Editors-in-Chief

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Table of ConTenTs 8

The effect of glove size in rubber hand illusion on object size estimations Eva Burlot

13

Tracking neural changes as a consequence of second language acquisition Junmi Saikia

16

Neural mechanisms implicated in visual selective attention as indexed by event-related brain potentials Olivia Salthouse

21

Electrophysiological evidence for a suppressive mechanism to the debate over selective attention Kyle Rand

30

A review of current psychopharmacological approaches to the treatment of schizophrenia in children and adolescents Caley Burrus

37

Schizophrenia and alterations in the fetal environment

44

Schizophrenia: An autoimmune disease?

47

Huntington’s disease: A monogenic mystery

F eature

a rticles

Max Castillo

Joshua Coulter

Han Jun Kim

2 25

The insula’s emergence in drug-related cravings and its potential role in addiction treatment Cary Politzer

Pupillary response to reward and loss: A comparison between adults and adolescents Jamie Stark & Youngbin Kwak

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The insula’s emergence in drug-related cravings and its potential role in addiction treatment Cary Politzer1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Cary Politzer (cary.politzer@duke.edu) 1

Substance addiction may cause harm to the individual, family and loved ones, and society as a whole. Its central feature is compulsive drug use: the loss of control over the acts of drug seeking and drug taking (A. Goldstein, 1994). Although substance use may seem voluntary to the outside observer, people who are addicted to drugs continue to seek and use them at a detriment to their health, relationships, livelihood, work, and other aspects of their lives. Therefore, gaining an understanding of the neurological underpinnings of the disorder may contribute to the discovery of valuable treatment methods in preventing drug use and maintaining abstinence. Until recently, the literature in drug addiction research has focused on a competition between the executive function of cortical areas and subcortical dopaminergic reward regions (Ernst & Paulus, 2005; Kringelbach, 2005; S. T. Tiffany, & Carer, B.L., 1998), but recent evidence suggests that processes beyond reward, pleasure, and desire are also implicated in addiction (Kelley & Berridge, 2002, Naqvi et al., 2009). In particular, interoception, decision making, and emotional experience, which are mediated at least in part by the insula, are such crucial neural processes.

This paper describes evidence for insular involvement in drug addiction, a model in which the insula translates the bodily effects of drug taking to cognitive awareness and executive functions, and novel methods of addiction treatment that incorporate this insular framework.

Historically, the motivational effects of drug dependence have been implicated in substance addiction. In 2000, Berke and Hyman mapped the action and projection of the dopaminergic reward system in rats and explained its relation to habitual learning, which can lead to compulsive drug use. Continuing these investigations, Koob et al. (2004) traced the brain reward and stress circuits in rats that result in negative motivational states and demonstrated a new dopaminergic set point at which the rats were compelled to maintain by self-administering cocaine. We can determine from these and other studies that the mesolimbic dopamine reward system is important to addiction; however, animal studies cannot capture the complex human decision making involved in the acquisition and abstinence of an addiction, especially because of the complexity of social and societal pressures.

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Addressing a major limitation of the animal addiction model, which does not differentiate hedonic “liking” from reward “wanting,” Kelley and Berridge (2002) outlined the Incentive-Sensitization Theory, which postulates that the mesolimbic dopaminergic system is sensitized to drug “wanting” even in the absence of “liking” the drug.

This theory explains the incentive motivation behind drug seeking even if the act of taking the drug is not pleasurable, i.e. subcutaneous injections elicit pain. Under this framework, addiction results, at least in part, from neural adaptation and plasticity, which sensitize the neural networks of wanting to the effects of drugs and peripheral drug stimuli. On the other hand, the neural networks for “liking” do not adapt in the same way as those for “wanting,” as evidenced by the characteristic increase in drug seeking behavior despite a decrease in drug effect. Therefore, a person might not like a drug but would increasingly want it as the addiction progresses (Berridge & Robinson, 2003).

In addition, drug “wanting” has been broken down further into conscious, goal-oriented and subconscious, habitual states. This suggests that cortical regions such as the OFC/ vmPFC are recruited for the conscious component of the “wanting” state, whereas subcortical dopamine projections to the amygdala and nucleus accumbens are responsible for subconscious component (Berridge & Robinson, 2003; Kringelbach, 2005). As a goal-oriented, rational behavior, voluntary drug taking in order to feel a hedonic “kick” arises from the former system, whereas uninformed compulsive drug taking is an example of the latter; thus, it may be postulated that dopamine modulates a transition in neural circuitry from executive control mediated by the OFC/vmPFC to drug seeking compulsions mediated by the nucleus accumbens in the ventral striatum (Everitt & Robbins, 2005).

Although dopamine system involvement had been established in addictive behavior, it was not shown to be necessary to maintain addiction. In a landmark study, Naqvi et al.

(2007) conducted a lesion study to determine if the insula were necessary in addiction to cigarette smoking. They found that the quitting rate of smokers who had insular damage in the right, left, or bilateral insulae were more likely than those with other lesions to quit smoking after the lesion was acquired (68% and 38%, respectively). They then administered a retroactive survey to the participants to find the pro-

OpiniOn portion that experienced a “disruption of smoking,” which indicated no relapse with a complete lack of any urge to smoke. They found that 63% of insula patients experienced “disruption of smoking,” as opposed to only 8% of controls. These results suggest that the insula is necessary for the conscious urge to smoke and provide evidence that subjective urges are important in maintaining addiction.

Although these results are promising, the study does have limitations. It has a small sample size (N=19) and nonspecificity in the lesion area. Other possibly confounding effects arise from the consequences of insular lesions besides smoking cessation. For instance, these effects, which mostly include abnormalities of autonomic function, sensory impairments, aphasia, and apathetic mood and willed action, could each independently affect smoking urges (Ibañez et al., 2010). Furthermore, it is yet to be determined if a lesion in the OFC/vmPFC, ACC, or dlPFC would also cause disruption of smoking addiction.

A conditioned place preference study of rats resolves many of these issues (Contreras et al., 2007). Rats were given the choice of entering a dark compartment or a bright white compartment, and they consistently chose the dark compartment at first, presumably because it offered protection from predation. When injected with methamphetamine in their tail vein while in the white compartment but not in the dark compartment, the rats reliably changed their preference to the white compartment. When their bilateral insulae were injected with lidocaine, a reversible inhibitor of neuronal activity, their preference switched back to the dark compartment. Then, when the lidocaine injections stopped, they switched their place preference again to the white compartment, where they received a dosage of methamphetamine.

The findings from this study, combined with those from the Naqvi et al. (2007) human insula lesion study, provide evidence that the insula is necessary for the explicit motivation to take drugs, that this function is common across drugs of abuse, and that explicit motivation is an important factor in the maintenance of drug addiction.

Because animal models cannot fully explain human addiction, experiments in human participants shed light on the neural mechanisms underlying the disorder; however, many of the techniques used in animal experiments cannot be adapted for human experiments due to ethical concerns.

Thus, noninvasive imaging techniques are often employed while eliciting addiction cue responses. Using functional magnetic resonance imaging (fMRI), the most consistent brain regions associated with drug cue wanting are the OFC/vmPFC, ACC, dlPFC, and insula with a similar response across a variety of drugs of abuse, including psychostimulants, alcohol, opiates, and tobacco, and studies are now converging to implicate the insula in cravings (Garavan, 2010). A recent study shows that cognitive inhibition of video-induced craving response in cocaine abusers is associated with a reduced metabolism in the right posterior insula (Volkow et al., 2010). Another demonstrates that men who actively inhibit their desire for food dur-

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ing an fMRI scan have a corresponding reduction in insular activation (Wang et al., 2009). Taken together, these findings implicate the insula in drug cue-induced urges.

As an important factor in addiction, why is the insula only being brought to attention now? Historically, the insula has been associated with pain, gustatory sensation, fear, anger, and disgust (Phan, Wager, Taylor, & Liberzon, 2002). It is activated by taste memory, aversion, and learning (Small, 2010) and appetitive feelings such as hunger (Wang et al., 2009) and sexual desire (Childress et al., 2008). Insula lesions are associated with impairment of conscious emotional feeling, such as reduced arousal in response to both unpleasant and pleasant stimuli (Berntson et al., 2011) and an impaired experience of disgust (Craig, 2002). In addition, the insula creates “as-if ” representations of body states, which may foster recall of emotional feelings from the past (Damasio, 1994). Peripheral cues can initiate that positive feedback cascade, especially for drugs that do not elicit a high CNS response such as nicotine, and the insula engenders involuntary bodily responses and conveys them to other brain regions. More recent studies show that the insula unifies hedonic body state and homeostasis in a process called interoception (Craig, 2002). This conscious emotional experience conjures a representation of body states essential to survival and allows humans to decipher the sensory information that they receive from their body. Thus, interoception may provide the avenue for continued drug “wanting” despite the absence of drug “liking” because both incentives and internal states are important in seeking drugs (Paulus, 2007).

Because the insula is involved with interoception in addiction, the underlying neural circuits that govern this process are essential to understanding addiction complexity. Utilizing a bottom-up approach, interoception depends on the thalamocortical pathway, which projects body state information to the posterior granular insula (Craig, 2002). That information is then passed ventrally and anteriorly to the anterior agranular insula, which projects primarily to the ACC, OFC/vmPFC, amygdala and nucleus accumbens for upper-level conscious processing and the integration of autonomic and visceral information into emotional and motivational functions (Gray & Critchley, 2007). Furthermore, the insula is rich in neurotransmitter receptors, allowing it to allocate tasks and assign resources efficiently. The insula receives high levels of dopaminergic innervation because of its high density of D1 dopamine receptors (Gaspar, Berger, Febvret, Vigny, & Henry, 1989; Hurd, Suzuki, & Sedvall, 2001), as well as endogenous opioids and opioid receptors, which are partly responsible for pain modulation and the rewarding effects of drugs of abuse (Baumgartner et al., 2006).

In addition, the insula contains a high concentration of corticotropin-releasing hormone receptors, which are involved with stress relief motivation (Sanchez, Young, Plotsky, & Insel, 1999). Evidently, the insular cortex, although an “island,” is diverse in neural connectivity and operates under many distinct and versatile circumstances.

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The insula’s tie to addiction may at first seem questionable. Why should interoception be as important as the dopaminergic reward system, for instance? After all, historical neurobiological models of addiction pin the rewarding effects of substance abuse as its primary goal (R. Z. Goldstein & Volkow, 2002; Robinson & Berridge, 2001). Dopamine certainly holds a large stake in addiction, but addiction is much more complex than just maintaining a set point of dopamine in the brain. The hedonic feeling that arises from drugs of abuse inherently involves body state, which is deciphered by the insula.

The emotional feeling which leads to compulsive drug use can also be triggered by cues. Generally, this process begins by introducing an emotional object, i.e. a drug cue, to the senses of a substance-addicted person, either consciously or subconsciously. This information is then projected to areas such as the OFC/vmPFC and amygdala, which translate it into conscious pleasure—for instance, imagining how the drug would feel. The signal also projects to other areas, such as the nucleus accumbens, which is involved in initiating and invigorating motivated actions, such as drug seeking behavior (Naqvi et al., 2007). Furthermore, conflicting signals from the insula and dlPFC converge in the ACC when, for example, an addicted person sees a drug cue but then faces conflict between wanting to take the drug and the avoidance of short- and long-term negative consequences (Franklin et al., 2002). The conscious thought of wanting the addictive drug, the physiological response to that thought with a feedback cascade, and the motivational behavior of drug seeking all result from the initial cue. Thus, the insula is highly implicated in the integration of body state information when confronting a drug-related cue, and it projects all over the brain with continuous feedback.

Just as the recall of a delicious ice cream flavor might prompt someone to seek that flavor again, recall of the interoceptive effects of the drug use ritual might prompt an addicted person to seek the drug. Cue-induced urges, triggered by areas that receive information about the presence of drug-related cues in the external environment, activate this recall of the sensory representation of the body stimulus that has been encoded into memory by prior drug use (Lovero, Simmons, Aron, & Paulus, 2009). Such emotional memory may link the complex rituals of drug use to craving and seeking behavior. In smokers, for instance, nicotine replacement alone does not satisfy cravings because transdermal nicotine does not prompt the emotional memory recall of smoking. On the other hand, denicotinized cigarettes, while paired with the transdermal nicotine, is much more effective in promoting abstinence and preventing relapse (Donny & Jones, 2009). Even though smoking denicotinized cigarettes is unpleasant, participants continue to smoke them because they suppressed some aspects of craving and withdrawal (Shiffman, Ferguson, & Gwaltney, 2006). Therefore, by simulating the drug taking experience, subjects could recall the emotional memory of the body state associated with taking the drug at some past time 4 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

OpiniOn and satiate the craving, decreasing the likelihood of relapse.

Drug use can cause a host of negative social, emotional, medical, financial, and legal consequences, each of which might spawn further negative hedonic body states that the drug might normally counteract. People who are addicted to drugs sometimes make the decision to overcome their addiction and quit. In the decision process to stop using a drug, they may weigh the immediate pleasurable interoceptive effects of drug taking against the representation of longer-term negative consequences of drug use. Because people with substance addiction generally discount long-term reward, they are more likely to relapse (Ernst & Paulus, 2005; Paulus, 2007), a phenomenon that has been studied using fMRI (Brody et al., 2007). Conflict between drug taking and abstinence is signaled by the ACC to the OFC/vmPFC, but if the immediate reward triumphs, then more attention is allocated toward drug-seeking goals.

However, this diverts attention away from alternative, nondrug goals, and disrupts inhibitory control processes within the OFC/vmPFC. As a result, the drug-taker is faced with automatic, implicit, and habitual motivational processes, which are much more difficult to control.

Urges that contribute to relapse can be subdivided into two types: cue-induced urges, which are long lasting and persist after drug replacement, and withdrawal urges, which last only days to weeks and reverse after drug replacement (S. T. Tiffany & Conklin, 2000). This distinction is most important during the early withdrawal phase of abstinence in which the representation of the positive hedonic experience of taking the drug may result in urges that many people find too hard to resist, resulting in relapse. However, if abstinence can be maintained past the initial withdrawal and habitual phase, relapse becomes much less likely despite cue-induced urges remaining intact. Insula lesions but not OFC lesions impair drug cue approach, and OFC but not insula lesions impair withdrawal cue avoidance (Scott and Hiroi, 2011).

Thus, the insula is involved with drug cue approach, and may also be linked to avoidance of withdrawal cues, perhaps because higher-level processes dampen down the aversive body state before the insula can recreate it.

The interoceptive model of addiction predicts that the interoceptive effects of drug use activate brain networks for conscious feelings and motivation, which include the insula and downstream targets such as the OFC and amydala. Such activity is related to the modulation of hedonic value derived from the interoceptive effects of drug use. Therefore, disrupting insula function may have a strong role in addiction treatment moving forward. Because it would be impractical and unethical to lesion the brains of people who have addictions, the next best method may be the modulation of insular function.

One relatively new method that could be used to modulate certain parts of the brain is repetitive Transcranial Magnetic Stimulation (rTMS). By passing current through a coil and placing it on the scalp over a specific brain region, a magnetic field arises that can depolarize or hyperpolarize

OpiniOn the neurons in the brain region, depending on the frequency of the pulses. This, in turn, can disrupt or excite the neural signals in that area. Therefore, rTMS can be applied to test hypotheses about the causal role of brain regions in modulating craving without long-lasting adverse side effects.

Because the insula is deep within the brain and hidden by the frontal, parietal, and temporal opercula, classic rTMS methods often cannot isolate it. Thus, studies have focused on stimulating brain regions that project downstream to the insula, as well as to the ventral striatum.

For example, a potentiated response to smoking cues was found during the application of rTMS over the Superior Frontal Gyrus (SFG) in the high frequency 10-Hz condition despite the lack of an attenuated response in the low frequency 1-Hz condition (Rose et al., 2011). Because the SFG projects to the insula, it may actually potentiate insula function in causing drug cue-related urges. In fact, the neutral cues, when paired with low-frequency magnetic stimulation, attenuated the cue-induced craving response.

Thus, by engaging in nonsmoking stimulus environments that inhibit cravings, patients may disrupt craving responses that might precipitate relapse after their smoking cessation attempt. These combined results may be important for potential addiction treatment using rTMS. For instance, subjects may respond to attenuation of the SFG while focusing on non-drug-related cues or on negative consequences of the drug. Additionally, as studied in the treatment of depression (Vedeniapin, Cheng, & George, 2010), it may be possible to speed up recovery by reconfiguring the neural networks related to cravings by simultaneously administering cognitive training and rTMS. Another method of rTMS is deep stimulation using an H-Coil instead of a classic figure-8 coil (Zangen, Roth, Voller, & Hallett, 2005). Because the electric field of the H-coil decays slower as a function of distance than that of the figure-8-coil, it is possible to stimulate deep brain regions or a combination of regions. Using this technology, it may soon be possible to isolate the insula in rTMS, which could lead to inhibition of drug cravings in response to cues. If multiple brain regions associated with cue-induced urges, such as the SFG (Rose, 2011), dlPFC (Fecteau, 2010), and insula, were targeted using rTMS, this may become a viable and reliable addiction treatment method. However, rTMS is still too imprecise to consistently hone in on small brain regions such as the insula, and the effects of deep rTMS on unintended brain regions still has to be studied more extensively. Other side effects of altering insula function must also be considered.

Although Naqvi et al. (2007) claims little change in behavior and cognition in the insula lesion patients besides the reduction of cravings, reduction of insular function has consequences beyond just removing drug cravings, such as gustatory, olfactory, auditory, and somatosensory perception, as well as body awareness (Ibanez et al., 2010).

In addition to rTMS, cognitive behavioral therapy (CBT) is a psychological approach to addiction treatment that aims to restructure cognitions and reduce maladaptive

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behaviors. This treatment concentrates on relieving symptoms of the disorder by reframing and reorganizing cognitions. By learning how to think and act effectively in a clinical setting, patients can later call upon that knowledge in the real world and eventually reconfigure their brain circuits to automatically think and act that way (Carroll et al., 2008). For instance, by focusing on craving and the cognitive interpretations of them, patients can learn how to detect a craving and how to avoid its escalation to drug seeking. Interoceptive and cognitive control exercises may help to develop coping in real life situations, such as being confronted with a drug-related cue. Furthermore, patients can learn how to avoid drug-related cues and gradually extinguish bodily and emotional memories for the pleasurable interoceptive effects of drug use.

Another avenue of addiction treatment is pharmacotherapy that targets insular function. The most common mechanism by which pharmacological drugs target addiction is the substitution of the addictive substrates in the brain, as methadone does for heroin (Spiga et al., 2008).

However, the replacements are oftentimes also addictive and can even lead to worse functional deficits and more side effects than the original drug (Pirastu et al., 2006).

Thus, changing drug metabolism may be a better avenue for future methods. By selectively inhibiting receptors associated with the specific drug, such as enzymes necessary for metabolizing nicotine in the case of smoking addiction, pharmacological treatments decrease the pleasant effects of drug use and possibly decrease the cue-induced urges associated the drug. In addition, parallel pharmacological drug treatments could be tailored to affect the function of the insula. For instance, the insula’s richness of D1 dopamine receptors may make it a good candidate for dopamine agonists and antagonists, which can modulate its function to affect interoception and, thus, cue-induced drug cravings. Furthermore, the modulation of CRH1 receptors within the insula can influence the expression of withdrawal urges (Addolorato, 2011). By decreasing the function of the insula, cue-induced urges could weaken, and the addicted person would be less likely to relapse.

Because the change in peripheral body state is important in absolving drug craving, simulation drugs can help decrease the severity of cravings and lead to abstinence.

For example, denicotinized cigarettes mimic the airway irritant effects of cigarettes with nicotine (Rezaishiraz, Hyland, Mahoney, O’Connor, & Cummings, 2007). Although they do not induce pleasure, they can successfully hold off withdrawal urges, and they can gradually reduce the habitual aspects of smoking by doing the drug action without the paired drug stimulus (Donny & Jones, 2009). Furthermore, cue-induced urges may also decrease over time because cues that once were associated with a drug, i.e. nicotine, become associated with an unpleasant stimulus. Gradually, new neural circuits may form with the cognitive association of the negative body state that arises from interoception in the insula.

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fect of cue-induced cravings, people struggling with drug addiction may be able to better manage their addiction and remain abstinent. Using rTMS, deep rTMS, CBT, pharmacotherapy, simulation drugs, or a combination of these may provide a means to that goal. Future experiments might separate the effects of interoception and the effects of emotional memory on drug use, and further work might investigate how interoceptive memories are encoded, stored, and recalled. Although many of the neural circuits of addiction are similar across drugs, it still remains to be seen if all drugs interact with the insula in the same way. Moreover, behavioral addictions, such as gambling, are largely understudied despite modest evidence of similarity to substance addiction; thus, their neural correlates, and their relation to the drug addiction literature, have yet to be established. Addiction is a complex disorder with societal, emotional, psychological, genetic, and many more diverse risk factors that contribute to its etiology and prognosis. A better understanding of the insula’s role in the maladaptive behavior may prompt novel treatment methods and preventive policies that reduce its prevalence, cost to the individual, and cost to society.

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The effect of glove size in rubber hand illusion on object size estimations Eva Berlot1 University College London WC1E 6BT, United Kingdom Correspondence should be addressed to Eva Berlot (eva.berlot.11@ucl.ac.uk) 1

Recent findings suggest that representation of one’s body is used as a reference for perception of external objects. Using the rubber hand illusion, we manipulated participants’ representation of their hand size. Illusion was induced in 32 participants using a small, medium-sized or large glove and participants then estimated ball diameters. Results indicated that glove size modulated diameter estimates: viewing a large glove resulted in underestimations of ball size, medium glove in accurate estimates, and a small glove in overestimations; however, estimates in small and medium glove condition did not differ significantly. Results suggest that one’s hand size is implicitly assimilated to the size of the glove and that this assimilation in turn influences subsequent size estimations. Further research is needed to determine whether or one’s hand size can be assimilated to the small glove.

Introduction Experiencing one’s body as part of the self is a fundamental aspect of self-consciousness and is also crucial for everyday interactions with the external world. Sensations that we perceive from the outside world (e.g. touch) are important in constructing mental body representations. In particular, it was suggested that integration of multiple sensations results in self-attribution of body parts (Ehrsson, Holmes & Passingham, 2005). This bodyrepresentation is constantly updated through interactions with the world and is very flexible.However, only recently have researchers started questioning if these changes in body-representation are driven entirely by the interaction with external stimuli or whether the representation of one’s body can act as a reference and drive changes in perception of external stimuli. This study investigated the effects of changes in body representation on theperception of intrinsic properties of external objects. In order to manipulate the body representation, a rubber hand illusion was used. The Rubber hand illusion (RHI) was developed

by Botvinick and Cohen (1998) as a powerful instrument for manipulating one’s hand representation, position and ownership. In their original experiment, a visible rubber hand was placed in front of a participant and stimulatedin synchrony with the participant’s own hand, which was concealed from view. Participants formed a strong impression that the touch they were experiencing was coming from the viewed brush on the rubber hand and that the rubber hand was in fact their true hand. This was assessed qualitatively by completing questionnaires as well as quantitatively by indicating the position of the hidden hand.

The indicated position was systematically biased towards the location of the rubber hand, showing the illusion induced a recalibration of hand position. Botvinick and Cohen (1998) suggested that one unified multisensory event 8

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interpretation is preferred over two separate unimodal events and that such intermodal matching is sufficient for experience of body-ownership. Armel and Ramachandran further elaborated this explanation (2003) suggesting that two perceptions are “bound” when they often co-occur with a high probability. Thus, co-occurrence of spatially discrepant visual and tactile inputs is crucial for RHI as a person thinks that it is more likely to have one event in which visual and tactile inputs match than to have two discrepant events. Thus, the two events are combined into one sensation by projecting the tactile inputs onto the rubber hand and hence, one experiences a feeling of ownership over the rubber hand. Imaging studies support the view that a sense of body self is achieved by combining sensoryinformation. Functional MRI that utilized an RHI paradigm have shown that activity in anterior intraparietal sulcus, which is crucial for receiving signals from different senses, occurs before the subjective feeling of illusion (Ehrsson, Spence & Passingham, 2004). Activity of anterior intraparietal sulcus then converges to the premotor cortex, where multisensory integration takes place. Experience and strength of illusion correlate with this activity (Makin, Holmes & Ehrsson, 2008). Thus, evidence shows that multisensory integration is a crucial component for subjective experience of body ownership. Experiments reliably show that the rubber hand is incorporated into the body-representation in RHI. However, only a few studies considered the functional consequences of this induced self-representation. Armel and Ramachandran (2003) performed RHI on participants and simultaneously measured their skin conductance response (SCR), a measure of autonomic nervous system activity. Once the illusion was induced, they lifted the concealed finger of participants and bent the corresponding finger of the rubber hand into a painful position. In such instances, participants’ SCR in-

article creased significantly. Researchers concluded that the rubber hand was effectively assimilated to participants’ bodyrepresentation and that the illusion was strong enough to trigger reflexive responses of preparing to act defensively when the external cues acted violently with the rubber hand. Haggard and Jundi (2009) went a step further and aimed to investigate the role of self-representation in perception of external objects. They performed RHI on participants using a small and a large glove and after each session of stroking, they asked participants to assess the weight of a cylinder given to the palm of their hidden hand.

From results they got, researchers explained that viewing a small/large glove during RHI made participants feel their true hand was smaller/larger respectively. The cylinder felt larger/smaller due to the distorted representation of their hidden hand. Perceived object size then in turn induced a change in perceived weight as the “large” cylinder felt surprisingly light (i.e. in the small glove condition) and the “small” cylinder surprisingly heavy. Researchers concluded that RHImodulated self-representation of the hand size that acted as a reference for judging externalobjects. In the mentioned experiment (Haggard and Jundi, 2009), it was assumed that glove size does not modulate the strength of the illusion and researchers also reported no effect of glove size on participants’ phenomenological experience.

Similarly, Armel and Ramachandran (2003) measured circumference of the rubber hand used and participants’ hand and reported no correlation with illusion strength.

However, a number of studies suggest that stored knowledge related to the pre-existing representation of one’s body can modulate the emergence of the illusion (Tsakiris & Haggard, 2005).Pavani and Zampini (2007) suggested that the size of the rubber hand used can constrain the extent of the illusion experienced. In their experiment, RHI only occurred if the rubber hand used was larger than or of approximately equal size to the participant’s hand, but not when it was smaller. They concluded that people might find it easier to accommodate for an enlarged but not the reduced hand size to their pre-existing body-representation. In addition,Vignemont, Ehrsson and Haggard (2005) elicited proprioceptive illusion of elongating or shrinking index finger by vibrating the biceps or triceps tendon. When the finger appeared longer, the tactile distance between two points was perceived as bigger, but when it was shrunk, the tactile distance did not appear significantly shorter than it truly was. These findings support the notion that there is an asymmetric tendency within our body-representation to acknowledge enlarged, but not reduced images of body parts and cast doubt on Haggard and Jundi’s claims (2009) that glove size (in particularly the small one) does not affect the strength of illusion experienced. By employing a similar experimental method but adding a more direct measure of perceivedhand size, the current experiment aimed at replicating the findings by

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Figure 1: Experimental set-up presenting relative positions of the hands and the glove.

Adapted from M. Gudaitis (2010). URL: http://sites.davidson.edu/psy379/ is-that-my-hand-because-it-certainly-feels-like-it/.

Haggard and Jundi (2009), who suggested that self-representation provides a reference for judging perceptions of external objects. Participants were randomly assigned to one of the three conditions depending on the size of the glove used for inducing the illusion: Small, Medium-sized or Large. Firstly, RHI was induced in participants and afterwards, they were asked to judge the diameter of a ball put in their hand for four times in total. Participants’ size estimation error of the diameter of the ball was taken as a dependent measure. At the end, participants weregiven a questionnaire to assess the strength of the illusion and the perceived hand size change. Based on previous findings, the predictions were that when viewing the small/ large glove, the diameter would be estimated larger/smaller than veridical, but in the medium glove condition, there would be no size-estimation error. The hypothesis was that the size-estimation error varies as a function of the rubber hand size used.

Method Participants Thirty-two full-time university students (Female=17, Male=15) were enrolled in this study with a mean age of 20.75 years (SD = 2.06). Of the initial participants, three were identified as outliers as the inspection of boxplots revealed their scores to be more than 2 standard errors away from the mean. Their data were not analysed further. All participants were blind to the purpose of this study and took part in the experiment voluntarily.

Materials Experimental set-up The study was conducted in the Psychology Cubicles and participants sat in front of a desk. One of their hands was resting on their lap, whereas the other was placed on the desk (palmdown). One Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com |

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direct view of the hand that was resting on the desk throughout the entire experiment. On the other side of the panel, a rubber glove was placed and the exact position of participants’ hand was aligned according to the glove. It was ensured that the spacing between the folder and the hand equaled that between the folder and the glove. A scarf was used to cover the lower part of the glove.

Figure 1 depicts the experimental set-up.

Apparatus Three different sized rubber gloves were used.

The small glove (length (wrist - tip of middle finger) = 14 cm) was green and made from cotton. Medium (length = 19 cm) and large (length = 24 cm) gloves were yellow and made from latex.

Equal number of left and right gloves was used to control for the hand dominancy. Two paintbrushes were used for stroking participant’s hand and rubber hand at the same time. In the size-estimation training phase, participants were given three polystyrene balls with diameters of 2 cm, 3 cm and 6 cm. Polystyrene ball with a diameter of 4.5 cm was used for size-estimation testing. In order to test participant’s phenomenological experience and their perceived hand size a questionnaire was adapted from Botvinik and Cohen (1998).

Ten statements (4 target questions, 6 fillers) were presented on a 5-point Likert scale (strength of illusion experienced: 1-Not at all, 5-Very much; perceived hand size compared to normal size: 1-smaller, 3-normal, 5-larger).

Design and procedure The experimental design used was a between-subjects design with three levels of independent variable (i.e. rubber glove size). Participants were randomly assigned to one of the three conditions: Small glove (N=9), Medium glove (N=9) or Large glove (N=11). The dependent variable was size-estimation error, operationalized as participant’s average deviation from the veridical diameter of the ball.

Firstly, a participant was seated behind the desk while the rubber hand was concealed from him. Experimenter placed his hands according to the set-up. In the training session, he was given three balls one at a time into their hand behind the folder and was told their diameters. The order was counterbalanced between participants. There were no time limits and participants were encouraged to familiarize themselves with the sizes.

Next, the glove was shown and participant was asked to fixate on it throughout the entire experiment. The experimenter stroked the glove and the participant’s hand synchronously for five minutes. Then, the 4.5 cm ball was 10 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

article given into participant’s palm and he was asked to estimate its diameter. The procedure was repeated for three more times with the stroking sessions lasting for one minute and after each session, the 4.5 cm ball was given to the participants.

Afterwards, participants completed the questionnaire and were debriefed. The study lasted for approximately 20 minutes in total.

Results Strength of RHI and perceived hand size The scores of three target questions related to the strength of the experience of RHI were averaged for each participant and a one-sample t-test was performed comparing scores of all participants to 1 (defined in the questionnaire as “not at all” experiencing the illusion). The strength of the illusion experienced was significantly higher than 1 (t (26) = 8.41, p < .001). Following, the scores were compared to 2 (experiencing the illusion “slightly”) and the strength of illusion experience was still significantly higher (t (26) = 8.41, p < .001).

Thus, participants experienced RHI significantly stronger than “slightly” or “2” on a 5-point Likert scale. There was no significant effect of the size of the rubber glove perceived on the strength of illusion experienced (F < 1).

Target question 4 was measuring participants’ experience of the size of their tested hand compared to the normal size on a 5-point Likert scale. One-way ANOVA revealed that the perceived hand size did not differ significantly depending on the glove size presented (F < 1).

Size-estimation error Size-estimation errors were calculated by averaging participant’s four estimates of diameter size and subtracting the veridical size (4.5 cm) of the ball from the average. Hence, positive discrepancies represent overestimation of the diameter size, whereas negative values show underestimation.

As can be seen from Figure 2 below, participants in Small glove condition (M=0.625, SD=0.931) estimated the diameters as bigger than their veridical size; those in Medium glove condition (M=-0.061, SD=0.358) estimated diameters very close to the veridical size, and participants in Large glove condition (M=-1.173, SD=0.539) estimated the balls to be smaller than they truly were. Mean size-estimation error in Medium glove condition was not statistically different from 0 (t (6) = -0.448, p = 0.67) showing that size-estimations were not biased.

As Levene test was significant, non-parametric KruskalWallis test was used to determine if there was a significant effect of glove size on size-estimation errors. The main effect was significant (KW (2)=17.365, p < .001). Following, pairwise Mann-Whitney tests were performed. Difference in size-estimates of participants in Small and Large gloves conditions were significant (U = 3.00, z = 3.541, p < .001) and so was the difference between Medium and Large conditions (U = 2.00, z = 3.309, p = .001). Difference in mean

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Figure 2: Mean size-estimation errors for each condition.

size-estimation errors in Medium and Small conditions was not significant (U = 20.00, z = 1.229, p = 0.22).

Discussion The present experiment aimed to investigate whether self-representation provides a reference for judging perceptions of external objects. Participants viewing a large glove underestimated the size of the ball, those viewing the medium sized glove gave accurate estimates and participants in the small glove condition overestimated the sizes, however, estimates in the small glove condition did not differ significantly from the medium glove condition.

Yet, the direction of participants’ estimates of the ball diameter was as expected thus confirming our hypothesis that the size of the glove affects perceived size of the ball.

Analysis performed on the scores of target questions regarding the strength of the illusion showed that RHI was successfully induced in all participants. There was no significant effect of glove size observed on the strength of the illusion perceived. Finally, analysis of the self-report questionnaire regarding how big participants felt their hand was during the experiment relevant to outside of the experiment period showed that participants did not experience a feeling of hand size change in any condition.

Firstly, our findings are in accordance with those of Haggard and Jundi (2009). The pattern of size-estimation errors suggests that judgments were referenced to the participants’ modulated representations of their bodies. The size of the rubber hand they viewed influenced the perception of the size of their hidden and when touching a ball, they estimated the diameter size relative to their own perceived hand size. However, our question that was aiming to assess whether the size of the glove modulated participants’ selfrepresentation of their hand size did not capture that effect.

It could be that our measure was inappropriate. Namely, the

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question assumed participants were consciously aware of their hand size during the experiment. Instead, the influence of glove size on perceived hand size could be implicit.

The nonsignificant difference of participants’ size estimates in small and medium-sized glove conditions can be interpreted in more ways. Pavani and Zampini’s (2007) explanation would be that the small rubber hand did not induce the illusion and hence, no modulation in hand size occurred. Also, due to limitations of our material an additional weakness might be the fact that the smaller glove was coloured green and of rough material compared to the medium-sized and large gloves, which were of more similar appearance to the human hand. However, our results oppose this explanation, as analysis of questionnaire answers showed that all participants experienced the illusion equally strongly regardless of which glove was used. Still, it is possible that regardless of the illusion induced, the size of the small glove was incorporated into one’s body image to a lesser extent then the medium- and large-sized gloves. This asymmetry in modulation of body-representation could be understood in terms of experiences of bodily changes. Extension of body is well known to people, both through natural growth and incorporation of tools into body-representation (Farnè & Làdavas, 2000). In contrast, body shrinkage happens more slowly, to a lesser extent and only later in life with ageing (Haggard & Jundi, 2009). Alternatively, the nonsignificant difference for the small glove condition could be attributed to the fact that the glove was not small enough and some participants did not experience its size as differing from theirs.

Further experiments using a smaller glove and a better implicit measure of hand size are needed in order to resolve whether our insignificant effects are due to methodological issues or whether they have theoretical grounds. For the implicit measure, participants could be shown a slide ruler caliper after the end of the experiment while having hands still hidden from view. Experimenter would move it until participants said the opening between the jaws corresponds to their hand size (palmend of the middle finger) and this size would be compared to the true size of participants’ hands. Using such a paradigm, we would be able to determine whether participants assimilated the size of their hands to the glove size without asking them explicitly whether their perceived hand size changed during the experiment. In addition, also for the strength of illusion a more implicit measure, such as proprioceptive drift, could be employed.

Another limitation was that we analysed data according to the rubber hand employed, but did not take into account that participants differed in their hand sizes.

Instead, we could measure the discrepancy in the sizes (hand-glove) and investigate, if there is a linear correlation between the discrepancy and the size estimation errors. Further studies could go a step further and explore Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 11

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how body-representation affects actions with external objects. For example, a grasp sensor that would monitor the grasp opening of the palm of the participant while reaching towards a ball in view could be used.

Despite its limitations, current study replicated findings by Haggard and Jundi (2009) that manipulations of one’s body size representation affect estimations of intrinsic properties of the external objects. Information about size of the body parts acts as a calibrator and provides a reference for perception of external objects one interacts with. Thus, intrinsic representation of one’s body is not only passively constructed through interactions with external world, but it also has a topdown influence on external world. Internal representation of one’s body needs to be constantly updated to act as a temporarily useful reference frame. This shows that not only body-representation but also perception of external objects is a transitory flexible construct that is easily modulated. To conclude, we suggest that a sense of self, in particular one’s body-representation is crucial for interaction with external world.

Armel, K. C., & Ramachandran, V. S. (2003). Projecting sensations to external objects: evidence from skin conductance response. Proceedings of The Royal Society, Series B, 270, 1499-1506.

Botvinick, M., & Cohen, J. D. (1998). Rubber hand ‘feels’ what eyes see.

Nature, 391, 756.

Ehrsson, H. H., Holmes, N. P., & Passingham, R. E. (2005). Touching a rubber hand: Feeling of body ownership is associated with activity in multisensory brain areas. The Journal of Neuroscience, 25, 1056410573.

Ehrsson, H. H., Spence, C., & Passingham, R. E. (2004). That’s my hand!

Activity in the premotor cortex reflects feeling of ownership of a limb.

Science, 305, 875-877.

Farnè, A., & Làdavas, E. (2000). Dynamic size-change of hand peripersonal space following tool use. Neuroreport, 11, 1645-1649.

Gudaitis, M. (2010). Is that my hand? Because it certainly feels like it.

Retrieved December, 3, 2012, from http://sites.davidson.edu/psy379/ is-that-my-hand-because-it-certainly-feels-like-it/.

Haggard, P., & Jundi, S. (2009). Rubber hand illusions and size-weight illusions: Self-representation modulates representation of external objects. Perception, 38, 1796-1803.

Makin, T. R., Holmes, N. P., & Ehrsson, H. H. (2008). On the other hand: Dummy hands and peripersonal space. Behavioural Brain Research, 191, 1-10.

Pavani, F., & Zampini, M. (2007). The role of hand size in the fake-hand illusion paradigm. Perception, 36, 1547-1554.

Tsakiris, M., & Haggard, P. (2005). The rubber hand illusion revisited: Visuotactile integration and self-attribution. Journal of Experimental Psychology: Human Perception and Performance, 31, 80-91.

Vignemont, F. de, Ehrsson, H. H., & Haggard, P. (2005). Bodily illusions modulate tactile perception. Current Biology, 15, 1286-1290.

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Tracking neural changes as a consequence of second language acquisition Junmi Saikia1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Junmi Saikia (jms129@duke.edu) 1

SUMMARY: Secondary language acquisition has been well known for inducing plastic changes within various cortical regions of the human brain. Currently, literature in this field focuses on two main aspects: (1) age of acquisition versus proficiency and (2) changes in the functional and structural anatomy of the brain with increased second language proficiency.

Learning a second language varies over time, highlighting the general trend that increased age correlates with increasing difficulty in acquisition tasks, a concept well recognized within the scientific community (Perani et al. 1998). Age of acquisition and language proficiency has also been directly associated with the extent of structural reorganization in the left inferior parietal cortex, with increased grey matter density being proportional to the age of acquisition and proficiency of language mastery (Mechelli et al., 2004).

Our present study seeks to shift current research from focusing on the structural and functional changes that result from second language acquisition to how second language novelty (based on the linguistic family of the second language) would influence changes in the brain. To explore this issue, this research creates two overarching groups of participants â&#x20AC;&#x201C; English monolinguals and Chinese monolinguals. From here, these two groups are broken into three subsets: the non-learning group (control, eNLG and cNLG for English and Chinese monolinguals respectively), the romance-language learning group (eRLG and cRLG, both learning Spanish), and the idiographic learning group (eILG, learning Chinese, and cILG, learning Japanese). These two overarching groups will allow us to study the effects of learning a second language outside the speakerâ&#x20AC;&#x2122;s native language family (comparison within groups) and determine whether there are neural differences in an idiographic native language speaker learning a romance language versus a romance language speaker learning an idiographic language (comparison across groups).

Aims 1. Track and compare changes in English speaking monolinguals learning a second language. Monolingual English-speaking participants who have agreed to learn a second language (either same familySpanish or different family-Chinese) will be tracked as they learn a new language. During quarterly testing periods, participants will take a battery of language proficiency tests and undergo neuroimaging.

The neuroimaging-based measurements are for tracking neural changes as a function of mastery, which would then allow for comparisons between and across groups to assess potential trends in neural changes.

2. Compare plastic changes of the English group against the Chinese monolinguals learning a second language. Instead of focusing on romance-language monolinguals, we will test idiographic-language monolinguals (i.e. Chinese monolinguals) undergoing second language acquisition (either Japanese or Spanish). These participants will also be given quarterly assessments over the course of four years; undertaking similar neuroimaging measures to see if the changes found in English monolinguals learning a second language are equivalent to changes seen in Chinese monolinguals learning a second language.

Background Literature shows that with lowered language proficiency, second language learners and speakers rely heavily

on the prefrontal cortical (specifically the inferior frontal gyrus) regions with selectivity towards the left hemisphere (Tatsuno and Sakai, 2005; Stein et al., 2006). Effortful semantic interpretation of a second language that is common in novice second language learners depends on the frontal cortex â&#x20AC;&#x201C; specifically the Brodmann Area 47 (Fiez, 1997). The matter of interest here would be that in adult secondary language acquisition, the brain relies on different cortical regions to aid in the learning task since the declarative type of learning involved in a second language is different from the implicit type learning task for a first language (Perani et al., 2005). Interestingly, these prefrontal regions do not show continued activation with proficiency (Stein et al., 2009); rather, with increased mastery of a second language, activation becomes more prominent in left temporal regions, in a manner liken to that of a primary language, especially for brain regions involved in grammatical processing (Perani et al., 1998; Perani et al. 2005).

This study seeks to branch from the sole topics of age of acquisition versus structural and functional changes at the cortical level to measures of bilingualism. In contrast to previous studies, we examine a relatively uncharacterized side of language acquisition: how the novelty of a second language impact plastic changes. To clarify, several languages share the same roots and thus maintain similar alphabets and general syntactic structure. Such related languages are derived from the same language family and, therefore, learning languages within a linguistic family presents a lower degree of novelty as compared to learning Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 13

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languages across families. In this study, we seek to isolate different types of monolinguals (either Chinese or English speaking) learning a second language either akin or disparate to the groups’ first language. The point of this grouping is to determine whether the effects of learning a truly novel language are universal and beneficial to any language learner. We primarily hypothesize that there will be differences between a Romance language monolingual (English speaker) learning a second romance language (for example, Spanish) versus learning an idiographic language (with Chinese serving as the paradigm for idiographic languages).

Aims 1. Track and compare the changes between eILG and eRLG with respect to eNLG using four measures: voxel based morphology (VBM), electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and behavioral measures (language proficiency tasks). As a general note, members of the control groups (eNLG and later the cNLG) will conduct language tasks in their native language.

I. VBM: We will track changes in grey matter (GM) density in this brain region increases using quarterly VBM measurements. We will use structural MRI scanners with gradient echo sequences to acquire GM images. We hypothesize that over the course of four years, we will see increased density in this regio, and that this will correlate with the behavioral tests that measure for language proficiency (Mechelli et al., 2004).

II. EEG: Visual stimuli can be interpreted in either an orthographic or non-orthographic manner (Appelbaum et al., 2009). Using mastoid recordings as a baseline, we will present meaningful and meaningless visual stimuli to the three groups and observe how processing of this visual stimuli results in the recording, focusing on the left occipital scalp region. We will present the subjects with a series of “nonwords” and “target” words. The participants will be told ahead of time that target words would be limited to any word taught as vocabulary in the classroom setting.

A second EEG task will test semantic meanings for phrases. In the same style of the target word and nonword task, we will present target phrases and nonphrases. Phrases will be short lines of text that either have or do not have actual meaning (an example of a target phrase would be: “a cup of coffee”; a nonphrase would be: “a cup of cloud”).

In response to a phrase containing semantically incongruent words, the EEG records a negativegoing potential approximately 400 milliseconds (N400). We predict that initially, the firing of this negative potential may lag a bit (due to effortful semantic processing) in the first few months. With 14 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

letters increased proficiency however, the time lag exhibited in the beginning of the study should diminish and start to match the expected 400 ms speed.

III. fMRI: Participants will repeat the task outlined in the EEG within an fMRI machine to look for specific deep-brain regions that are active during discrimination tasks outlined in the EEG section (rather, these tasks may be performed in a joint fMRI/EEG study). The fMRI measurements, which will be taken in a full-body scanner, will also look at auditory comprehension to see brain regions involved in interpreting a new second language.

While in the fMRI, participants will hear a two minute dialogue. This dialogue will be presented twice per trial. After the second presentation, the subject will be asked to describe what happened in the scenario. By analyzing BOLD signaling during the listening task, we aim to pinpoint how a second language is interpreted when presented in an auditory (as opposed to visual) form. We hypothesize that with proficiency, the signal will shift from frontal to temporal/parietal brain regions (Tatsuno and Sakai, 2005; Stein et al., 2006; Fiez, 1997; Stein et al., 2009; Perani et al., 2005).

IV. Behavioral Measures: Participants will be subjected to a battery of language proficiency tasks to help keep track of acquisition and mastery over the four-year period. These behavioral measures will include testing in the subsets of vocabulary, grammar, writing fluency, reading comprehension, aural comprehension, and spoken language production.

These tests will be designed so that questions are presented in an increasingly difficult manner, such that the beginning of a test is easy while the end of the same test is hard. A general increase in scores (across all domains) would signify improvement in the second language. While the tests will not be same each time (to prevent a habituation effect), they will be equally challenging and will test the same higher-level language skills throughout the eight sessions. Lower scores are expected in the first sessions with increasing scores in later sessions as participants become more fluent in their second language. Testing will be conducted similar to how “final exams” are conducted at universities.

2. Compare findings from the English monolingual group against Chinese-speaking monolinguals learning a second language by using the same measurement tools used in the English monolingual group.

I. VBM: Track the changes in the GM measurements at each meeting and observe not whether GM changes will occur but rather how they occur in comparison to the eILG and eRLG groups. We predict that gen-

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eral changes observed for the eILG-cRLG pairing and the eRLG-cILG pairing will be similar and that rates of change will differ between groups.

II. EEG: Utilize the same techniques and design schemata as Aim 1 to gather EEG data over the course of eight meetings. We will use the “Nonword” and “Target Word” paradigm introduced earlier, except instead of using Spanish and Chinese for the eRLG and the eILG respectively, we will use Spanish and Japanese for the cRLG and the cILG. III. fMRI: Track shifts in regions of activation, switching from frontal activation (resulting from effortful semantic processing) to left temporal parietal activation (for more natural second language processing). We expect that the cILG group will show earlier signs of mastery in the visual task. Therefore, left temporal activation should occur earlier than cRLG. In the case of cRLG and eILG, we predict that the cRLG group will pick up the novel second language much faster since there are fewer character/letters to be learned for romance languages as compared to East Asian languages.

IV. Behavioral Measures: Both Chinese monolingual learning groups will undergo a battery of language proficiency exams to account for changes in proficiency over time. cRLG and eRLG will receive the same language tests.

Comparative Analysis: After data collection for both groups at the end of the four-year period, the results from the English monolingual learning groups will be time matched with the results from the Chinese monolingual learning groups. Since the Chinese learning groups are meant to mirror the English learning groups, the bulk of comparisons will be drawn between the following two pairings: eILG to cRLG and eRLG to cILG. There will also be generalized comparison between both language groups to their respective control non-learning groups. We will use a multivariate analysis of variable approach to analyze the data collected from the six groups.

Conclusion Results from this proposed study will present researchers with a more in-depth understanding of how second language acquisition affects changes in neural connections, especially in regards to how novelty of a language may influence language acquisition and related brain changes. We expect that for both the cILG and the eRLG groups, changes will be minimal, as novelty of the second language is fairly low. However, we do expect that the cILG will still show greater degrees of modification because new idiographic languages are still fairly different than the first language. Simply, we expect that the data will show that the degree of novelty for an

English monolingual learning Spanish would be lower than that of a Chinese monolingual learning Japanese.

The more interesting findings, however, would be the results drawn from the cRLG and the eILG subgroups.

These two groups present “mirrored” learning groups, in which one purely phonetic monolingual is presented with the task of learning a purely idiographic language and vice versa. We expect that both of these groups would show greater degrees of changes from baseline as compared to the eRLG and cILG groups. However, it is difficult to predict which of these two groups present the absolute greatest plastic change. Should cRLG and eILG show similar changes, we can say that learning a highly novel language imparts plastic reorganization, regardless of a person’s mother language. Should the two groups present drastically different levels of changes from baseline, then we can start to consider how a person’s first language affects acquisition of a second language.

Limitations While Spanish and English are similar languages with the same basic alphabet, grammatical structures, and linguistic roots (as romance languages), the linguistic relationship between Chinese and Japanese is unclear. In addition to the idiographic kanji, Japanese written language also possesses a phonetic alphabet not used in Chinese. However, for the purposes of this study, these two languages are similar enough to mirror the relationship between English and Spanish.

Appelbaum LG, Liotti M, Perez III R, Fox SP and Woldorff MG. (2009). The temporal dynamics of implicit processing of non-letter, letter, and word-forms in the human visual cortex. Front. Hum. Neuro sci. 3:56.doi: 10.3389/neuro.09.056.2009 Fiez JA. (1997). Phonology, semantics, and the role of the left inferior prefrontal cortex. Human Brain Mapping, 5: 79e83.

Mechelli A, Crinion JT, Noppeney U, O’Doherty J, Ashburner J, Frackowiak RS, et al. (2004). Neurolinguistics: Structural plasticity in the bilingual brain. Nature, 431: 757.

Perani D and Abutalebi J. (2005). The neural basis of first and second language processing. Current Opinion in Neurobiology, 15: 202e206, 2005.

Perani D, Paulesu E, Galles NS, Dupoux E, Dehaene S, Bettinardi V, et al. (1998) The bilingual brain. Proficiency and age of acquisition of the second language. Brain, 121(Pt 10): 1841e1852.

Stein M, Dierks T, Brandeis D, Wirth M, Strik W, and Koenig T. (2006).

Plasticity in the adult language system: A longitudinal electrophysiological study on second language learning. NeuroImage, 33: 774e783, 20 Stein M, Federspiel A, Koenig T, Wirth M, Lehmann C, Wiest R, et al.

(2009). Reduced frontal activation with increasing 2nd language proficiency. Neuropsychologia, 47: 2712e2720.

Tatsuno Y and Sakai KL. (2005). Language-related activations in the left prefrontal regions are differentially modulated by age, proficiency, and task demands. Journal of Neuroscience, 25: 1637e1644.

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Neural mechanisms implicated in visual selective attention as indexed by eventrelated brain potentials Olivia Salthouse1 University of Auckland, Auckland, New Zealand 1142 Correspondence should be addressed to Olivia Salthouse (osal004@aucklanduni.ac.nz) 1

Introduction On a daily basis people are inundated with an immense diversity of visual information from which we select and attend to only a small selection (Hickey, Di Lollo & McDonald, 2009). For example, when looking for a particular car in a busy parking lot, we selectively attend only to cars that could possibly belong to us, whose features are relevant such as the same colour or model. However, cars that do not share the same features are deemed irrelevant and filtered out. The concept of â&#x20AC;&#x153;selective attentionâ&#x20AC;? therefore refers to the capacity by which we focus on critical aspects of our environment while disregarding those that are insignificant (Couperus & Mangun, 2010).

This selection of only a small amount of visual input is necessary because if everything in our visual fields were represented equally and simultaneously, it is likely that our visual system would present us with an incorrect representation of the true environment (Hilimire, Mounts, Parks, & Corballis, 2009). A similar line of thought likewise suggests that the visual system is limited in capacity, and hence only important, relevant stimuli can gain representation within the visual cortex (Hilimire, Mounts, Parks, & Corballis, 2011). Thus it has become clear that selective attention is incredibly important and adaptive.

Certain neural mechanisms must exist within the brain in order to assist selection of important objects from the environment while ignoring those that are irrelevant (Couperus & Mangun, 2010). Current research suggests that visual selective attention occurs through either the enhanced representation of attended stimuli or suppressed representation of irrelevant stimuli or a combination of the two mechanisms indicated (Daffner et al., 2012).

Enhancing neural mechanisms Much of the research in the field of visual selective attention has made use of event-related brain potentials (ERP) as a temporal measure of neural activity, which in turn corresponds to visual processing (Hillyard & AnilloVento, 1998). ERP waveforms can be divided into positive and negative components that indicate the polarity of voltage deflection and the time at which they are elic16 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

ited following stimulus onset (Hillyard & Anillo-Vento, 1998). The information gathered from these ERP waveforms has an incredibly high temporal resolution and thus provides researchers with a wealth of information regarding response times and the mechanisms involved in selective attention (Hillyard & Anillo-Vento, 1998). In terms of visual selective attention and stimulus enhancement, the N2pc and Nt components in particular, appear to be implicated (Eimer, 1996; Hickey et al., 2009; Hilimire et al., 2012). Research on N2pc and Nt has indicated N2pcâ&#x20AC;&#x2122;s role in the filtering of attention, while Nt has been suggested as a subcomponent of N2pc representing the processing of the target stimuli (Eimer, 1996; Hickey et al., 2009). Likewise, further research also indicated that P1 and N1 components play a role in enhancement, with P1 indexing initial processing and N1 further processing in more difficult contexts (Mangun & Hillyard, 1991).

Half of the argument regarding selective attention proposes that neural mechanisms enhance the representation of important target objects and thus lead us to attend to those objects. The theory behind enhancement posits that when presented with a visual scene containing numerous items, we attentionally select those which are more salient and important, and the representation of these objects is then enhanced resulting in continued processing of the object (Hilimire et al., 2011). In turn, the enhanced representation of the object in the visual cortex results in attention being focused on that object and hence representation in our visual environment (Hickey et al., 2009). Furthermore, as mentioned earlier, it is not adaptive or possible to process and attend to every object in a visual scene. As a result, irrelevant objects do not receive the same level of processing and hence are not represented in the visual cortex or environment (Hilimire et al., 2011). Although there is a lack of consistent evidence regarding which ERP components index enhancement mechanisms, there have nonetheless been numerous studies to suggest that such mechanisms do exist (Mangun & Hillyard, 1991).

The N2pc component is thought to be involved in attentional filtering, and evidence from extensive research has suggested its role in the enhancement of target stimuli

review (Hilimire et al., 2009). Eimer (1996) ran a study consisting of three experiments in which a selection of stimuli – either a lateral target and three distractors (experiment 1) or a lateral target and one distractor (experiments 2 and 3) – were presented for 150 milliseconds while participants watched a central fixation point. Experiments 1 and 2 contained targets that differed from distractors in terms of form (the letter ‘M’ or ‘W’ as targets and vertical bars as distractors) or colour (blue or green squares as targets, and yellow squares as distractors). Furthermore experiment 3 presented word pairs as stimuli (the German words ‘LINKS’ or ‘RECHTS’ as targets and ‘WEISS’ and ‘BRAUN’ as distractors), with the content of targets and non-targets being the differentiating factor. In all three experiments, participants were required to respond to the target by a button-press. Using EEG to record the data, Eimer (1996) found evidence of N2pc contralateral to the attended targets, over the three visual stimulus arrays. This data shows that regardless of the number of distractors present in the scene, the N2pc component still appears. However, in the word discrimination task, N2pc was confined to the left hemisphere. This result might be attributable to language domination of the left hemisphere. Subsequently, reducing distractor interference did not diminish or eliminate the N2pc component, further suggesting that N2pc indexes target enhancement (Eimer, 1996). In order to strengthen this N2pc target-facilitation finding, an effort needs to be made to explore the effect of placing target and distractor stimuli on differing feature dimensions (Eimer, 1996).

Further research into N2pc’s role in the processing of stimuli has bolstered support for Eimer’s (1996) findings.

Hickey et al. (2009) suggested that N2pc in played an important role in target selection processing. However, their research has shown evidence that the component may in fact be a summation of a separate positive and negative component, each representing a different mechanism. In this study, participants attended to two different stimuli – an isoluminant line and a bright square – as they flashed on the screen and were required to respond (via a computer mouse click) based on their form – whether the line was short or long and whether the square was oriented as a square or as a diamond. The line shared the same luminosity with the background to ensure equal luminance processing. The results showed that when participants attended to the line (the target) and ignored the square (the distractor), a negative component, Nt, was elicited showing a resemblance to N2pc in terms of polarity, latency, and relative location contralateral to the target. Following statistical analyses of the isolated component, a significant effect of electrode laterality for Nt was discovered (p>0.005).

On the basis of these findings, the study concluded that Nt component is linked to the target stimulus and indexes enhanced target processing. However, across the visual hemifields, Nt component eliciting was disproportionate

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– suggesting that sensory factors such as visual processing of differing displays and attentional processing might be involved as opposed to attentional processing target stimulus alone. Consistent with Hickey’s findings, Hilimire et al. (2012) used the same experimental paradigm and also concluded that Nt plays a role in the processing and enhancement of target stimuli. In addition, this replication found supporting evidence of N2pc as a summation of suppressing and enhancing mechanisms and likewise suggested that Nt is involved in attentional processing.

In contrast to the aforementioned studies which both suggest that enhancement of the attended stimuli is indexed by a negative component, the role of a positive component in indexing enhancement has also been demonstrated. Mangun and Hillyard (1991) performed a study to determine whether spatial priming of a target was related to the enhancement of processing. Following an attentional cue, participants responded to the height of the bars presented (choice) or to the target as soon as it appeared (simple). Results from both experiments showed that for validly cued stimuli, the positive component (P1) increased in amplitude contralateral to the attended target. In addition, validly cued trials in the choice experiment also elicited an enhanced negative component (N1). No N1 was present in the simple condition. When choice and simple conditions were incorporated into one experiment, results were consistent with those already collated. Based on these results, Mangun and Hillyard (1991) proposed that P1 indexes enhancement of sensory signals from the target stimuli and hence a possible visual pathway mechanism involved in regulating these sensory signals. In terms of the difference between the P1 and N1 components, previous literature suggests that N1 represents continued processing in more difficult discrimination tasks and therefore plays a role in continued enhancement (Mangun & Hillyard, 1991). Furthermore, such a hypothesis is consistent with results indicating that no N1 was elicited in the simple experiment, as further discrimination was not required (Mangun & Hillyard, 1991). However, there is still the possibility that N1 does indeed exist in the simple condition but is obscured by a series of overlapping components known as large positive deflection (LPD) (Mangun & Hillyard, 1991).

Couperus and Mangun (2010) similarly identified the P1 component as being involved in target enhancement and the N1 component as being involved in difficult tasks where further processing was required. Using a slightly different experimental paradigm, Couperus and Mangun (2010) showed two differing stimulus arrays – unilateral (target only) and bilateral (target and distractors) – to participants and asked them to respond whether the target was in the upper or lower half of the visual display.

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orientations) and low perceptual load condition (same as experiment one). As in Mangun and Hillyard (1991), both experiments found an increase in P1 amplitude contralateral to the target, reflecting target enhancement.

Subsequently in the high perceptual load task, increased processing as marked by N1 was discovered contralateral to the target – supporting Mangun and Hillyard’s (1991) hypothesis that the N1 indexes target enhancement and that further processing is required for more difficult tasks.

Steady-state visual evoked potentials (SSVEPs) have also been implicated in the enhancement of target stimuli (Müller et al., 1998). In contrast to measures using ERPs, which only allow transitory stimuli to be presented, SSVEPs enable continuous presentation of a stimulus and thus require participants to maintain attention over a particular period of time (Müller et al., 1998). To examine long-term attention, Müller et al. (1998) presented participants with bicolour vertical LED bars in either visual field, one flickering at 20.8 Hz and the other at 27.8 Hz. A cue to either side of the central fixation point indicated where to attend. Participants were also instructed to attend and respond to colour change, with an alteration in top and bottom LEDs constituting the target. Results of this study show that when the flicker was located in the attended field, there was a significant increase in the amplitude of SSVEP contralateral to the target. Differing frequencies were also proportionally similar. As a result, these findings suggest a mechanism that enhances the representation of the target (Müller et al., 1998). Müller et al. (1998) suggest that such enhancement occurs through extrastriate visual pathways, which are biased to environmental stimuli at the attended locations. As a result of this bias, these stimuli gain enhanced processing over those in the unattended locations.

Suppressing neural mechanisms While both negative and positive components have been implicated in the neural mechanisms that enhance the representation of selected stimuli, this is only half of the story of visual selective attention (Hilimire et al., 2012). In addition to enhancement, there is also much research and supporting evidence to suggest that neural mechanisms which suppress the representation of distractor stimuli are also at work either in conjunction with mechanisms of enhancement or alone (Couperus & Mangun, 2010). While the aforementioned research has found evidence of both negative and positive components implicated in enhancement, suppression seems to be more closely linked to positive ERP components (Hilimire et al., 2011; Hilimire et al., 2009; Couperus & Mangun, 2010).

Hilimire et al. (2011) found evidence of a bias signal in the form of a positive component, Ptc. They suggest that Ptc represents a mechanisms of distractor suppres18 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review sion necessary for the resolution of attention competition.

As a result, when participants are presented with visual input, those objects that are not important undergo suppression and do not gain representation in the visual cortex (Hilimire et al., 2011). In this study, participants were presented with a 16-letter display positioned around an imaginary circle. The target item was either an upright or inverted T, coloured orange or green, with the colour of the target opposite to that of the distractor. Participants were required to state the orientation of the target by a button press. An earlier experiment by Hilimire et al. (2009) used the same experimental procedure and also looked at Ptc in relation to the size of the separation between the target and the distractor. Hilimire et al. (2009) found that Ptc amplitude increased as target-distractor separation decreased, possibly suggesting that Ptc may be a marker of active suppression. As the target and distractor become closer to each other, competition increases. More active suppression of the distractor thus might be necessary to ensure representation of the target (Hilimire et al., 2009). Hilimire et al. (2011) similarly supported this initial finding by showing that only the presence of the distractor showed evidence of Ptc, suggesting that Ptc might be specifically linked to a neural mechanism involving distractor suppression following target identification.

Pd is also very similar to Ptc (Hilimire et al., 2009). Hilimire et al., (2009) suggested that Ptc might be a delayed Pd component, while Hickey et al. (2009) suggested that Ptc may form a part of N2pc in combination with Nt. Hickey et al. (2009) ran a study to examine this possibility, hypothesizing that Pd plays a role in locating and processing irrelevant objects and then directly suppressing any representation of these objects in the visual cortex. As stated earlier, participants attended to a line – determining its length or its orientation (square or diamond). When the distractor was presented laterally, there was an increase in the amplitude of Pd, providing evidence in support of distractor processing and suppression. When less attention was required using a simple detection task, Pd was no longer observed. These results further validate the claim that Pd indexes distractor processing (Hickey et al., 2009) and show that location of the distractor in the visual environment leads to variations in the Pd component. Hilimire et al. (2012) used the same procedure and included a distractor only condition. When the green shape was presented as the distractor at the same time as the target (line), positivity increased in amplitude in the hemisphere contralateral to the distractor. Likewise, Pd was only evident when the target and distractor were presented together (Hilimire et al., 2012) – suggesting that these results are consistent with those of Hickey et al. (2009).

Neural mechanisms and overall selective attention While a number of ERP components enhance representations of targets and others suppress representations of distractors, these processes do not act alone (Couperus &

review Mangun, 2010). Hickey et al. (2009) studied the N2pc component and found that N2pc most likely represents both of these processes through the Pd and Nt components, which summate to give the overall N2pc. While both Pd and Nt have been discussed earlier in terms of their isolated roles of suppression and enhancement respectively, considering them together as they contribute to efficient visual selective attention is important, not only in visual search paradigms but in our everyday lives (Hickey et al., 2009). As Hickey et al. (2009) suggest, when we are presented with a relevant and irrelevant object in our visual environment, Pd locates and processes irrelevant objects and suppresses them while the Nt locates and processes relevant object and enhances them.

Hilimire et al. (2011) also suggest that a number of components are implemented in the overall process of visual selective attention. According to them, N2pc indicates the initial processing of both the target and distractor and is followed by Ptc reflecting active suppression of the distractor. On the other hand, SPCN indexes further target processing that facilitates target representation in short-term visual memory. Visual selective attention clearly requires a number of processes to successfully select what is relevant in our environment. As a result, we cannot consider individual components to reflect the processes of selective attention (Couperus & Mangun, 2010).

Limitations of selective attention studies These studies provide evidence for neural mechanisms of enhancement and suppression and have helped to further our understanding of the processes that underlie visual selective attention. However, there are limitations to the evidence provided thus far, and there is still a lot to learn in order to gain a full understanding of the processes involved in selective attention (Couperus & Mangun, 2010).

Firstly, despite the very similar visual paradigms used in these experiments, there is still not complete consistency or agreement in the findings. Hilimire et al. (2009, 2011, 2012) and Hickey et al. (2009) all endeavoured to investigate the role of neural mechanisms that suppress the representation of distractors. While all found evidence of a positive component that indexed such a mechanism, Hilimire et al. (2009, 2011) suggested a Ptc component while Hickey et al. (2009) and Hilimire et al. (2012) suggested a Pd component. Although it has been argued that Ptc and Pd may reflect the same component, differing onset times and scalp distributions – Ptc located temporally and Pd parietally (Hilimire et al., 2009) – suggest otherwise.

A similar argument can be made of components that index enhancement. Eimer (1996) and Hickey et al.

(2009) both found evidence of the N2pc component.

While Eimer suggested that N2pc indexed enhancement however, Hickey et al. indicated that N2pc might actually be the summation of two components, with Nt re-

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sponsible for enhancement and Ptc responsible for suppression. Furthermore, Mangun and Hillyard (1991) and Couperus and Mangun (2010) found evidence for two completely different components – P1 and N1. Such a lack of consistency across different studies limits our understanding of mechanisms involved in visual attention.

Finally, many of these studies also examine mechanisms in isolation (Daffner et al., 2012), selecting only one component to focus on while paying little attention to others (Hilimire et al., 2012). For example, Hilimire et al. (2012) focused on the Pd component. While this study does reference N2pc’s role as summating positive and negative components (Pd and Nt), a full account of Nt’s importance in regulating selective attention remains uncharacterized. As a result, while these studies have provided crucial evidence for the processes of visual selective attention, there are limitations that need to be taken into account when explaining these processes.

Conclusion Over the past two decades, much research has been done in this domain and has given us a clearer picture of the neural mechanisms underlying the processes of visual selective attention. One such mechanism that has been proposed is that of enhancement, whereby important objects in the visual environment gain enhanced representation in our visual cortex (Hilimire et al., 2011).

In terms of this enhancing mechanism, a number of components have been implicated – namely the N2pc, Nt, P1 and N1 components – while SSVEPs have also evidenced enhancement (Couperus & Mangun, 2010; Eimer, 1996; Hickey et al., 2009; Mangun & Hillyard, 1991; Müller et al., 1998). While there appears to be some overlap of these, they nonetheless have provided us with evidence for an enhancing mechanism in selective attention. A mechanism of suppression has also been evidenced in the research (Couperus & Mangun, 2010).

The suppressing mechanism is thought to act on objects in the visual environment which are unimportant and thus do not need to gain representation in the visual cortex (Couperus & Mangun, 2010). Components that are thought to index this mechanism are Ptc and Pd (Hickey et al., 2009; Hilimire et al. 2009; 2011; 2012). Again there appears to be a great degree of overlap between the two components. However, we cannot discount a suppressing mechanism when considering selective attention (Hilimire et al., 2009). As evidence for both mechanisms has been consistently found, both mechanisms appear to play a complementary role rather than working in isolation (Couperus & Mangun, 2010). Inclusion of both mechanisms in a model of selective attention seems most likely, as research has suggested the presence of both enhancing and suppressing components (Hickey et al., 2009).

While studies discussed here have all been confined to Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 19

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laboratory settings, they nonetheless have implications for the everyday lives of people. As mentioned earlier, people are confronted with an overwhelming amount of visual information imbedded in a number of visual environments everyday (Hickey et al., 2009). However, as it is necessary for us to make sense of our world, and to do so efficiently, it is impossible to attend to every aspect of an environment (Hickey et al., 2009). It is therefore adaptive for important objects to be enhanced and attended to and unimportant objects to be suppressed.

Irrelevant information is unnecessary and paying attention to that information may mean we miss out on crucial information, as the visual processing pathways of the brain become overloaded and lose efficiency (Hilimire et al., 2011). By suppressing unimportant information, we are ensuring that only what is relevant is processed and represented in our visual cortex (Hilimire et al., 2011). Nevertheless, it is important to understand that enhancement and suppression do occur and that not all aspects of a visual scene are necessarily attended to. For example, in eyewitness accounts of crimes or other events where an account of what has happened is important, it is crucial for those listening to/taking the account to realize that unconsciously, some details may not have been deemed to be important, and therefore may have been suppressed and left out of the account all together. In such a situation the person giving the account might not even be aware that certain details even occurred. Understanding these mechanisms and how they work is thus important not only from a laboratory standpoint but also from real-life problems.

Although there is still a large amount of debate surrounding this issue, the current research has provided a good foundation from which continued research can build on and thus attempt to clarify the exact processes underlying selective attention. Instead of considering each component in isolation, research which looks at the bigger picture and considers all components and where they fit in relation to each other would be very beneficial. Future research of this nature could lead to greater consistencies in the literature and determine why differing components are sometimes found, despite similar experimental paradigms. Furthermore a greater focus on both enhancement and suppression processes together might elucidate this debate by establishing the extent to which each process contributes to attention.

It would be advantageous to have a better understanding of the roles of each mechanism – whether these components are equal or operating simultaneously or sequentially. Nonetheless it is apparent that efficient visual selective attention relies on both mechanisms of enhancement and suppression. Future research along these lines will result in a greater understanding of the mechanisms involved in selective attention.

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review Couperus, J.W., & Mangun, G.R. (2010). Signal enhancement and suppression during visual-spatial selective attention. Brain Research, 1359, 155-177.

Daffner, K.R., Zhuravleva, T.Y., Sun, X., Tarbi, E.C., Haring, A.E., Rentz, D.M., & Holcomb, P.J. (2012). Does modulation of selective attention to features reflect enhancement or suppression of neural activity? Biological Psychology, 89(2), 398-407.

Eimer, M. (1996). The N2pc component as an indicator of attentional selectivity. Electroencephalography and Clinical Neurophysiology, 99(3), 225-234.

Hickey, C., Di Lollo, V., & McDonald, J.J. (2009). Electrophysiological indices of target and distractor processing in the visual search. Journal of Cognitive Neuroscience, 21(4), 760-775.

Hilimire, M.R., Hickey, C., & Corballis, P.M. (2012). Target resolution in visual search involves direct suppression of distractors: Evidence from electrophysiology. Psychophysiology, 49(4), 504-509.

Hilimire, M.R., Mounts, J.R.W., Parks, N.A., & Corballis, P.M. (2009). Competitive interaction degrades target selection: An ERP study. Psychophysiology, 46(5), 1080-1089.

Hilimire, M.R., Mounts, J.R.W., Parks, N.A., & Corballis, P.M. (2011). Dynamics of target and distractor processing in visual search: Evidence from event-related brain potentials. Neuroscience Letters, 495(3), 196-200.

Hillyard, S.A., & Anillo-Vento, L. (1998). Event-related brain potentials in the study of visual selective attention. Proceedings of the National Academy of Sciences of the United States of America, 95(3), 781-787.

Mangun, G.R., & Hillyard, S.A. (1991). Modulations of sensory-evoked brain potentials indicate changes in perceptual processing during visual-spatial priming. Journal of Experimental Psychology, 17(4), 1057-1074.

Müller, M.M., Picton, T.W., Valdes-Sosa, P., Riera, J., Teder-Sälejärvi, W.A. , & Hillyard, S.A. (1998). Effects of spatial selective attention on the steadystate visual evoked potential in the 20-28 Hz range. Cognitive Brain Research, 6(4), 249-261.

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Electrophysiological evidence for a suppressive mechanism to the debate over selective attention Kyle Rand1 Duke University, Durham, NC 27708 Correspondence should be addressed to Kyle Rand (kyle.rand@duke.edu) 1

Selective attention, the ability to mentally devote attention to a small number of the stimuli in oneâ&#x20AC;&#x2122;s environment, is a well-recognized concept in the study of cognitive neuroscience. At any point in time, the human retina registers thousands of aspects of every part of oneâ&#x20AC;&#x2122;s visual field, yet cognitive functions enforce the processing of just a specific, small subset of these. While many studies have demonstrated the competence of selective attention as a cognitive process, the scientific community has yet to find any conclusive evidence as to the nature of this process; some argue for an enhancement of signaling of salient signals, while others argue for an actively suppressive mechanism that diverts processing from less salient signals. While research can be used to support both sides of this debate, recent evidence supports the existence of an active suppressive mechanism in the top down processing of sensory stimuli.

There is a duality between bottom-up and top-down processing that must occur in order for the brain to effectively handle such a large quantity of inputs (Ansorge et al., 2011). The mechanism of bottom-up processing is defined by a simple registration and classification of all stimuli in the sensory receptive field. Following this sensory registration, top-down processes must occur to determine the relative salience of each signal. All forms of goal-directed action and functional thinking rely on the ability of the brain to narrow down the amount of information that must be fully processed, so as not to exhaust energetic resources by processing irrelevant information.

This forms the basis of selective attention; there is a welldistinguished mechanism in the brain that is responsible for the differential handling of stimuli based on relative salience (Ansorge et al., 2011). Those who suggest that selective attention is a product of specific enhanced signaling believe that every given stimulus has some cortical representation, but one stimulus will cause heightened activation that is far greater than each other stimuli. This stimulus has such comparatively high representation in the cortex that all other stimuli will be disregarded during cognitive processes.

This argument for enhancement of salient stimuli largely differs from its counterpart in an electrophysiologi-

cal sense. In arguing for selective attention based on enhanced signaling, one is making the critical statement that every stimuli will produce an evoked brain potential, but the brain will only process the potential that is greatest in magnitude (most salient). The key difference between this argument and that of an active suppression mechanism is that the argument for enhancement implies that all other evoked signals are left unhandled by cognitive processes.

By supporting an active suppressive mechanism instead, there is an assertion that the brain must be manipulating the less salient stimuli in some way, rather than just ignoring them and focusing exclusively on the most salient stimuli. This foundational difference in reason provides a clear distinction between arguments: is there a process that attends to the signal that has been enhanced, or is there a process that attends to the signal of highest salience and then suppresses all others?

Much current research on selective attention involves the use of electroencephalography to obtain a topographical and temporal organization of cognitive processes. This technique allows researchers to measure brain potentials over time, and determine how they change in response to stimuli (Lalor et al., 2010). A successful electroencephalogram displays the voltage versus time of potentials at each measuring electrode distributed along the scalp, enabling neuroscientists to evaluate the electrical firing of brain signals across all regions of the brain. Once these voltage readings are standardized, event-related potentials are readily distinguishable and can be evaluated against the time-course of stimuli presentation, making EEG quite useful for selective attention tasks.

The relationship between spatial proximity of stimuli and competitive representation has been well defined over the past few years. In 2009, Hilimire and colleagues designed a visual search study based on the concept of localized attentional interference, and compared the event related potentials (ERPs) between trials. They were able to do this by utilizing the localized attentional interference paradigm, a widely used selective attention task that involves the simultaneous presentation of a target stimulus, distractor stimulus, and space-filling stimuli arranged in a circular position at a set radius from a fixation point Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 21

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(Hilimire et al., 2009). The participant is instructed to quickly locate the position of the target across a series of trials, with each trial categorized by the proximity of the target to the distractor. Based on the theoretical receptive field of neurons in the visual cortex, the distractor is either placed fully in the receptive field surrounding the target, partially overlapping, or completely outside of the receptive field of the target, and comparisons can be made in ERPs across trials. In their study, Hilimire and colleagues categorized trial type based on spatial proximity between target and distractor, and formulated their analysis on the inverse relationship between target-distractor separation and competitive interaction. Using electroencephalography, they recorded evoked potentials to determine how competitive interaction caused changes in the response of the extrastriate cortex.

Their measure of target selection relied on measuring the peak amplitude of the N2pc neural component, a peak that has been shown to occur during attentional tasks (Hilimire et al., 2009). Through testing of an orientationdiscrimination task, they were able to confirm that the N2pc component of the ERP was correlated with localized attentional interference; when attention to target was being increasingly interfered by a close-proximity distractor, the amplitude of the N2pc decreased (Hilimire et al., 2009). This is due to the fact that the N2pc component can be attributed to target selection, and as competition for extrastriate representation increased as the target-decoy separation decreased, the strength of target selection also decreased. This attenuation of N2pc amplitude corresponded with a decrease in accuracy of behavioral response (i.e. decreased ability to correctly locate the target) when the spatial difference between target and decoy separation decreased (Hilimire et al., 2009). This clearly demonstrates the neural connection between selective attention and the N2pc neural component, and has paved the path for continued research as to the explanation for differential representation of stimuli in the extrastriate cortex.

Following their 2009 publication, Hilimire and colleagues continued to identify the neural correlates of selective attention. In their original study, they analyzed the evoked potentials during the orientation-discrimination task by comparing difference waveforms across trials, and were able to clarify the existence of another neural component present: the Ptc, occurring for approximately 50 milliseconds, beginning around 290 milliseconds poststimulus (Hilimire et al., 2010). Unlike the N2pc, which is attenuated as target-decoy separation decreased, the Ptc was shown to increase in amplitude as target-decoy separation increased (Hilimire et al., 2010). In order to evaluate the neural significance of the Ptc, a second study was conducted using the visual search paradigm, and were able to determine that the different time courses of the N2pc and Ptc, along with the different localization of each component, represent separate components of attentional selection (Hilimire et al., 2010). This subsequent study searched to evaluate the nature of the Ptc component and 22 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

OpiniOn define it in a way that would allow for comparison between N2pc and Ptc. Since the N2pc is related to selective attention, understanding the nature of the N2pc is critical in determining its role in processing. The visual search paradigm currently used involves the visual processing of salient stimuli, and causes the generation of an ERP with a larger potential contralateral to the stimulus location in the visual field. Due to the organization of the human visual cortex, the N2pc neural component is much stronger on the contralateral side compared to the ipsilateral side, so each ipsilateral waveform was subtracted from the corresponding contralateral waveform in order to more clearly compare neural representations of ERPs (a process called contralateral control) (Hilimire et al., 2011). This calculated difference wave is used for analysis to compare visual ERPâ&#x20AC;&#x2122;s to baseline. The increased negativity produced in the contralateral cortex is temporally followed by a positivity in the same area, suggesting two neural components correlated to selective attention mechanisms. To decipher between them, Hilimire and colleagues altered the paradigm by placing either the target or the distractor on the midline for each trial. Since one relevant stimulus is on the midline (i.e. is not lateralized) there will be equal representation between the contralateral side and the ipsilateral side, essentially forcing the difference wave to zero (Hilimire et al., 2011). In doing this, Hilimire and colleagues were able to determine the difference between the N2pc and Ptc components of an ERP. When the target is on the midline and only the distractor is lateralized, the ERP still contains a noticeable N2pc component, reassuring that the N2pc is based on directing attention to salient stimuli. Similarly, when the target is on the midline and only the distractor is lateralized, a contralateral positivity is produced (Ptc). However, when the distractor is on the midline and only the distractor is lateralized, no similar Ptc response is evident in the difference waveform (Hilimire et al., 2011). This suggests that the N2pc is, in fact, relevant to attentional selection, as it is always produced despite lateralization conditions. The Ptc, on the other hand, only responds to lateralized distractors, and does not respond to target stimuli, as there is no statistically significant difference in the evoked potential contralateral to the target when compared to the ipsilateral side (Hilimire et al., 2011). This implies that the presence of the Ptc component is dependent on the distracting stimuli, and therefore shows that there is some neural mechanism acting on the distracting stimuli that is not acting on the salient stimuli.

The evidence of a neural mechanism acting exclusively on non-salient stimuli has significant implications for the understanding of the cognitive basis of selective attention. The N2pc signal can be confidently attributed to the mechanism of determining behaviorally relevant stimuli, and is always activated contralateral to either relevant stimulus (i.e. the distractor or the target) (Hilimire et al., 2009). However, the discovery of a neural component

OpiniOn that correlates with salient determination is a relevant finding for both sides of the debate surrounding selective attention. The N2pc component neither favored a mechanism for the enhancement of salient signals nor the suppression of non-salient signals, but rather affirmed the presence of a neural mechanism related to selective attention of salient stimuli. Instead, the discovery of the Ptc, and thereafter defining of its behavior, adds an entirely fresh perspective to the debate. Since the Ptc is exclusively evoked due to distracting stimulus, it demonstrates that there is a neural mechanism that acts on distracting stimulus. Furthermore, the Ptc peaks nearly one hundred milliseconds after the N2pc, meaning that it peaks after another neural mechanism has already determined behaviorally relevant stimuli (Hilimire et al, 2009). Since it peaks after this distinction during the N2pc, the Ptc may act to affect the relative salience of the behaviorally relevant stimuli that have been identified. This corresponds with the previously found Pd component of ERP during visual search tasks, however more conclusively occurs after the N2pc component.

Although both the target and distractor are initially attended to directly following presentation during the visual search paradigm, the Ptc component is a correlate of a neural mechanism affecting the distractor, rather than the target. This gives strong evidence for the suppression of distracting stimuli in the course of selective attention, as the existence of a neural correlate that acts on non-salient stimuli cannot logically support the enhancement of a salient target. This does not, however, disprove the existence of a simultaneous mechanism that enhances neural representation of salient stimuli, but rather provides quite tangible evidence for a neural mechanism that suppresses non-salient stimuli in the interest of attending to the most salient stimulus.

The complexity of the visual system could provide many potential purposes for the Ptc component during the visual search paradigm. The finding that Ptc only acts on nontarget stimuli definitely supports the existence of a neural mechanism of suppression. However, the broadness of the visual field complicates the definition of suppression as it is understood in the selective attention debate. The Ptc may be responsible for completely diverting attention away from an unattended signal post-identification, or may imply that processing of this signal then produced a reaction that labeled the stimulus as non-salient, without actually suppressing its neural representation. As the retina scans the visual field, it may be useful to have a mechanism that processes relevant stimuli in a top-down process and labels them as unimportant so that the brain will not attempt to process them again; perhaps the Ptc is simply a labeling process (Hilimire et al, 2012). The actual function of this Ptc component can be better understood by looking across the sensory systems to interpret how the brain processes non-target stimuli in other sensory pathways.

Studies looking into unattended stimuli that have a high level of sensory involvement may help describe how

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this Ptc component actually functions on unattended stimuli. In one such study, Power and colleagues applied similar methods to the debate surrounding selective attention in the auditory system (2012). Using a dichotic listening paradigm, they successfully compared participantsâ&#x20AC;&#x2122; understanding of target speech versus non-target speech streams. After simultaneously playing different hearing segments to the participants, one in each ear, they asked various questions about each passage, finding participants to have a vastly larger success rate in answering questions related to the attended story (Power et al., 2012). EEG analysis ran throughout the paradigm shows the existence of a similar suppressive neural mechanism as previously described in visual processing; they found clear activation in the left temporal lobe to both attended and unattended stories, via Auditory Evoked Spread Spectrum Analysis and the convolution integral applied to the time-variant auditory signal (Lalor et al., 2009). This method allows researchers to describe auditory processing across a wide spectrum of input (e.g. in the form of natural speech streams),and has been used to demonstrate cortical response to different auditory inputs (Lalor et al., 2010).

Usually, a Pd component is present in auditory ERPs that is responsible for the non-selective processing of speech.

This Pd component has been shown to be elicited over a wide range of auditory inputs, and as of now is signified as a neural correlate to impulse processing (Lalor et al., 2010).

However, the dichotic speech task presently used demonstrates a total degradation of the usual Pd component of the unattended speech pathway (Power et al., 2012). This is a crucial finding to the debate over selective attention as it clearly defines a prolonged absence of processing of an unattended stimulus. The lack of this Pd component for unattended stimuli demonstrates the suppression of the non-target auditory signal, and the prolonged inattention despite the continuous-impulse nature of auditory signals (Lalor et al., 2009). This demonstrates the long-lasting effect of the mechanism temporally acting on unattended stimuli in a way that is not yet conclusive in the visual cortex Though the results of these two research paradigms depend on separate processing pathways, there is a distinctive interconnection with strong influences on the current debate in selective attention. The largest potential controversy with the findings of the Ptc in the visual cortex is that the paradigm currently used cannot effectively describe the component as a suppressing mechanism, because there is no way to prove behaviorally that the distractor has in fact been suppressed from sensory engagement. The paradigm has conclusively shown the existence of a neural mechanism that acts directly on non-target stimuli, but utilizes no continued task to prove that the non-target stimuli is permanently suppressed from further or repeated processing. Power and colleagueâ&#x20AC;&#x2122;s auditory task, however, provides concrete evidence for the effect of a mechanism to effectively suppress non-target stimuli and maintain that level of suppression despite a maintained level of impulse Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 23

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sensory inputs. Through Hilimire and colleaguesâ&#x20AC;&#x2122; analysis of electrophysiological responses to visual stimuli, a mechanism was defined that clearly acted upon unattended stimuli in the visual processing pathway (2011). Through Power and colleaguesâ&#x20AC;&#x2122; analysis of electrophysiological responses to auditory stimuli, a modality was defined that clearly suppressed even basic levels of auditory processing of unattended stimuli (2012). The concurrent conceptualization of these two different findings strongly supports the existence of a suppressive mechanism during selective attention processes. Based on this interconnection, the integration of the two paradigms could provide the key to tracing the prolonged effect of the Ptc component identified in the visual system, and providing a conclusive answer as to the nature of the mechanism of suppression.

To further assess this debate, research must focus on providing stronger evidence for the role of neural correlates to the suppression of unattended stimuli. Selective attention tasks need to be modified to incorporate methods of determining the prolonged effects of the Ptc component on the visual field to affirm its role in the proposed suppression mechanism. In addition, further research into the temporal localization of the Ptc component will strengthen understanding of its role in the overall process of selective attention. A conclusively defined neural correlate to the method of selective attention would provide key comparisons in cortical activity for further study of neurodegenerative disorders such as attention deficit disorder and schizophrenia. By defining the usual mechanism that controls selective attention, we may identify the difference in brain patterns surrounding such disorders, and provide a better means of understanding and prognosis of patients.

Ansorge, U., Kiss, M., Worschech, F., & Eimer, M. (2011). The initial stage of visual selection is controlled by top-down task set: new erp evidence.

Attention Perception Psychophysics, 73, 113-122.

Hilimire, M. R., Hickey, C., Corballis, P. M. Target resolution in visual search involves the direct suppression of distractors: evidence from electrophysiology. Psychophysiology, 49(4), 504-9.

Hilimire, M. R., Mounts, J. R. W., Parks, N. A., & Corballis, P. M. (2009).

Competitive interaction degrades target selection: An erp study. Psychophysiology, 46, 1080-1089.

Hilimire, M. R., Mounts, J. R. W., Parks, N. A., & Corballis, P. M. (2011).

Dynamics of target and distractor processing in visual search: Evidence from event-related brain potentials. Neuroscience Letters, 495(3), 196200.

Lalor, E. C., & Foxe, J. J. (2010). Neural responses to uninterrupted natural speech can be extracted with precise temporal resolution. European Journal of Neuroscience, 31, 189-193.

Lalor, E. C., Power, A. J., Reilly, R. B., & Foxe, J. J. (2009). Resolving precise temporal processing properties of the auditory system using continuous stimuli. J Neurophysiol, 102, 349-359.

Mounts, J. R. W. (2000). Evidence for suppressive mechanisms in attentional selection: Feature singletons produce inhibitory surrounds. Perception & Psychophysics, 62(5), 969-983.

Power, A. J., Foxe, J. J., Forde, E., Reilly, R. B., & Lalor, E. C. (2012). At what time is the cocktail party? a late locus of selective attention to natural speech. European Journal of Neuroscience, 35(9), 1497-1503.

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Pupillary response to reward and loss: A comparison between adults and adolescents Jamie Stark and Youngbin Kwak1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Jamie Stark (jamie.stark@duke.edu) 1

Introduction Risky behavior is a manifestation of the changes that occur during the turbulent years of adolescence. This is supported by a 200% increase in the mortality rate among adolescents despite their being stronger, faster, more resistant to disease, and more cognitively advanced than children (Dahl, 2001). In the United States, 71% of deaths among people ranging between 10-24 years of age were caused by motor vehicle accidents, homicide, suicide, and other traumatic injuries. Furthermore, the leading causes of mortality among adolescents are the result of behaviors that increase the likelihood of unintentional injuries through violence, tobacco use, drug and alcohol abuse, and unprotected sexual behavior resulting in sexually transmitted disease and unwanted pregnancy (Eaton et al. 2006).

Such adolescent risk taking has obvious economic, psychological, and health implications including unnecessary property and infrastructure damage, general impairment upon societal morale, and a serious toll on the health care system and its costs (Maynard 1997). Additionally, habits initiated during this transformative period of life often continue into adulthood, further compounding the negative impact upon society of poor decisions made during adolescence (Reyna and Farley 2006).

My first objective is to review the literature that investigates risky decision-making during adolescent development. In doing so, I will examine the neurobiological differences between adults and adolescents and how these dissimilarities cause behavioral differences. Second, I will propose a research study which investigates how a physiological measure, pupillometry, can signal and highlight the characteristics of adolescent decision making. In so doing, I will assess the viability of pupillometry as a measure of brain activity and describe how this particular method of measurement can be applied to decision-making paradigms. Then, I will evaluate the limited amount of research that has been performed on adolescents using pupillometry. Finally, I will describe the paradigm used in the proposed study and explain how the study will contribute relevant information and data to the field of adolescent decision- making.

Risky decision making across development Adolescents, much like adults, generally exhibit an optimistic bias during their decision-making processes that often results in risky behavior (Reyna and Farley 2006).

Yet, there must exist other differences in the adolescent decision-making process that account for the groupâ&#x20AC;&#x2122;s sharp increase in risky behavior. A wide spectrum of studies has been performed to explain these changes in risk preference during development and across a series of ages.

Two classes of hypotheses have emerged from the conclusions of these studies (Paulsen et al. 2012). The first class of hypotheses suggests that adolescents are less capable of incorporating prior negative experience into their decision-making process and exhibit a desensitization to loss (Paulsen et al. 2012). When compared with adults during a feedback-based learning task, children have performed poorly at disproportionate levels when receiving negative feedback as opposed to positive feedback (van Duijvenvoorde et al. 2008). Imaging data from this study also showed reduced activation of the dorsolateral prefrontal cortex in children relative to adults following negative feedback, but a higher level of activation following positive feedback. These findings are significant because other imaging studies have reported associations between fMRIbased regional volumes of prefrontal cortex and measures of cognitive control in the decision-making process. This reduced activity shown in van Duijvenvoorde et al.â&#x20AC;&#x2122;s study suggests that children are less capable of executive cognitive functions after receiving negative feedback (Casey et al. 1997), which may lead to continuing suboptimal decision-making. Similarly, another study reported a desensitized reaction to loss in adolescents, supported by the significantly lower activation of the amygdala in response to reward omission (Ernst et al. 2005). This response may reflect a reduction in dopaminergic activity and, therefore, decreased emotional salience in response to omission of the reward or a reward that was smaller than expected.

It has also been demonstrated that although adolescents understand the consequences a particular decision holds based on previous experience, they underestimate the severity of the long-term consequences or simply believe that the negative outcome is far more likely to occur to somebody else (Reyna and Farley 2006). This set of hypotheses suggests that adolescents do not consider themselves invincible. Instead, they just have a reduced capacity to incorporate what they know from their prior adverse experiences into their decision-making process.

The second set of hypotheses posits that adolescents have greater sensitivity to rewards and an immature executive control process that results in risk-seeking behavVol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 25

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ior (Paulsen et al. 2012). When compared side-by-side, benefits weigh more heavily than risks from an adolescent’s perspective. A neuroimaging study demonstrated that, relative to adults, adolescents have greater activation of the nucleus accumbens and amygdala in response to reward receipt (Ernst et al. 2005). The nucleus accumbens has been linked to risk-seeking behavior in previous studies (Kuhnen & Knutson 2005). Another study also found that adolescents displayed an exaggerated response in anticipation of reward when compared to children and adults, despite a linear increase in prefrontal activity from children to adults (Galvan et al. 2006). These results indicate that in an adolescent’s brain, rewards are processed with greater emotional sensitivity, but decreased regulatory function from higher-level executive control regions.

Novelty seeking, a potential mechanism for experiencing reward, is common across adolescents in several mammalian species, suggesting that it is an evolutionary mechanism, possibly to facilitate separation from family in order to become more independent and, ultimately, find mates (Spear 2000). Regardless of purpose, this elevated desire for reward comes with negative consequences such as drug use and other forms of artificial stimulation (Spear 2000).

This set of hypotheses supports the more typical stance on adolescents that view them as pleasure seeking individuals, as asserted in a study on adolescent response to reward (Cohen et al. 2010).

A comprehensive review of adolescent rewardseeking behavior has attempted to integrate all of these findings to produce a neurobiological model of decision making in adolescence that explains how “neural changes in subcortical regions (e.g. accumbens and amygdala) associated with reward-seeking and emotion coincide with development of the prefrontal regions” (Casey et al. 2010).

Ultimately, the model suggests that the combination of heightened perception of rewards due to increasing development of sub-cortical areas of the brain (amygdala and nucleus accumbens) and inability to control behavior due to lack of development in prefrontal regions of the brain causes adolescents to seek immediate reward instead of long-term gain, often by means of risky decision making (Casey et al. 2010). This encompassing theory incorpororates both an emotional and a cognitive component that provides an explanation to both classes of hypotheses described.

Pupillometry as an index of brain activity Pupillary measurement is another method, apart from fMRI, by which researchers can assess brain activity in humans. Pupillometry is a viable measurement of brain activity because it is minimally invasive and requires machinery that is less expensive and complicated than fMRI. Pupil size as an index of brain activity was largely introduced by a study done by Michael Ross in 1986 showing that the underlying mechanism for the change in pupil size was activation of an inhibiting neural pathway through release of norepinephrine (NE) onto the Eding26 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review er-Westphal nucleus, which innervates the iris contraction muscles (Ross 1986; Yoshitomi 1985). This entire pathway has not been completely analyzed and understood but one theory suggests that it begins in the locus coeruleus (LC) of the pons, one of the primary suppliers of NE to the brain (Levitt and Moore 1975). From there, the NE has several downstream targets that profoundly influence how the brain allocates attention and determines which stimuli to select, store, and retrieve information for generating adaptive behavior (Sara 2009).

There is direct evidence supporting the role of pupillometry as a measure of the activity in LC. Utilizing a single unit recording, one study found that pupil diameter varies with the mode of firing in the LC such that a larger diameter corresponds to tonic firing and a smaller LC corresponds to phasic activity (Rajkowski 1993). The adaptive gain theory developed and proposed by AstonJones and Cohen provided a functional explanation for these observations. Their theory stated that phasic LC activation facilitates optimal task performance (exploitation) while tonic firing facilitates task disengagement and search for alternative behaviors (exploration) (AstonJones and Cohen 2005). This explanation for the correlation between pupil dilation and brain activity provided a behavioral connection to pupil dilation that could be measured and tested in future experiments.

Today, the eye-tracking paradigm is applied in a wide variety of research fields and is used as a way to describe arousal, cognitive load, and even risk prediction and response. A recent study utilized pupillometry to analyze the adaptive regulation of the balance between exploration and exploitation that is necessary for the optimization of behavioral performance ( Jepma and Nieuwenhuis 2011).

The results imply that pupil diameter correlates closely with control state and confirmed that the LC-NE system plays an integral role in the regulation of the explorationexploitation trade-off. Furthermore, they also found that pupil diameters could be predictive of the type of decision made and that individual differences in baseline pupil diameters were predictive of an individual’s behavioral tendencies ( Jepma and Nieuwenhuis 2011). The data revealed that exploratory choices were preceded by a larger baseline pupil diameter than exploitative choices. This is consistent with previous findings that indicate that tonic firing of the LC, which is associated with exploratory behavior, corresponds to increased pupillary diameter (Aston-Jones and Cohen 2005). Other predictive capabilities were seen in the relationship between an individual’s baseline pupil diameter and their tendency to explore.

Eye-tracking results confirmed that larger baseline pupil diameter predicted more exploratory behavior. This supports the hypotheses set forth by the adaptive gain theory and illustrates the value of pupillometry as an index for brain activity ( Jepma and Nieuwenhuis 2011). They also confirm the conclusions of another similar study by Gilzenrat et al. which found that pupil diameter closely correlates with control state of the LC, and specifically that

review increases in diameter are associated with the exploration control state and decreases in diameter are associated with task engagement (Gilzenrat et al. 2010). These two studies are crucial to the foundation of the current study because they show that pupil diameter is not only a valid way of assessing the inner mental state of study participants, but is also a tool that can be used to make predictions about a subject’s decision-making tendencies.

Pupillometry has also proven useful when assessing the subjects’ mental states during reward seeking and decision making behavior. One study investigated the relationship between pupil dilation and errors in “judging uncertainty” following a decision, which they described as surprise (Preuschoff et al. 2011). Their hypothesis was that this error in predicting the outcome of their decision would be reflected by changes in pupil size. This notion was based on prior research by Preuschoff that concluded that the dopaminergic system of the brain differentially signals between reward expectation and risk prediction (Preuschoff et al. 2006; Preuschoff 2007). Their approach was novel in that they dissociated reward, a heavily investigated topic, from the less understood concept of uncertainty in their auditory gambling task. It demonstrated that pupil dilation does not signal expected reward or uncertainty, but error in predicting the uncertainty (Preuschoff et al. 2011).

The observations confirm that pupillometry can be used as a measure of reward response and reaction. Based on the findings of these previous studies, we can confidently assert that pupillometry is a viable, yet less explored, method of measuring reward sensitivity and decision making behavior, especially with regards to the adolescent age group.

Pupillometry in adolescence Very limited amounts of research utilizing the pupillometry method have been applied to adolescents. These following are three of the few studies that used pupillometry in adolescents and provide a basis for the hypotheses of the current study.

The younger population is a demographic in which pupillometry could be particularly useful because it does not require the absolute stillness that fMRI necessitates. Only a few studies have applied this eye-tracking paradigm to adolescents though. Silk et al. adapted a report concluding that depressed adults show sustained pupil dilation in response to emotional stimuli and applied it to depressed adolescents (Silk et al. 2007). They investigated how differences in pupillary responses to emotional stimuli correlate to self-reported emotional experiences in participants’ everyday life. Results showed that teens with major depressive disorders had diminished late pupil dilation relative to controls following presentation of a negative word (Silk et al. 2007). This finding was markedly different from the conclusion of the adult study, and suggested that diminished late pupil dilation in depressed adolescents could be a marker for problems in emotional activity and/or regulation (Silk et al. 2007). With regards to the current study, these observations are significant because they show

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that pupillometry is a valid metric that shows differences in emotional reactivity among adolescents.

Silk et al. have also implemented eye tracking during an emotional word valence identification paradigm with adolescent children across two different groups: pre-to-early pubertal children and mid-to-late pubertal children (Silk et al. 2009). The study yielded several different conclusions about the salience of emotional situations in adolescents.

It demonstrated that the older group had greater response to the presented words, regardless of their word valence, and that this pupillary response lasted for a shorter period of time following the word’s removal from the screen than that of the younger group. Older adolescents also had faster reaction times to all words, rated themselves as more emotional during the study, and had a greater ability to recall emotional words following the task than the younger adolescents. These findings are generally consistent with models suggesting that puberty is associated with greater emotional reactivity (Silk et al. 2009; Spear 2000; Casey et al. 2010; Steinberg 2005). Additionally, these findings show that there are significant differences in pupil response across ages during adolescence. In the current study, the objective is to determine whether the difference in pupillary responses explains the difference in decision behavior across the age spectrum of adolescents.

In another study, the same group recorded eye-tracking data while adolescent subjects received acceptance or rejection feedback from virtual peers in a novel chat room interaction task (Silk et al. 2012). They developed this new paradigm, which includes photographs of other adolescents and live feedback, to more closely replicate realistic interactions between two adolescents. Findings revealed increased pupil dilation in response to rejection feedback, a trend that became more dramatic with age and that was not seen in response to positive feedback. These responses were also related to real world feelings of social connectedness insofar as greater pupil dilation in response to rejection correlated with feelings of greater disconnect with peers. Another interesting conclusion from this study was that gaze patterns from the eye tracker showed that adolescents actively avoid attending to rejection feedback stimuli, and that this avoidance is stronger with increased pupillary response even before the subject sees the feedback (Silk et al. 2012). These findings suggest that adolescents, especially older members of the demographic, are sensitive to rejection and seek to anticipate and avoid lending attention to negative stimuli (Silk et al. 2012).

These findings are significant to the current study for two reasons. First, they show that the data collected in the lab are correlated to the data collected from the subjects in real world setting (using a cell phone data collection paradigm). This provides a foundation for the hypothesis that observations obtained in a laboratory are capable of having predictive power in reality. Secondly, this study also shows that gaze patterns offer intriguing and novel information that can be purposefully associated with pupil diameter measurements.

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The current study Our study takes a novel approach to investigating the adolescent decision-making process by comparing eyetracking data from a single paradigm between adults and adolescents, as well as across adolescence. Here we utilize a gambling task, adapted from a previous study conducted

by Cohen et al. (2011), in which the participants make one choice from a set of three different options according to which one they believe will give them the best outcome.

After 87 trials of subjects choosing one gamble from three options, the computer then cycles through ten randomly selected gambles that the subject already chose and displays the outcomes. Pupillary changes in response to the outcome of the gamble will be analyzed and compared between groups and across ages in the adolescent group.

Average in pupil diameter over time following the revelation of the outcome for each of the ten trials will be compared between the two groups. Furthermore, we will look at fixation durations prior to outcome reveal to analyze which possible outcome the participants are focusing their attention to the most.

We expect to see the strongest pupillary changes following outcome revelations that surprise the subject or most strongly contradict what the subject was expecting.

We expect that this pupil dilation will be exaggerated in the adolescent group compared to adults because of the generally increased salience of emotional and arousing experiences among adolescents (Galvan et al. 2006; Casey et al. 2010; Cohen et al. 2010). From the fixation data, we expect to see marked differences between adults and adolescents, such that adolescents spend a greater amount of time avoiding looking at negative outcomes (Silk et al.

2012; van Duijvenvoorde et al. 2008).

The data and analyses for this study have yet to be published and are therefore prohibited from being shared due to publication restrictions. We hope to publish the results soon.

Aston-Jones, G., and Cohen, J.D. (2005). An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance.

Annu. Rev. Neurosci. 28, 403–450.

Calvo, M.G., and Lang, P.J. (2004). Gaze patters when looking at emotional pictures: motivationally based attention. Motivation and Emotion. 28: 3.

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A review of current psychopharmacological approaches to the treatment of schizophrenia in children and adolescents Caley Burrus1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Caley Burrus (cjb53@duke.edu) 1

SUMMARY: Childhood-Onset Schizophrenia (COS) and Early-Onset Schizophrenia (EOS) are rare manifestations of the more common adult-onset schizophrenia. However, despite the similarities between COS, EOS, and adult-onset schizophrenia, the treatment of children and adolescents with antipsychotics poses several challenges. In this review, several current antipsychotics used in the treatment of COS and EOS are discussed. The efficacy of these medications in reducing both positive and negative symptoms of schizophrenia is reviewed, and consideration is also given to the safety of each drug and its side effects. This review indicates that many of the same drugs used to treat adult-onset schizophrenia, including clozapine, olanzapine, risperidone, haloperidol, aripiprazole, and molindone, may be effective in reducing symptoms in children with COS and EOS. However, some of these treatments, notably olanzapine, have fewer and less severe side effects than the other medications, whose side effects often include tardive dyskinesia, tachycardia, and akathisia. When deciding which medication individual patients should be prescribed, physicians should consider not only the efficacy of the medications in symptom reduction, but also their side effects and what the effects on the childâ&#x20AC;&#x2122;s quality of life will be. Further research should be conducted to discover new, more comprehensive treatments for COS and EOS that have fewer, less debilitating side effects.

Introduction Schizophrenia is a chronic psychiatric disorder that results in severe impairment of functioning and personal distress. Common symptoms include but are not limited to delusions, hallucinations, catatonia, disorganized speech, and blunted affect (DSM-IV-TR). Schizophrenia is rather common among adults, with nearly 1% of the population suffering from the disorder. In a substantial proportion of cases, the patient develops symptoms between the ages of 18 and 30. Schizophrenia rarely develops in childhood or adolescence. Schizophrenia that first develops between the ages of 13 and 18 is termed early-onset schizophrenia (EOS), while schizophrenia that develops before the age of 13 is termed childhood-onset schizophrenia (COS). Presentation may either be acute, meaning the symptoms develop rapidly over the period of weeks to a few months, or insidious, meaning symptoms develop slowly over a much longer time period, often over many months or years. Children and adolescents with schizophrenia tend to have far worse prognoses and life outcomes than patients with adult-onset schizophrenia (Ropcke, B. & Eggers, C, 2005). For this reason, schizophrenia in children and adolescents should be studied independently from adult-onset schizophrenia.

Despite the poor prognoses of EOS and COS, treatment delivered early and properly can help reduce the 30 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

negative effects of the illness and improve the patientâ&#x20AC;&#x2122;s long-term outcomes. As the brain is still undergoing a great deal of developmental change during childhood and adolescence, mitigating the negative effects of the disorder could help the brain develop as normally as possible (Rosebaum, J., Tompson, M., & McGrath, E., 2004).

However, the dynamic development of the brains of children with schizophrenia poses additional challenges for psychopharmacological therapy. Antipsychotics--medications typically used to treat adult schizophrenia -- tend to have many detrimental side effects. Although clinical studies have shown that these drugs are successful in relieving many symptoms of schizophrenia, little is known about their long-term effects on brain growth and development. The developing brain of a child or adolescent could respond differently to these medications than the mature, adult brain. For this reason, antipsychotic medications should be carefully assessed in children and adolescents for safety and functionality.

This article reviews current literature assessing various treatments for COS and EOS, with a focus on commonly-used pharmacological interventions. The objective is to explore whether some medications are more effective than others, whether the benefits of antipsychotic medication use outweigh the risks posed to pediatric patients, and finally, what steps should be taken to (1) improve the

review standard of care for patients with COS and EOS and (2) differentiate pediatric from adult schizophrenia therapies.

Clozapine vs. Olanzapine A recent study conducted by Kumra and colleagues assessed whether clozapine or high-dose olanzapine was more effective in treating refractory EOS (2008). The study selected 40 patients between the ages of 10 and 18 years with a diagnosis of either schizophrenia or schizoaffective disorder and no history of other severe medical or psychological illnesses. The patients were randomly assigned to either the olanzapine group (21 patients) or the clozapine group (18 patients). There was no placebo control group.

The doses for each patient were titrated by a practicing physician as deemed necessary to account for the individual characteristics of the patient, such as weight and age.

The drugs were administered in a double-blind fashion to minimize experimenter bias. The patients were closely monitored with physical and psychological examinations and side effects were noted.

Results indicate that 66% of the patients who received clozapine had diminished schizophrenic symptoms by the end of the 12-week study, while only 33% of the patients who received olanzapine noted such improvement. This statistically significant difference in improvement supports the notion that clozapine may be a more effective treatment for refractory early-onset schizophrenia than olanzapine.

However, patients in both treatment groups suffered from side effects of the medications, many of which may not have been tolerable outside of a hospital setting. Of the 40 participants, 5 patients exhibited severe side effects which required that their medications be stopped. These side effects included an upper bowel obstruction requiring surgery, neutropenia, polyuria, and drug-induced diabetes. Four of five of these patients with severe side effects were taking clozapine. The remainder of the patients on both medications experienced less acutely severe side effects including excessive weight gain, hyperglycemia, prediabetes, drowsiness, and insomnia. Due to the severity of clozapineâ&#x20AC;&#x2122;s side effects in this pediatric population, the researchers suggest that a high dose of olanzapine (30 mg/ day) be administered first and clozapine be administered only if the patient is unresponsive to olanzapine after a reasonable period of time.

The limitations of this study should be considered before conclusions are drawn, particularly in light of the serious side effects. First, the sample size was rather small (n = 40 participants) which may limit generalizability of the findings. Second, the study did not specify the method used to quantify symptom improvement. Without understanding the methodology, determining whether the results are clinically significant is difficult. Finally, the data derived from these pediatric patients was not compared to

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data from adult patients, so little can be concluded about the efficacy of clozapine and olanzapine in the treatment of EOS as compared to that of adult-onset schizophrenia.

Further research should be conducted with a larger sample size and with clear operational definitions of improvement to assess the clinical significance of using olanzapine versus clozapine. Additionally, research should be conducted to determine if and why pediatric patients respond differently to these antipsychotic drugs than their adult counterparts. Finally, longitudinal studies should be conducted to determine whether either clozapine or olanzapine is effective in preventing future relapses and whether their use is associated with improved functioning in the long term relative to controls. The potential for longer-term side effects also warrants careful examination.

Clozapine vs. Olanzapine A similar study conducted by Shaw and colleagues attempted to analyze the efficacies of olanzapine and clozapine. Twenty-five children between the ages of 7 and 16 with EOS were included in this study (Shaw, P., Sporn, A., Gotgay, N. et al, 2006). Before beginning the experiment, the patients stopped receiving their existing antipsychotic medications and went through a medication wash-out period for three weeks. The children were randomly assigned to two groups: the olanzapine group and the clozapine group. There was no placebo control group. The medications were delivered in a double-blind fashion for eight weeks, at the end of which several evaluations were made.

The CGI Severity of Symptoms Scale and the Schedule for the Assessment of Negative/Positive Symptoms were used to document the patientsâ&#x20AC;&#x2122; status changes. Several other methods were used to monitor side effect severity.

At the end of the eight-week trial, clozapine was associated with a higher level of improvement than olanzapine. However, clozapine also had a more severe side effect panel. Clozapine patients experienced enuresis, hypersalivation, difficulty concentrating, and insomnia at statistically significantly higher rates than the olanzapine patients. Additionally, a higher incidence of cardiac complications was reported in the clozapine cohort, including hypertension and tachycardia. Both cohorts also showed a marked increase in BMI. No difference was observed, however, in reported extrapyramidal effects between olanzapine and clozapine patients.

Upon follow-up two years later, only two of the ten patients originally assigned to the olanzapine group were still receiving the drug. The other eight had switched to clozapine therapy, most often because of inefficacy of olanzapine in reducing psychotic symptoms. It is worth nothing that although olanzapine therapy exhibited efficacy during the 8-week trial, its efficacy waned in comparison to that of clozapine over time.

The main limitation of this study was the lack of a conVol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 31

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trol population. Also, the sample size was small. Out of the 96 patients who underwent eligibility assessment, 71 were excluded either because of comorbidity or mental retardation. Therefore, the generalizability of the results from this study to the average clinical population of EOS patients is limited. A follow-up study could be conducted with a larger and more representative sample such that the differences in efficacy and side effect profile of clozapine compared to olanzapine could be documented in a more clinically significant way.

Efficacy and safety of Olanzapine Additional research suggests limited size effects for olanazpine. In a study by Sholevar and colleagues, 15 patients under the age of 13 with schizophrenia in an inpatient child psychiatric hospital were asked to participate in a study of olanzapine (Sholevar, E., Baron, D., & Hardie, T., 2000). The study excluded children with mental retardation, underlying neurological abnormalities, and comorbid psychiatric diagnoses. During their two-week hospital stay, each child received olanzapine. The dosage of olanzapine was titrated to a maximum of 5 mg per day.

There was no control group. The childrenâ&#x20AC;&#x2122;s behaviors, levels of sedation, side effects, and schizophrenic symptoms were assessed daily by trained clinicians.

At the end of the study, five children showed significant improvement, five showed moderate improvement, and three improved slightly according to the Likert scale rating for psychotic improvement. Two children showed no improvement. The most common side effect was sedation. Interestingly, the results showed that children who experienced more sedation while taking olanzapine also showed the most improvement at the end of the study. No other major side effects were noticed.

Since there were no control or comparison groups, conclusions cannot yet be made regarding whether olanzapine is better than other medications or placebo. Similarly, the children were not randomly selected, as schizophrenic children under the age of 13 represent a very small proportion of the population However, in spite of these limitations, this study lends further support to other studies that suggest olanzapine may be a reasonable treatment for childhood-onset schizophrenia, since major side effects were minimal in this sample and results indicated some level of improvement for most participants (13 of 15).

Olanzapine 1-year trial Children between the ages of six and 15 who had developed schizophrenia prior to their 13th birthday were recruited for this study (Ross, R., Novins, D., Farley, G., & Adler, L., 2003). Three of the 20 children reported history of abuse or trauma, but were not excluded from the study.

Olanzapine was administered for one year, and ratings of symptoms, behaviors, and side effects were taken regularly.

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review The Scale for the Assessment of Positive Symptoms and the Scale for the Assessment of Negative Symptoms revealed that the patientsâ&#x20AC;&#x2122; schizophrenic symptoms had improved since the beginning of the study. However, it took approximately two months before maximum reduction of positive symptoms was noted. In some cases, the patients experienced worsening depression and physical health problems after taking olanzapine for three months.

Most patients did not experience negative symptom improvement until they had been on olanzapine for a full year.

The most common physical side effect was weight gain, with patients gaining an average of 12.8 kg by the end of the year. For many of the patients, treatment pushed their BMI from the normal range into the overweight range, and further from the overweight to the obese category.

However, no other major side effects were commonly noted. No child had developed dyskinesias or other extrapyramidal side effects by the end of the one year trial.

This study had many strengths: the trial lasted through a one year period, and the overseeing physicians were able to titrate the dose of olanzapine to the particular needs of the child. In other words, the researchers were able to assess the effects of more than one particular dose of olanzapine. They were able to assess the effects of olanzapine in a more traditional clinical setting, where the physician could titrate the dose of the medication as needed to achieve optimum symptom improvement. The sample size was small, however, thus determining true clinical significance was inappropriate. Finally, there was no control group; the effectiveness of olanzapine could not be compared to that of placebo or other drug treatments. Despite these shortcomings, the study adds further evidence to suggest that olanzapine may be effective for reducing both positive and negative symptoms of early-onset schizophrenia when taken for at least one year. Additionally, given that the most commonly observed effect of olanzapine was weight gain, its side effect panel appeared tolerable for most patients.

Oral Aripiprazole In this study, the efficacy of aripiprazole in treating schizophrenia was assessed in a large pediatric sample (Findling, R., Rob, A., Nyilas, M. et al, 2008). The study included 302 patients with adolescent-onset schizophrenia between the ages of 13 and 17 from across the world, with a focus on the United States and Europe. Patients who had a history of other psychiatric disorders, suicide risk, depression, mental retardation, or any other underlying neurological conditions were excluded from the study.

The remaining patients were randomly assigned to three groups. One group received placebo while the other two groups received 10 mg/day and 30 mg/day of aripiprazole, respectively, for 6 weeks. The patients and staff were blind

review to the experimental conditions. The efficacy of the drug was measured using the Positive and Negative Symptom Scale (PANSS). Side effects were also noted by trained clinicians. Health evaluations, especially of metabolic and cardiac activity, were conducted throughout the study.

Aripiprazole at 10 mg/day and 30 mg/day was found to be effective in reducing positive symptoms of schizophrenia in adolescents. However, only the 30 mg/day group showed significant improvement of negative symptoms.

The most commonly noted side effects were extrapyramidal disorders, akathisia, nausea, somnolence, and tremor.

The higher the dose of aripiprazole the patient was receiving, the more side effects he or she typically experienced.

The study length was too short for weight gain and other metabolic changes to be observed.

Overall, the study appeared to be well-designed. The sample included patients from diverse regions of the world and the sample size was large enough to allow for reasonable calculations of statistical and clinical significance.

The randomization and double-blind procedures helped eliminate sample and experimenter bias, thus increasing both internal validity and generalizability. However, this study was rather short in duration. Previous research has shown that full drug efficacy and side effects may not be evident until six to eight months after treatment initiation. With these limitations in mind, further studies could be conducted over longer periods of time to confirm this study’s conclusion that aripiprazole is an effective treatment for adolescent-onset schizophrenia. This longerterm research also would give additional time to explore other potential side effects.

Clozapine vs. Haloperidol Haloperidol is commonly used to treat adult-onset schizophrenia. This study conducted by Kumra and colleagues attempted to explore the efficacy and side effects of haloperidol compared to clozapine. Twenty-one patients between the ages of 6 and 18 with schizophrenia were enrolled in this study (Kumra, S., Frazier, J., Jacobesen, L. et al, 1996). Before the study began, the patients were taken off of all other medications for four weeks to remove potentially confounding effects. The patients were then randomly assigned such that half would take clozapine and half would take haloperidol. Doses of each medication were titrated to the individual characteristics of each patient. Weekly behavior ratings were taken using the Children’s Global Assessment Scale and the Clinical Global Impressions (CGI) scale. Negative and positive symptoms were also assessed with reliable measures.

The study lasted six weeks and four of the 21 patients did not complete the study because of serious, adverse medication effects. The side effects of both medications were similar, except clozapine was found to cause hematopoietic toxic effects. Two of the patients in the clozapine

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group also experienced severe seizure activity. Even after the seizures were controlled with anticonvulsant therapy, the patients’ electroencephalography (EEG) tests continued to show seizure-like activity; clozapine treatment was subsequently stopped. It was not stated whether the prolonged seizure activity and noted EEG abnormalities caused long-term detriment to these patients’ developmental processes.

The behavioral and symptom analyses conducted in this study revealed that clozapine is more effective at improving both positive and negative symptoms compared to haloperidol in children. However, upon follow-up one year later, nearly 50% of the patients had been taken off of clozapine therapy because of serious adverse effects such as seizures and hematological abnormalities. Although clozapine appears superior to haloperidol in the treatment of schizophrenic symptoms, its side effect panel is extensive, and long-term use may pose significant problems for children’s health and well-being.

Though the study only lasted six weeks, a yearly followup was conducted; this helped to determine the long-term effects of clozapine. As previously mentioned, however, it can often take up to six to eight months before all side effects and treatment benefits are seen. Based on this six week trial, it therefore cannot be concluded that clozapine is more effective than haloperidol.

Risperidone Risperidone is a common treatment for adult-onset schizophrenia. Few studies, however, have documented its safety and efficacy among pediatric populations. In this study, 160 schizophrenic adolescents between the ages of 13 and 17 were enrolled into a clinical trial of risperidone (Haas, M., Unis, A., Armenteros, J. et al, 2009). Each participant was randomly assigned to one of three groups: placebo, risperidone at 1-3 mg/day, and risperidone at 4-6 mg/day. Patients were assessed using the PANSS, and levels of adverse events and extrapyramidal symptoms were noted. At the end of the 6-week trial, the patients in both of the risperidone treatment groups showed significantly more improvement than patients who received the placebo. The patients receiving the higher dose of risperidone showed more symptom improvement than patients receiving the lower dose. However, patients in the higher dose group also experienced more unpleasant side effects, such as extrapyramidal disorders, dizziness, and hypertonia. No metabolic abnormalities were noted during this short study.

After weighing the benefits and drawbacks of the higher dose of risperidone, the authors concluded that children should be started on the low 1-3 mg/day dose of risperidone to avoid increasing the risk of serious side effects when possible. While the authors suggest both doses may be safe if the patients are closely monitored medically Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 33

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and psychologically, the patient’s quality of life represents a serious concern and unnecessary adverse effects should be avoided whenever possible.

As with many drug trials of antipsychotic medications on pediatric populations, this trial was short in duration and did not include a longitudinal follow-up. For this reason, no conclusions can be drawn about the long-term safety of higher doses of risperidone in children. Longitudinal trials are needed to assess the side effect profiles of low and high doses of risperidone in children and adolescents to determine the longer-term safety and effectiveness of this drug for the pediatric population.

Risperidone vs. Olanzapine vs. Molindone The purpose of this trial was to assess the efficacy of second-generation antipsychotics compared to first-generation antipsychotics (Sikich, L., Frazier, J., McClellan, J., et al 2008). Over 100 COS and EOS patients were identified and recruited from across the United States and were randomly assigned to receive one of three treatment options: olanzapine, molindone, or risperidone. There was no placebo group. The medication was delivered daily in a double-blind fashion to minimize experimenter and expectation biases. Treatment lasted for eight weeks and, at the end of this period, several scales and assessments were used to determine which of the three medications had been more effective in reducing symptoms.

No significant difference in symptom improvement was noted among the three groups, which supports the hypothesis that there is not a large efficacy difference between first and second generation antipsychotics. However, olanzapine and risperidone were more significantly associated with increased weight gain than molindone.

Molindone and risperidone patients experienced Parkinsonian symptoms and akathisia, while these two severe side effects were absent for the olanzapine group. Overall, the side effects of olanzapine were less severe than the side effects of the other two antipsychotics.

The authors made no recommendations as to which medication was preferable for use among pediatric patients with schizophrenia, as all three were effective in reducing schizophrenia symptoms. However, when treating youth, the side effect panel is a particularly important consideration. Effects on quality of life should be considered in addition to the efficacy of the medication when making clinical treatment decisions. Further studies are needed to determine whether olanzapine, the drug for which study results suggest a more favorable side effect panel, improves the quality of life of children with schizophrenia more so than the other antipsychotic medications.

Brain Abnormalities in Schizophrenic Children Unlike the previously reviewed trials, this study conducted by Yeo and colleagues (1997) analyzed several developmental aspects of children with schizophrenia.

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review Several measures were used to analyze verbal ability, verbal memory, non-verbal ability, and non-verbal memory.

Magnetic resonance imaging (MRI) was also conducted to observe differences between the 20 patients with schizophrenia and the 20 controls in total brain volume, ventricular volume, frontal lobe volume, and anatomic symmetry.

Structural MRI’s of brains of children with schizophrenia revealed similar neuroanatomical abnormalities among both adult and pediatric patients with schizophrenia, when compared to neurotypical brains. For example, the ventricles of COS patients’ brains were significantly larger in volume than those in control children. The temporal cortex was significantly smaller in COS patients. The schizophrenia group also exhibited significant differences in all of the neurodevelopmental categories assessed in the study, with children in the schizophrenia group performing worse in both verbal and nonverbal memory and function tasks.

The main weakness of this study was the small sample size of patients (N=20). The trial conclusions were also correlational, as there was no way to determine whether the structural and neurodevelopmental abnormalities noted were the result of neuroanatomical and functional deterioration caused by the disorder, or whether the abnormalities existed prior to the development of the disorder. More studies should be conducted using larger sample sizes and prospective research to determine direction of causality. A better understanding of the neuroanatomical, functional, and developmental aspects of schizophrenia could be beneficial in discovering new, effective, and safe medications to treat this debilitating disorder.

Effects of Clozapine and Olanzapine on cortical thickness This review has included studies that suggest possible effectiveness for both clozapine and olanzapine as treatments for EOS. Mattai et al (2009) attempts to establish the direction of causation between structural brain changes and the delivery of olanzapine and clozapine (Mattai, A., Chavez, A., Greenstein, D. et al, 2009). Gaining a better understanding of the underlying mechanisms is an especially important topic to address for the pediatric population, whose developing brains may be more sensitive to the effects of neuroleptic medications.

This study recruited 24 COS patients from across the nation. Twelve received clozapine and 12 received olanzapine. An average of 30 MRI scans were conducted for each group to assess the cortical thickness of the patients’ brains. Decreased cortical thickness is associated with less neurological functioning in several domains, including perception, intellect, and memory. The cortical thickness of children with schizophrenia was significantly smaller when compared to results previously derived from non-schizophrenic children. Between the two treatment groups, there was no noted difference in cortical thickness,

review implying that the medication likely did not contribute significantly to cortical thinning. Rather, it is more probable that the cortical thinning occurs concurrently with or before the development of schizophrenic symptoms.

Further research may confirm the direction of causality by conducting MRIs on a group of children without schizophrenia and comparing these to the MRIs of the same children who, in that group, develop schizophrenia both at the time of onset of symptoms and after treatment has begun.

Conclusion Choosing a course of treatment for childhood and adolescent schizophrenia is complex, as many factors must be considered. All of the studies reviewed in this paper indicate that most antipsychotic medications used in the general population of adults with schizophrenia may be effective for reducing symptoms in children and adolescents. Due to their growing bodies and developing brains, however, children with schizophrenia may respond differently to antipsychotic medications than adults. For this reason, the adverse effects of each drug, as well as its symptom reduction efficacy, should be considered when making clinical treatment decisions.

For instance, clinical trials have shown that clozapine may be more effective in reducing schizophrenia symptoms than olanzapine (Shaw, P., Sporn, A., Gotgay, N. et al, 2006; Kumra, S., Krazzler, H., Gerbino-Rosen, G. et al, 2008). Despite this difference in efficacy, however, results of the studies included in this review suggest that clozapine in newly-diagnosed schizophrenic children may not be recommended because the side effects of clozapine tend to be more severe and occur in high incidences than those of olanzapine. Similarly, higher doses of risperidone appear to be more effective than lower doses, but the higher doses often coincide with more severe side effects (Haas et al, 2009). Some of these side effects, such as tardive dyskinesia, persist even after drug treatment is stopped and may become permanent. These studies would suggest that patients should be kept on the lowest possible dose of medication to delay side effects for as long as possible, and the dose should only be increased when the symptoms of schizophrenia became more detrimental to the patientâ&#x20AC;&#x2122;s quality of life than the side effects. This is to ensure that the negative impact of the prescribed antipsychotic does not exceed the positive impact gained from the reduction of the schizophrenia symptoms.

Another important consideration for the pediatric population is the effect of antipsychotic medications on neurological development. The antipsychotics discussed in this review generally function by altering dopamine levels in the brain. When neurotransmitter levels are altered, the neurons responsible for producing these neurotransmitters may be altered as well. Therefore, drug therapy

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during childhood neural development places the child at heightened risk for permanent neuronal dysfunction. At this point, however, little is known about the neurodevelopmental trajectory of schizophrenia and how antipsychotics affect this trajectory (Rosebaum, J., Tompson, M., & McGrath, 2004; Ropcke, B. & Eggers, C., 2005; Yeo et al, 1997). Further research is needed on this topic to ensure the complete safety of antipsychotic medication on children and adolescents.

Additionally, even though all of the medications discussed in this review exhibited some degree of efficacy in reducing schizophrenia symptoms, the exact mechanism by which these antipsychotic drugs function in the young, underdeveloped brain is still unknown. Elucidating this mechanistic information could help clinicians tailor treatment and maximize benefits while minimizing risks and side effects for EOS and COS patients.

Finally, the literature suggests that children and adults with schizophrenia may have structural variations in their brains that coincide with the presentation with symptoms of schizophrenia, such as reduced cortical thickness and enlarged midline ventricles. The revised dopamine theory of schizophrenia states that positive symptoms are likely caused by neurotransmitter imbalance, while negative symptoms are likely caused by structural abnormalities in the brain (Rabiner, 2011). To ignore the effect of structural change on the development of schizophrenia in antipsychotic drug therapy is to potentially neglect addressing a large precursor of disorder. We must determine how the structural abnormalities of this disorder are formed, what effect they have on symptom presentation, and what, if anything, could reset these alterations before symptoms are presented.

This review concludes based on the available research to date that no single antipsychotic medication can be deemed the most clinically useful in the treatment of childhood and adolescent schizophrenia. There are a number of medications available that, with proper dosing and side effect monitoring, could be effective and fairly safe for children and adolescents with schizophrenia. These medications include olanzapine, which appears to be the one of the most tolerable of the medications, as well as clozapine. The latter is effective in reducing schizophrenia symptoms but appears to have more severe side effects than olanzapine. Other antipsychotic treatment options include risperidone, molindone, aripiprazole, and haloperidol. Careful consideration of the patientâ&#x20AC;&#x2122;s condition and monitoring the patientâ&#x20AC;&#x2122;s side effects, especially extrapyramidal effects, metabolic levels, and cardiac complications, are needed for patients on any of these drugs. In addition, providers should conduct assessments regularly throughout the treatment process to ensure that the risk to benefit ratio of antipsychotic drug therapy continues to favor the well-being and overall quality of life of the child.

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American Psychiatric Association. Diagnostic and statistical manual of mental disorders, 4th ed, text rev. doi: 10.1176/appi.books.9780890423349.

Carlisle, L. & McLellan, J. Psychopharmacology of Schizophrenia in children and adolescents. Clinical Pediatrics, 2011, 58: 205-218. Doi: 10.1016/j.pcl.2012.11.006.

Findling, R., Rob, A., Nyilas, M., Forbes, R., Jin, N., Ivanova, S., Marcus, R., McQuade, R., Iwamoto, T., & Carson, W. A multiple-center, randomized, double-blind, placebo-controlled study of oral aripiprazole for treatment of adolescents with schizophrenia.

American Journal of Psychiatry, 2008, 165(11): 1432-1441.

Haas., M., Unis, A., Armenteros, J., Copenhaver, M., Quiroz, J., & Kushner, S. A 6-week, randomized, double-blind, placebo-controlled study of the efficacy and safety of risperidone in adolescents with schizophrenia.

Journal of Child and Adolescent Psychopharmacology, 2009, 19(6): 611621. Doi: 10.1089/cap.2008.0144.

Kumra, S., Frazier., J., Jacobsen, L., McKenna, K., Gordon, C., Lenane, M., Hamburger, S., Smith, A., Albus, K., & Rapoport, J. Childhood-onset schizophrenia: A double-blind clozapine-haloperidol comparison. Archives of General Psychiatry, 1996, 53: 1090-1096.

Kumra, S., Kranzler, H., Gerbino-Rosen, G., Kester, M., DeThomas, C., Kafantaris, V., Correll, C., & Kane, J. Clozapine and “high dose” olanzapine in refractory early-onset schizophrenia: A 12-week randomized and double-blind comparison.” Biological Psychiatry, 2008, 63: 524-529.

Doi: 10.1016/j.biopsych.2007.04.043.

Mattai, A., Chavez, A., Greenstein, D., Clasen, L., Bakalar, J., Stidd, R., Rapoport, J., & Gotgay, N. Effects of clozapine and olanzapine on cortical thickness in childhood-onset schizophrenia. Schizophrenia Research, 2010, 116: 44-48.

Ropcke, B. & Eggers, C. Early-onset schizophrenia: a 15-year follow-up.

European Child and Adolescent Psychiatry, 2005, 14: 341-350. Doi: 10.1007/s00787-005-0483-6.

Rosenbaum, J., Tompson, M., & McGrath, E. Annotation: Childhood-onset schizophrenia: Clinical and treatment issues. Journal of Child Psychology and Psychiatry, 2004, 45(2): 180-194.

Ross, R., Novins., D., Gordon, F., & Adler, L. A 1-year open label trial of olanzapine in school-age children with schizophrenia. Jounral of Child and Adolescent Psychopharmacology, 2003, 13(3): 301-309.

Shaw, P., Sporn, A., Gogtay, N., Overman, G., Greenstein, D., Gochman, P., Tossell, J., Lenane, M., & Rapoport, J. Childhood-onset schizophrenia: a double-blind, randomized clozapine-olanzapine comparison. Archives of General Psychiatry, 2006, 63: 721-730.

Sholevar, E., Baron, D., & Hardie, T. Treatment of childhood-onset schizophrenia with olanzapine. Journal of Child and Adolescent Psychopharmacology, 2000, 10(2): 69-78.

Sikich, L., Frazier, J., McClellan, J., Findling, R., Vitiello, B., Ritz, L., Ambler, D., Puglia, M., Maloney, A., & Michael, E. Double-blind comparison of first and second generation antipsychotics in early onset schizophrenia and schizoaffective disorder: Findings from the treatment of early onset schizophrenia spectrum disorders (TEOSS) study. American Journal of Psychiatry, 2008, 165(11): 1420-1431.

Yeo, R., Hodde-Vargas, J., Hendren, R., Vargas, L., Brooks, W., Ford, C., Gangestad, S., & Hart, B. Brain abnormalities in schizophrenia-spectrum children: Implications for a neurodevelopmental perspective. Psychiatry Research: Neuroimaging, 1997, 76:1-13.

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Schizophrenia and alterations in the fetal environment Max Castillo1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Max Castillo (max.castillo@duke.edu) 1

ABSTRACT: The origins of schizophrenia are largely unknown and there is much debate as to whether the disorder’s onset is more attributable to genetic or environmental factors. Models exist to help curb this debate, but most research has been focused on possible genetic predispositions. As genetic manipulation raises extreme ethical considerations, this line of exploration does not bring doctors much closer to preventing the onset of schizophrenia. For this reason, environmental stressors should be of greater interest to researchers. In order to prevent future cases of schizophrenia, the developing brain in the prenatal environment should be a key target of analysis. Three main prenatal events have been thought to increase the risk of brain damage and contribute to adult offspring schizophrenia: 1) maternal illness is suspected to trigger the release of neurotoxins to help combat the virus or parasite infecting the body, which inadvertently scar the fetal brain; 2) prenatal malnutrition deprives the fetus of essential nutrients, inhibiting proper brain development; and 3) researchers believe that traumatic experiences during maternity release a stress-relieving hormone which, if in high enough concentrations, can also damage the fetal brain. If a causal relationship could be determined between these factors and the risk of schizophrenia, then perhaps researchers could have a greater probability of lowering the high prevalence of schizophrenia.

Schizophrenia is a mental disorder that affects about 1% of the population, yet its origins are still poorly understood. Various treatments are currently used to quell the symptoms of the disorder, from common medications intended to treat the milder symptoms to the rare employment of electroconvulsive therapy for the most extreme cases. Many of the treatments are successful in controlling schizophrenia’s symptoms; research shows that antipsychotic medication alone is effective in remedying the positive symptoms (hallucinations, paranoia, etc.) in about 70% of patients (Ross et al., 2010). Great strides have been made in treating those currently diagnosed with the illness, but the origins of the disease are still quite hazy. While researchers agree that schizophrenia partially results from genetic predisposition, the consensus is also that an environmental stressor actually triggers its inception. This dual-cause explanation (termed the “diathesis-stress model”) is one of the few that exists to account for the causes of schizophrenia. However, the theory suggests that in order to prevent the disorder, the alteration of one’s genetic predisposition, a practice that is not currently feasible, might be necessary. Furthermore, the diathesis-stress model does not rationalize those patients who have the disorder yet does rationalize those that experience a stressful environmental trigger.

Because people with little genetic predisposition are diagnosed with schizophrenia without any major stressor, the problem must originate from abnormal brain development. To trace the source of these brain abnormalities, a good direction to take would be to look at adverse events in the prenatal environment that could lead to improper

brain formation. As this paper will demonstrate, several studies have already hypothesized that certain fetal environment changes increase the risk of offspring developing schizophrenia in adulthood.

Much research, backed by substantial data, has already been conducted to study how various prenatal environmental alterations affect brain growth. For example, Finnish mothers who were pregnant during the 1957 flu epidemic were more likely to give birth to children who would develop schizophrenia in adulthood (Mednick et al. 1994). Current research attributes this to the activation of the mother’s immune system, which releases a variety of chemicals to help combat the disease, yet adversely affects fetal brain formation in ways that increase the risk of schizophrenia (Boksa et al. 2010).

Further, maternal protein malnutrition has been linked to disruption in fetal cell migration and neurogenesis.

Should inhibition of these processes occur, brain development could be significantly disturbed, especially with regards to the hippocampus (Morgane et al. 1992). Protein malnutrition can also result in retardation of placental growth. An insufficient placenta deprives the fetus of vital nutrients and oxygen, which can cause fetal hypoxia, a known prenatal factor that increases the risk of schizophrenia (Morgane et al. 1992). Specific studies also show an increase in schizophrenia in the offspring of mothers that were pregnant during food shortages and famines (Dauncey and Bicknell 1999; McGarth 1999).

Lastly, mothers who experience severe stress while pregnant tend to have a greater chance of giving birth to a future schizophrenia patient. For example, mothers who Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 37

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lost their spouse during their first trimester of pregnancy showed an increased probability of their child developing schizophrenia (Khashan et al. 2008). Other comparable studies followed pregnant women caught in warzones, particularly the Arab-Israeli War of 1967. These mothers likewise showed a greater probability of birthing children predisposed to schizophrenia (Malaspina et al. 2008).

These three factors (maternal illness, prenatal malnutrition, and maternal stress) are the primary focuses of current research and will be the primary topics of exploration for this paper. If researchers are able to label these aspects before the child is born or before the brain is permanently scarred, enacting some form of intervention to prevent future cases of schizophrenia may prove possible.

Maternal infection Several studies have associated prenatal infection (viral, parasitic, or bacterial) with an increase in schizophrenia (Brown and Susser, 2002, Sørensen et al., 2009). Fetuses exposed to the Finnish A2 influenza outbreak in 1957 correlated to a higher risk of hospitalization for schizophrenia, though investigators cited many other possible confounding causes (Mednick et al. 1988). So what is the reasoning behind these relationships? Various studies provide different interpretations and here, the most prominent theories and their supporting studies will be discussed.

Parasitic infection can severely disrupt the neurodevelopment of the brain and thus, may be linked to a higher risk of schizophrenia. Thorough examinations of this possibly found that “infectious causation[s] have been largely overlooked by experts on schizophrenia” (L.G. Ledgerwood et al. 2003). Researchers have looked at one parasite in detail, Toxoplasma Gondii, which causes marked changes in behavior and personality in infected humans.

Interestingly, roughly 42 percent of schizophrenic patients were found to have T. Gondii infections in comparison to only about 11 percent of controls. However, evidence supports the possibility of a legitimate causal relationship between T. Gondii infection and schizophrenia. T. Gondii is known to alter the presence of nitric oxide (NO) in the central nervous system. Interestingly, NO’s functions vary depending on its concentrations; it works as a neurotransmitter in low concentrations, but as a neurotoxin in higher concentrations (Karson et al. 1996). When the body is infected with T. Gondii, NO production is significantly increased, reaching toxic levels to help fight off the infection while simultaneously damaging the brain. As we grow older and as our brain becomes more developed, it begins to resist the toxicity of NO, which leaves the fetal brain especially vulnerable. This effect is compounded since NO production is already necessary to work as a neurotransmitter in the developing fetal brain (Hayashi et al. 1996).

Alternate studies suggest that T. Gondii directly produces or stimulates the production of other chemicals that 38 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review can trigger the symptoms of schizophrenia. One such chemical, D-lysergic acid diethylamide (LSD), has been found to coexist with T. Gondii in about 44.9 percent of patients with schizophrenia, compared to none in the control groups (Silverman and Varela, 1958). The hallucinogenic symptoms experienced by schizophrenia patients can also be accounted for by the LSD and brain damage that the infection produces (Langs and Barr 1968).

This is one case where the attacking agent can be easily prevented from causing infection. The origin of T. Gondii has been traced back to cats, which contract the parasite after eating infected rodents ( Jackson and Hutchison, 1989). The cat can then transmit the parasite to humans.

Some studies proclaim that the mere presence of a large number of cats can be related to higher incidences of schizophrenia within the household. Thus, keeping cats out of the homes of pregnant women may decrease the risk of T. Gondii infection and thus limit the occurrence of schizophrenia ( Jackson and Hutchison, 1989).

Next, it would be beneficial to examine how viral infection affects the prevalence of schizophrenia, specifically maternal influenza infection. Many of the studies conducted in this regard have looked at periods of major flu outbreaks and compared them against the incidence of schizophrenia. A positive relationship has been found between schizophrenia and influenza outbreaks. One of the most famous studies observed the children of mothers pregnant during the Finnish A2 flu epidemic in 1957 (Mednick et al., 1988). The study determined that roughly 35% of those exposed to the flu virus in the second trimester of gestation and had been admitted to a psychiatric hospital in their lifetime had schizophrenia. This number is compared to a 20% chance for the control group (Mednick et al., 1988). Two years later, Mednick and Barr followed up on this study with another, showing a higher schizophrenic birthrate during winter months (2.61±0.67 per 1,000 in January versus 2.11±0.59 in August) (Barr et al., 1990). This was particularly true when the pregnancy’s second trimester occurred during the months of October and November, which had the greatest increase in influenza prevalence.

However, Barr and Mednick offer some caveats that admit their findings do not confirm a direct connection between schizophrenia and the flu. First, opposing studies noted that doctors in Finland during the flu epidemic had record sales in prescription and over-the-counter drugs, and that some of these drugs could have adverse effects on the neurodevelopment of the fetus (Hakosalo and Saxen 1971). Second, there was no way to prove that those who were admitted to a psychiatric hospital had mothers who were infected with influenza in the second trimester of gestation, though this downfall was ousted in 2004 when Brown et al. serologically determined that influenza-sick mothers had a higher chance of giving birth to schizo-

review phrenia children. Third, some researchers suggest that the fetal central nervous system is overly vulnerable to hypothermia, an important concern and factor in the winter months (Edwards, 1986). Lastly, and perhaps most significantly, a handful of researchers claim that viral infection can only increase the risk of schizophrenia in those that are genetically predisposed (Machon et al. 1983).

One must exercise caution when interpreting these findings though, for many researchers openly state that their results do not prove causation (Boska, 2010). As seen, many of the studies that provide the most concrete evidence for a link between schizophrenia and maternal illness are only post-hoc analyses of “schizophrenia outbreaks”, as is the case with Mednick et al. (1988) and Barr and Mednick (1990). As more research is conducted, maternal illness is further hypothesized to affect the fetus in three principal ways: it can distort the expression of essential, early proteins, cause DNA modifications, and alternate the peripheral systems that influence brain functioning; all of which skew neurodevelopment and increase the risk for schizophrenia in adulthood (Boska, 2010). Regardless, not much is known about prenatal infection and current research needs to shift its focus to finding possible causal, preventable factors. Since ethical considerations and practicality forbid researchers from conducting experiments on human control and test groups, a better option would be to conduct additional tests on lab animals (rats, monkeys, etc.).

After their children are born, we could then take measure for schizophrenic symptoms via cognitive tests. However, if researchers choose to go down this route, ecological validity of the findings must be a primary concern.

Prenatal malnutrition As mentioned previously, interference with protein regulation in the fetus can increase the risk of schizophrenia in the child. Besides prenatal infection, this alteration can also occur if the fetus is malnourished from maternal starvation. Some studies have shown that prenatal malnutrition retards all central nervous system growth, but that the hippocampus is especially vulnerable, possibly leading to learning and cognitive disabilities in adulthood (Dauncey and Bicknell, 1999, Morgane et al. 1992). In this section, three topics will be discussed: neural deprivations resulting from malnutrition (individual chemicals/proteins), how these deprivations directly affect brain development, and studies that support a potential relationship between schizophrenia and prenatal malnutrition.

While many studies point to protein restriction as the principal source of lackluster brain growth, various other micronutrients may also contribute to this growth defect if present in low levels. In particular, researchers have identified six express candidates that “might explain the association between early gestational famine and schizophrenia” (Brown and Susser 2008). 1) Folate limitation can impede

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the growth and regulation of DNA in the fetus. 2) Essential Fatty Acids (Docosohexarnoic acid, DHA, in particular) make up the brain’s gray matter, supplying brain mass.

The limited intake of these fatty acids can severely restrict brain growth and even lower IQ. Moreover, many schizophrenics are found to have lower brain mass and total brain volume (Lawrie and Abukmeil, 1998). 3) Vitamin A deficiency has been found to cause major malformations in the central nervous system (Warkany, 1945). Additionally, Vitamin A is essential to gene expression. 4) Vitamin D deprivation goes back to prenatal infection because during winter months (when access to sunlight is restricted and schizophrenic births are abnormally high as Mednick [1990] showed) a lot of people lack sufficient Vitamin D levels. Thus, Vitamin D has been thought to have a direct link to schizophrenia risk (McGarth, 1999). 5) Iron is necessary to the growth of the fetus, the creation of placenta (to deliver nutrients to the fetus), and the production of red blood cells. Should iron levels become low, oxygen delivery to the fetus can be compromised and fetal hypoxia can result (Rao et al., 1999). The effects of fetal hypoxia will be discussed later.

Sixth and perhaps most importantly are low levels of protein. Low levels of protein intake have been directly connected to lower brain mass, as several studies have shown. For example, rats born of mothers fed a lower-protein diet had “significantly lower brain and body weights”, with the hippocampus being noticeably affected (Dauncey and Bicknell 1999, Morgane et al. 1992). These results make intuitive sense since many cell, brain, and body parts depend on amino acids for their creation and maintenance through cell division and neurogenesis. Furthermore, out-

Figure13-D rendering of the hippocampus in a healthy person (A) versus that of a schizophrenia patient (B). (Adapted from Heckers, 2001)

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side the fetus, protein is necessary to create a sufficiently sized placenta, without which the fetus has a difficult time receiving vital nutrients (Morgane et al., 1992). This results in a cycle that is hard to break: the lack of protein creates a small placenta that delivers sublevels of nutrients to the fetus, so even if the mother consumes more proteins, their delivery to the fetus would still be impaired. Moreover, once malnutrition damages the brain, it is more or less permanent since fetal brain development occurs in a series of major, strictly timed events (Scott, 1979).

As for how prenatal malnutrition contributes to adult onset schizophrenia, focusing on two categories may prove fruitful: interference with brain development (namely in the hippocampus) and undersized placenta (relating to fetal hypoxia). Both of these points are closely related to malnutrition.

In many studies designed to measure the damaging effects of prenatal malnutrition, researchers gave rats various cognitive tests to find the general area of brain damage (Dauncey and Bicknell, 1999). Of the rats in the nutritionally-deprived group, scores on maze tests were significantly lower than in control group, suggesting severe damage to the hippocampus, and thus in the areas of cognition and memory.

Interestingly, schizophrenia has been linked to not only lower brain weights, but also to decreased hippocampal size (Heckers, 2001). Figure 1 shows a 3-dimensional rendering of a hippocampus in a healthy person versus one in a person with schizophrenia. Notice that for Patient B, someone who has schizophrenia, there is much smaller hippocampus than Patient A. Probably the most accepted reason for this deformity is that protein is necessary in cell multiplication and thus neuron formation (Cintra et al., 1997). Without protein, neurogenesis is critically altered, leaving the brain unable to produce sufficient neurons to form and maintain a healthy, full-sized hippocampus (Debassio et al., 1996). The primary piece of evidence that supports a link between hippocampal size and schizophrenia are the above brain images of a shrunken hippocampi and the observation that schizophrenic patients and malnourished animals with lesions on the hippocampus display similar abnormal behaviors (Schmajuk, 2001). Given this evidence, it is possible that the undersized hippocampus witnessed in people with schizophrenia may be a result of prenatal protein malnutrition.

Protein is also a necessary component in healthy placenta formation, which is fundamental in the delivery of blood and nutrients to the fetus. As with the development of the hippocampus, protein is largely used for cell differentiation, thus a lack of protein means slower cell division and hence a deficient placenta. If the placenta is so undersized that the oxygen supply to the fetus is limited, fetal hypoxia may result. Hypoxia is a serious obstetrical complication that spawns from a lack of proper blood (and 40 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review hence oxygen) flow to the fetus. Interestingly, the number of incidences of fetal hypoxia have been found to increase linearly with the risk of schizophrenia in adulthood - a phenomena possibly resulting from an interaction between genetic predispositions and the hypoxia itself (Cannon et al. 2000). However, some proportion of hypoxia cases occur regardless of protein intake levels and researchers are currently working to map the genes that may cause this susceptibility. This is to say, due to certain genes, a perfect relationship does not exist between protein levels and one’s vulnerability to hypoxia and hence, to schizophrenia.

There are several important things to note about these particular results before continuing onto further evidence. First, many researchers that study the effects of prenatal malnutrition remark that the brain develops in “leaps and bounds,” each of which are enormously important to the creation of a healthy brain (Morgane et al., 1992).

Should one of these stages be missed or interrupted, the effects are practically irreversible. Many researchers have concluded that even re-nutrition and positive environments cannot remedy the effects of prenatal malnutrition.

Thus, the effects of a reduced hippocampus or a diminutive placenta may be present throughout the individual’s life.

Also, several of these studies, like those done by Morgane et al. (1992) and Dauncey and Bicknell (1999), were conducted on rats, provoking considerations about ecological validity. Moreover, although some of the studies had the excellent design of a prospective cohort, the sample sizes were rather small. For example, Cannon et al. (2000) only followed 72 schizophrenic patients while following almost 8,000 controls.

Lastly, some studies examine the relationship between prenatal malnutrition and schizophrenia. The Dutch Hunger Winter of 1944-1945 resulted in a substantially higher-than-normal number of birth defects and mental disorders, including schizophrenia (Brown and Susser, 2008, Stein et al., 1975). During this era, Nazi rationing limited Dutch citizens to less than 500 calories a day, causing double the mortality rate and half the fertility rate (Brown and Susser, 2008). Rates of schizophrenia and schizoid personality disorder also doubled in the years following this period (Hoek et al. 1996). In the same vein, parents who survived China’s Great Leap Forward campaign had a similar proclivity to give birth to children who would grow up to develop schizophrenia (Brown and Susser, 2008). However, the authors of these studies also identify heightened prenatal stress during these extreme points in history as a possible confounding contributor to the observed increase in schizophrenia rates. Since a significant number of researchers mentioned prenatal stress in their study of schizophrenia, the next section will discuss this variable and its probable relation to one’s susceptibility to the disorder.

Maternal Stress

review Maternal stress comes in many forms. War, famine, spousal death, or even unwanted pregnancy can all result in stress for the fetus and increase the risk of schizophrenia diagnosis later in life (Myhrman et al., 1996, van Os and Selten, 1998). These studies most commonly carried out post-hoc analyses of particular stressful events and the subsequent number of cases of schizophrenia in children of mothers who endured the event. Nevertheless, there have been a few studies that tried to trace this relationship directly back to hormonal releases that help the mother cope with stress. As with the sections before, the following paragraphs will discuss the scientific reasoning behind prenatal stress as a possible causal factor for schizophrenia and then highlight some of the key studies that support such a claim.

One of the most cited research articles on how prenatal stress disrupts brain development focused on how the hypothalamic-pituitary-adrenal axis (HPA axis) affects the release of the hormone glucocorticoid. When an animal experiences stress, whether it is a rat or human, the HPA axis triggers the release of glucocorticoids which assist in coping with adverse situations (Welberg and Seckl, 2001).

In humans, the primary glucocorticoid, cortisol, can also function as a neurotoxin when present in high concentrations. During pregnancy, some cortisol will invariably make its way into the fetal bloodstream with potentially dangerous effects. While the fetus does has specific adaptive enzymes that break down the cortisol before it reaches the brain, particularly stressful situations involving a lot of cortisol will overwhelm these defenses and damage the fetal hypothalamic structures (Uno et al., 1994). This damage can cause a number of serious disruptions in cognitive and behavioral development, which has been associated with higher chances of schizophrenia and anxiety disorder onset (Nemeroff et al., 1984, van Os and Selten, 1998, Welberg and Seckl, 2008).

Well-known evidence supports the possibility of prenatal stress as a causal factor of schizophrenia. Nevertheless, no study has listed all potential schizophrenia-causing stressors since â&#x20AC;&#x153;stressâ&#x20AC;? is subjective and could result from a myriad of life events. For these reasons, this section underscores two of the most researched maternal stressors: living in war zones and experiencing the death of a close relative (spouse or otherwise).

Because military invasion is a virtually universal stressful situation and has been linked to a great number of psychological disorders, researchers have focused on how such an environment could affect the well-being of a mother and her offspring. For example, the Arab-Israeli War of 1967 is often subject to analysis due to its extremely short duration (six days), which provides a specific time frame for researchers to explore the possible onset of mental afflictions (Malaspina et al. 2008). Moreover, this war was rather conventional in that neither side used chemical

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attacks and the short duration prevented food blockades from being effective, both of which may have contributed to birth defects. Because of these unique aspects, Malaspina and fellows were able to narrow down the time of gestation to the month, rather than by the trimester. They found that fetuses exposed to stress during the second month of gestation had a nearly threefold greater likelihood of developing schizophrenia (Table 1), and a generally higher rate when exposed at any point during the first trimester.

These results are supported by van Os and Selten

Table 1: Notice the number of schizophrenia cases for those born during the month of January. Many researchers concur that stress has its most detrimental effects during the first trimester of the pregnancy. (Modified from Malaspina et al., 2008)

(1998), who studied the stress of the German invasion of the Netherlands of 1940. Mothers subjected to the stress of military invasion during the first trimester of gestation had a statistically greater chance of having schizophrenic offspring. Also, both studies notice that famine is both a prenatal stressor and a cause of prenatal malnutrition. For this reason, their combination greatly heightens the risk of schizophrenia, so it is important to study situations where famine is not a factor. While the authors reached similar conclusions in this respect, they disagreed in other substantially important areas. Under wartime circumstances, female fetuses may actually have a higher predisposition to schizophrenia later in life than males (Malaspina et al.

2008). Opposing this result, Dutch males in gestation during the 1940 invasion were found to have higher rates of schizophrenia (van Os and Selten 1998). However, in the latter study, the analyzed population was rather small and this disagreement may be nothing more than a design flaw, but it still warrants a need for future exploration of gender differences.

Other stress-related studies have looked at the effects the death of a loved one can have on a pregnant mother, whether it is the death a family member or a husband. In one study, researchers looked to see if the loss of a close relative would increase the risk of schizophrenia in the child (Khashan et al. 2008). Results indicate that such an event did indeed correlate with higher vulnerability to Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 41

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schizophrenia, especially when the death occurred in the first trimester of the pregnancy. Huttunen and Niskanen (1978) confirm these results when they examined the children whose mothers had lost their husbands in the Second World War. In fact, Huttunen and Niskanenâ&#x20AC;&#x2122;s results were so statistically significant (six cases of schizophrenia in the tested group versus just one in the control), that potential designs flaws were a non-factor.

One should take note of a couple caveats with regard to the seemingly conclusive results exhibited by these studies. Firstly, the tested populations for the majority of these studies were very small, and while some authors controlled for this shortcoming, many did not. Secondly, as mentioned several times, these studies do not prove a direct causal relationship between schizophrenia and stress.

While the studies explored here hypothesize that stress triggers some maternal, biological reaction that adversely affects the fetus, Huttunen and Niskanen (1978) bring up a possibly confounding variable when they studied the environment in which the child is reared. They point out that the fatherless child still has to be raised by a widowed mother, who may be very emotionally insecure and thus distance herself from the child, contributing to the risk of mental illness. Lastly, studies that contradict the evidence presented above do indeed exist. In one such study, children in gestation during the Arab-Israeli War of 1967 were found to have no greater susceptibility to schizophrenia than any other child (Selten et al., 2003). This study is in direct contradiction to the work done by Malaspina et al. (2008), a conflict which demonstrates some of the major disagreements regarding evidence for the possible prenatal origins of schizophrenia.

Future research studies on stress factors should be conducted similarly to the ones mentioned above but on different events throughout the century and not just those pertaining to one major event (like World War II). Researchers should ensure that these findings are not merely isolated incidents relevant to a decade or two around 1950.

Further tests of this correlation should also be globalized to include non-Western populations since the vast majority of research has so far taken place in Western nations.

Conclusion Fetal environmental alteration is one of the few easily identifiable and possibly preventable factors that is shown to contribute to the onset of schizophrenia. For example, if a pregnant mother becomes infected with the T. Gondii virus, the child has a much greater risk of developing schizophrenia in adulthood (Ledgerwood et al., 2003). T. Gondii has its origins in cats, so eliminating a schizophrenia risk factor may be as simple as controlling a pregnant womanâ&#x20AC;&#x2122;s exposure to felines ( Jackson and Hutchison, 1989). Other viruses and illnesses that heighten schizophrenia susceptibility may be similarly preventable, such as via an an42 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review nual flu shot or taking simple hygienic precautions during the winter. The Mayo Clinic even recommends that pregnant women get an annual flu shot regardless to lower the chance of birth complications resulting from the flu (Harms, 2010). Likewise, prenatal malnutrition may be rather straightforward to guard against, but researchers note that once the fetus is deprived of certain nutrients, the effects are irreversible (Morgane et al., 1992). Severe maternal stress may be more difficult to counteract though, as extreme stressors like war and the death of a loved one are often out of the motherâ&#x20AC;&#x2122;s hands. Nevertheless, by identifying and acting on the stress soon after it occurs, future researchers may at least be able to limit its effects. Ways to ease the stress may include therapy for the mother, learning particular coping skills, or even removing her from the stress-inducing environment altogether. In conclusion, stopping adverse fetal environmental changes can be seen as an all-or-nothing way of reducing the risk of schizophrenia; one damaging influence can cause a domino effect on future brain development, and thus make the development of a healthy brain nearly impossible. If future research reveals that the above prenatal environmental variations have a direct, causal relationship to schizophrenia, simple acts such as limiting viral exposure, maintaining a proper diet, and avoiding stress when possible could put a significant dent in the prevalence of schizophrenia.

Barr, C, & Mednick, S. (1990). Exposure to influenza epidemics during gestation and adult schizophrenia.Archive of General Psychology, 47, 869874.

Boksa, P. (2010). Effects of prenatal infection on brain development and behavior: a review of findings from animal models. Brain, Behavior, and Immunity, 24, 881-897.

Brown, A, & Begg, M. (2004). Serological evidence for prenatal influenza in the etiology of schizophrenia.Archive of General Psychology, 61, 774780.

Brown, A., & Susser, E. (2002). In utero infection and adult schizophrenia.

Mental Retardation Development Disability, 8, 51-57 Brown, A., & Susser, E. (2008). Prenatal nutritional deficiency and risk of adult schizophrenia. Schizophrenia Bulletin, 34(6), 1054-1063.

Cannon T.D, Rosso L, Hollister J, Bearden C, Sanchez L, Hadley T. (2000).

A prospective cohort study of genetic and perinatal influences in the etiology of schizophrenia. Schizophrenia Bulletin, 26(2), 351-366.

Cintra L, Granados L, Aguilar A, Kemper T, DeBassio W, Galler J, Morgane P, Duran P & Diaz-Cintra S. et al. (1997). Effects of prenatal protein malnutrition on mossy fibers of the hippocampal formation in rats of four age groups. Hippocampus,7, 184-191.

Dauncey, M.J., & Bicknell, R.J. (1999). Nutrition and neurodevelopment: mechanisms of developmental dysfunction and disease in later life. Nutrition Research Reviews, (12), 231-253.

Debassio, WA, Kemper TL, Tonkiss J & Galler JR. et al. (1996). Effects of prenatal protein deprivation on postnatal granule cell generation in the hippocampal dentate gyrus. Brain Research Bulletin, 41, 379-383.

Edwards, M. (1986). Hypothermia as a teratogen: a review of experimental studies and their clinical significance. Teratogenesis Carcinog Mutigen., 6, 563-582.

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Karson, C. (1996). Nitric oxide synthase (nos) in schizophrenia: increases in cerebellar vermis.Molecular Chemistry Neuropatholgy, 27, 275-284.

Khasan, A, Abel, K, McNamee, R, Pedersen, M, Webb, R, Baker, P, Kenny, L, Mortensen, P. (2008). Higher risk of offspring schizophrenia following antenatal maternal exposure to severe life events. Archive of General Psychology, 65(2), 146-152.

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Stein Z, Susser M, Saenger G, Marolla F. (1975). Famine and human development.Oxford University Press Uno, H, Eisele, S, & Sakai, A. (1994). Neurotoxicity of glucocorticoids in the primate brain. Hormones and Behavior, 28, 335-348. van Os, J, & Selten, JP. (1998). Prenatal exposure to maternal stress and subsequent schizophrenia. the may 1940 invasion of the netherlands. British Journal of Psychiatry, 172, 324-326.

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Schizophrenia: An autoimmune disease?

Joshua Coulter1 University of Auckland, Auckland, 1010, New Zealand Correspondence should be addressed to Joshual Coulter (jcou047@aucklanduni.ac.nz) 1

Introduction Schizophrenia, a neurological condition affecting close to 1% of the population (Goldsmith & Rogers, 2008), can be diagnosed in a patient based on the presence of positive and negative symptoms and cognitive dysfunction (Strous & Shoenfeld, 2006). Positive symptoms refer to a gain of function such as delusions and hallucinations (Goldsmith & Rogers, 2008); negative symptoms to a loss of function such as an inability to derive pleasure from everyday activities (anhedonia) (Strous & Shoenfeld, 2006) and to cognitive dysfunction, including altered behavior and thought patterns (Monji et al., 2012).

A number of theories exist as to the likely causes of schizophrenia, each with its merit in partially explaining the aetiology of the disease. Plausible theories include the role of genetics, as evidenced by twin studies (Goldsmith & Rogers, 2008), the psychosocial role of the environment (i.e. the stress-diathesis model) (Walker & Diforio, 1997), and a possible element of neurodegeneration due to prenatal or postnatal viral infections or brain damage (Goldsmith & Rogers, 2008; Monji et al., 2012). Thus far however, these hypotheses have been unable to provide a thorough enough explanation for the diseaseâ&#x20AC;&#x2122;s induction and progression (Goldsmith & Rogers, 2008).

A viable theory is that of the possibility that schizophrenia, or at least certain subsets of the condition, may in fact be an autoimmune disease (AD) (i.e. there is a failure of self-tolerance) (Goldsmith & Rogers, 2008). In particular, it appears that neuroinflammation and immune-genetic interactions may be involved in the pathogenesis (Monji et al., 2012). This review shall hence briefly examine the validity of this hypothesis with respect to specific criteria relating to the potential classification of schizophrenia as an AD. Family history of AD One feature of schizophrenia that suggests it could be an AD is the apparent genetic susceptibility and greaterthan-otherwise expected rates of appearance in families (Goldsmith & Rogers, 2008; Heward & Gough, 1997).

The hypothesis gains further credibility through the observation that there is an increase in ADs in general in relatives of those with schizophrenia (Strous & Shoenfeld, 2006). If afflicted with an AD, there is a 45% increase in the risk of developing schizophrenia (Strous & Shoenfeld, 2006). An exception to this however is in the case of 44 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

Rheumatoid Arthritis (RA), for which a negative association exists (Freudenreich et al., 2010; Strous & Shoenfeld, 2006). It has been suggested that the two may share a common mechanism of development and that upon acquiring one, a patient becomes somewhat immune to the other (Freudenreich et al., 2010; Strous & Shoenfeld, 2006).

This may be due to a weakened helper T-cell type 1 (TH1) response in favour of an enhanced type 2 (TH2) response in schizophrenia; consequently, there is contracted cytotoxic T-cell activity which bears relevance since RA may be caused by a self-reactive cytotoxic response (Freudenreich et al., 2010). A study by Gilvarry et al. has also shown both thyrotoxicosis and type I diabetes to be more prevalent in the relatives of psychotic patients (Gilvarry et al., 1995). Most notably, it was revealed that thyrotoxicosis rates were five-fold greater in mothers of schizophrenic patients relative to a control sample (Gilvarry et al., 1995).

These results, in conjunction with evidence that many ADs demonstrate a familial pattern of inheritance or susceptibility (Gilvarry et al., 1995; Goldsmith & Rogers, 2008), suggest an autoimmune component to schizophrenia.

Association with the human leukocyte antigen The human leukocyte antigen (HLA) is a distinct region of the major histocompatibility complex (MHC) and has been shown to have an immunoregulatory role (Debnath, Cannon, & Venkatasubramanian, 2012). HLA genes are involved in the formation of antigen presentation complexes (APCs) and, significantly, in helping the immune system discriminate between self and non-self (Debnath et al., 2012; Goldsmith & Rogers, 2008). A number of HLA polymorphs have been correlated with schizophrenia and in particular, circulating levels of HLA-A10, -A11 and -A29 antigens have been shown to be elevated in some cases of adult-onset schizophrenia (Goldsmith & Rogers, 2008); conversely, HLA-A2 levels have been shown to be lower (Goldsmith & Rogers, 2008). There are however a number of concerns with this. Firstly, a positive association does not necessarily mean causation and while some HLA antigens are elevated in other ADs (e.g. multiple sclerosis (MS) and type I diabetes), it does not mean they are the underlying risk factors for the development of schizophrenia (Debnath et al., 2012; Goldsmith & Rogers, 2008). Secondly, these same increases and decreases have not been ubiquitously observed (Debnath

OpiniOn et al., 2012) and it appears that circulating antigen levels may vary with the type of schizophrenia (Goldsmith & Rogers, 2008). Finally, studies of juvenile-onset schizophrenia have not observed any statistically significant correlation between the disease and HLA classes 1 and 2 (Goldsmith & Rogers, 2008). As such this suggests, at the very least, that the association with HLA antigen expression may only be significant in certain subsets of the condition (Goldsmith & Rogers, 2008). Nevertheless, it cannot be denied that due to the essential role of the MHC in immune function and the likely influence of HLA molecules on a number of neurobiological processes (Boulanger, 2009; Debnath et al., 2012), it is probable that MHC region variations may in some way be a determining risk factor for some types of schizophrenia (Goldsmith & Rogers, 2008). Therefore, it is reasonable to state this provides support for the possibility that schizophrenia may possess an element of immune compromise.

Presence of immune cells to defined surface antigen A key aspect of any AD is the presence of specific immune cells or antibodies (ABs) to a defined surface antigen, relevant to the disease process. A number of brain structures have been highlighted as potential targets for specific ABs; most notably the hippocampus and amygdala, linked to paranoid symptomology (Carter et al., 1998; Goldsmith & Rogers, 2008), and the frontal cortex, linked to the cognitive dysfunction resulting from hypofrontality (Carter et al., 1998; Goldsmith & Rogers, 2008). This has been in part evidenced by increased circulating levels of S100B, shown to be an appropriate marker for central nervous system (CNS) tissue damage (Monji et al., 2012).

Furthermore, a fairly consistent finding in many studies is that secretion of pro-inflammatory cytokines such as IL-6 and TNF- by cells of the CNS is upregulated (Naudin, Capo, Giusano, Mege, & Azorin, 1997). These increased levels indicate an ongoing inflammatory process and thus may reflect immune-mediated destruction of CNS targets (Naudin et al., 1997). In particular, the increased IL-6 is strongly correlated to the disease status (Naudin et al., 1997) and, at least in other ADs, may exacerbate disease progression through facilitating IgG synthesis and augmenting disturbances of the blood brain barrier (Strous & Shoenfeld, 2006). It has also been proposed that several neurotransmitters and their receptors may be targets for the elevated levels of ABs in schizophrenia (Goldsmith & Rogers, 2008), which is feasible given the altered signalling function in the disease (Monji et al., 2012). Whilst it is difficult to say with certainty that the altered levels of cytokine and AB expression directly reflects an autoimmune process; it is conceivable that autoreactive mediated destruction of CNS targets could underpin the disease pathophysiology. Thus, schizophrenia might well be classified as an AD, particularly when considering the

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increased IL-6 expression and how this may relate to the associated neurodegenerative traits (Monji et al., 2012).

Transmission of disease to animals It has been previously demonstrated that ADs can be experimentally induced in animals following the direct transfer of T cells or ABs from an afflicted individual, a process now integral in the classification of ADs (Heath & Krupp, 1968). Upon isolation of a plasma protein from schizophrenic patients, dubbed â&#x20AC;&#x2DC;taraxeinâ&#x20AC;&#x2122; (an immunoglobulin), it was possible to induce psychotic activity in monkeys and humans (Heath & Krupp, 1968). Subsequent studies on monkeys using purified IgG from patients revealed similar findings; however, psychotic effects were also found to be induced with IgG from controls, albeit at one third the prevalence, which was not detected previously (Heath & Krupp, 1968). In addition, the psychosis was usually accompanied by a neurodegeneration that was qualitatively alike to that in schizophrenics (Heath & Krupp, 1968). Despite the observation that schizophreniclike effects could be induced in controls (Heath & Krupp, 1968), these results suggest that in some instances, transfer of ABs can be sufficient for disease induction, thus substantiating the claim that schizophrenia could be an AD. Clinical response to immunotherapy If schizophrenia is indeed an AD, it could be presumed that it may be responsive to immunotherapy, as with other ADs. No direct benefits of plasmapharesis have yet been observed (Strous & Shoenfeld, 2006); it has been reported, however, that the efficacy of some antipsychotics may be due to an immunosuppressive effect (Monji et al., 2012; Strous & Shoenfeld, 2006). Olanzapine can cause an elevation in CD8+ levels and a diminished CD4:CD8 ratio and as such may inhibit the production ABs through increased numbers of T-suppressors (Goldsmith & Rogers, 2008; Richard & Brahm, 2012). Antipsychotics may also downregulate the release of cytokines from microglia in the CNS (Monji et al., 2012), thereby possibly offsetting some of the associated neuroinflammatory aspects of the condition (Monji et al., 2012). Despite these findings, problems exist in differentiating between the neuromodulatory and immunomodulatory contributions to overall clinical benefit (Goldsmith & Rogers, 2008). In addition, studies examining selective COX-2 inhibitors have yielded some insight into the possible autoimmune component of schizophrenia (Freudenreich et al., 2010).

In particular, celecoxib has proven therapeutically beneficial, particularly when administered in conjunction with risperidone (Freudenreich et al., 2010; Richard & Brahm, 2012). Whilst not all patients respond to these treatments, possibly because not all schizophrenia subsets are characterised by immune dysfunction (Richard & Brahm, 2012), the evidence does suggest that immunosuppressive Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 45

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and anti-inflammatory effects can lead to improvements.

Conclusion The evidence discussed certainly provides credibility to the hypothesis that schizophrenia may be an autoimmune disease, or at least that it may possess a significant immunological component. It must be acknowledged that some of the data may appear conflicting at times and that the puzzle is far from solved. A steady observation, however, is that there are alterations in the levels of immune mediators in patients that seem to correlate to some specific symptoms as opposed to others (Monji et al., 2012; Strous & Shoenfeld, 2006). It is likely, therefore, that the autoimmune component will be further realised in its relation to genetic and psychosocial interactions, and that an autoimmune aetiology will be more relevant to certain disease subtypes rather than as an explanation for all forms of schizophrenia.

Boulanger, L. M. (2009). Immune proteins in brain development and synaptic plasticity. Neuron, 64, 93-109.

Carter, C. S., Perlstein, W., Ganguli, R., Brar, J., Mintun, M., & Cohen, J. D. (1998). Functional Hypofrontality and Working Memory Dysfunction in Schizophrenia. The American Journal of Psychiatry, 155(9), 1285-1287.

Debnath, M., Cannon, D. M., & Venkatasubramanian, G. (2012). Variation in the major histocompatibility complex (MHC) gene family in schizophrenia: Associations and functional implications. Progress in Neuro-Pharmacology & Biological Psychiatry.

Freudenreich, O., Brockman, M. A., Henderson, D. C., Evins, A. E., Fan, X., Walsh, J. P., & Goff, D. C. (2010). Analysis of peripheral immune activation in schizophrenia using quantitative reverse-transcriptase polymerase chain reaction (RT-PCR). Psychiatry Research, 176, 99-102.

Gilvarry, C. M., Sham, P. C., Jones, P. B., Cannon, M., Wright, P., Lewis, S. W., . . . Murray, R. M. (1995). Family history of autoimmune diseases in psychosis. Schizophrenia Research, 19(1), 33-40.

Goldsmith, C. W., & Rogers, D. P. (2008). The Case for Autoimmunity in the Etiology of Schizophrenia. Pharmacotherapy, 28(6), 730-741.

Heath, R. G., & Krupp, I. M. (1968). Schizophrenia as a Specific Biologic Disease. The American Journal of Psychiatry, 124(8), 1019-1027.

Heward, J., & Gough, S. C. (1997). Genetic Susceptibility to the Development of Autoimmune Disease. The Journal of Clinical Science (London), 93(6), 479-491 Monji, A., Kato, T. A., Mizoguchi, Y., Horikawa, H., Seki, Y., Kasai, M., . . . Kanba, S. (2012). Neuroinflammation in schizophrenia especially focused on the role of microglia. Progress in Neuro-Pharmacology & Biological Psychiatry.

Naudin, J., Capo, C., Giusano, B., Mege, J. L., & Azorin, J. M. (1997). A differential role for interleukin-6 and tumor necrosis factor-alpha in schizophrenia? Schizophrenia Research, 26, 227-233.

Richard, M. D., & Brahm, N. C. (2012). Schizophrenia and the immune system: Pathophysiology, prevention, and treatment. American Journal of Health-System Pharmacists, 69, 757-766.

Strous, R. D., & Shoenfeld, S. (2006). Schizophrenia, autoimmunity and immune system dysregulation: A comprehensive model updated and revisited. Journal of Autoimmunity, 27, 71-80.

Walker, E. F., & Diforio, D. (1997). Schizophrenia: A Neural DiathesisStress Model. Psychological Review, 104(4), 667-685.

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Huntington’s disease: A monogenic mystery Han Jun Kim1 Duke University, Durham, North Carolina 27708 Correspondence should be addressed to Han Jun Kim (hjkim7156@gmail.com) 1

Huntington’s disease (HD) is a complex neurodegenerative disorder caused by expansion of CAG repeats in the Huntington gene. Despite identification of the mutation responsible for the disease, a specific molecular pathway for the disease remains to be identified by various models of study. Challenging aspects of treating HD include: its delayed onset, and subtle cognitive and motor symptoms. This review will attempt to briefly cover current molecular theories for Huntington pathogenesis, models used for supporting these theories, and current treatment options and future directions Introduction HD is a complex neurodegenerative disorder that to this day, eludes investigators attempting to parse its pathogenesis. While HD is similar to other neurodegenerative disorders in that it is caused by protein misfolding, it has its share of unique characteristics that clearly sets it apart (Ross & Tabrizi, 2011). Unlike similar neurodegenerative disorders like Parkinson’s disease (PD), or Alzheimer’s disease (AD), HD is monogenic and fully penetrant (Ross & Tabrizi, 2011). Prevalence of HD is about 4~10 per 100,000 which is much less than the prevalence of PD or AD (Ross & Tabrizi, 2011). However as an autosomal dominant disorder with full penetrance only requiring one copy of the mutant allele, any offspring of the affected individual has a 50% chance of inheriting the disease (Novak & Tabrizi, 2011). This somewhat unique high penetrance makes HD one of the most commonly inherited neurodegenerative diseases (Munoz-Sanjuan & Bates, 2011).

Symptoms of HD include a variety of motor, cognitive, and psychiatric dysfunctions. While cognitive and psychiatric symptoms can develop years before motor symptoms during the prodromal period, a typical patient is considered somewhat arbitrarily as asymptomatic until the motor symptoms are apparent (Novak & Tabrizi, 2011).

Some of the cognitive symptoms include: trouble communicating, perceptual distortion, and difficulty planning and initiating thoughts (Novak & Tabrizi, 2011). Psychiatric symptoms can include depression, obsessive compulsive disorder, anxiety and psychosis (Novak & Tabrizi, 2011).

However formal clinical diagnosis of HD is made on identification of motor signs like chorea (involuntary jerking of muscles), dystonia (involuntary sustained contracture of muscle), or bradykinesia (slowed muscle movement) (Novak & Tabrizi, 2011). Although chorea usually manifests earlier, later motor disabilities such as bradykinesia are more functionally disabling (Novak & Tabrizi, 2011).

Molecular basis of Huntington’s disease I. Gene pathology The pathogenic symptoms of HD are caused by ex-

pansion of CAG repeats in the Huntington gene (HTT), which is located on the short arm of chromosome 4 (Cisbani & Cicchetti, 2012). While the normal wild-type HTT gene has 34 copies of CAG repeats, mutant HTT (mHTT) has 35 copies and above, with over 40 copies threshold for full penetrance (Ross & Tabrizi, 2011). However those in range between 36~40 copies of CAG repeats may or may not develop HD, but those who do are likely to have later onset (Ross & Tabrizi, 2011). The length of the CAG repeats is negatively correlated with the age of onset and accounts for approximately 60~70% of the variance, but seem to contribute less to determine the rate of progression (Munoz-Sanjuan & Bates, 2011). The allele carrier for HD can be identified prior to the development of disease (Munoz-Sanjuan & Bates, 2011). This presents a unique model for studying disease-modifying therapies and developing intervention strategies that could be applied to other neurodegenerative disease that have heterogeneous genetic factors (Munoz-Sanjuan & Bates, 2011).

II. HTT protein Huntington’s gene encodes for the large Huntington’s protein that consists mainly of amino acid repeats termed HEAT repeats. HEAT repeats are made up of 50 amino acids that form antiparallel alpha helices in a helical hairpin configuration (Ross & Tabrizi, 2011). Biochemical analysis suggests Huntington protein interacts with many partners at its N-terminus, which hints it serves as a scaffold to coordinate complexes of other proteins (Ross & Tabrizi, 2011). However the cellular functions of HTT protein are still not fully understood. Studies have indicated HTT protein is associated with organelles involved in intracellular trafficking, and plays a role in proteins involved in synaptic functions (Cisbani & Cicchetti, 2012).

Other studies speculate a possible role in gene transcription and RNA trafficking (Novak & Tabrizi, 2011). Overexpression of normal HTT in cultured striatal mouse cells has demonstrated HTT’s ability to protect against apoptosis and excitotoxicity (Cisbani & Cicchetti, 2012).

Mutant Huntington (mHTT) protein on the other Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 47

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hand, has abnormal beta sheet conformation due to its expanded polyglutamine stretches in the N-terminus domain (Cisbani & Cicchetti, 2012). Evidences from range of biochemical and animal models suggest that these abnormal mHTT proteins are toxic and cause pathogenic symptoms of HD (Ross & Tabrizi, 2011). However, there is some controversy regarding the specificity of its toxicity.

The expanded polyglutamine stretches at the N-terminus were shown to cause the alteration of the HTT protein and its toxicity (Cisbani & Cicchetti, 2012). However, there is evidence that shorter fragments of these N-terminus domains are more toxic than the longer fragments (Ross & Tabrizi, 2011). Others argue that longer fragments lead to more insoluble aggregates that ultimately lead to HD pathogenesis (Cisbani & Cicchetti, 2012). In the case of AD, shorter fragments have been known to be more toxic than the actual amyloid plaques (Cisbani & Cicchetti, 2012). However specific mechanism of mHTT toxicity is still poorly understood, and requires further investigation.

III. Possible pathogenic mechanisms Although the molecular mechanisms behind toxicity of mHTT are still not quite understood, one of the most consistent features of the disease across different models of study is the neuronal atrophy in the select regions of the brain (Ross & Tabrizi , 2011). While there is neuronal death in cerebral cortex, thalamus, and other brain regions, there is relatively massive neuronal atrophy in the striatum (Ross & Tabrizi, 2011). Specifically there is up to 95% loss of GABAergic medium spiny neurons that project to globus pallidus and the substantia nigra (Ross & Tabrizi, 2011). The pathogenic suspect mHTT protein aggregates are present in various regions of these neurons such as nucleus, cytoplasm, dendrites, and axon

review terminals (Figure 1). However the density of these visible aggregates does not correlate well with distribution of cell death (Ross & Tabrizi, 2011). It begs the question of why there is such selective death in the striatum even though HTT is expressed throughout brain and body.

Some studies have postulated that these aggregates might not be actual pathogens responsible for neuronal atrophy, but rather a neuroprotective response to some other actual toxic pathogen (Ross & Tabrizi, 2011). This conundrum behind causative mechanism of mHTT makes it difficult to zone in on the best therapeutic approach for HD. In the next section, we will outline some the characteristics of the research models used to address such questions.

Research models of Huntingtonâ&#x20AC;&#x2122;s disease I. Cellular/bacterial models Cell lines are valuable models for HD research as they allow direct examination of the molecular processes linking mHTT protein aggregation to possible disease mechanisms. They can be manipulated by investigators for transient, stable, and inducible expression strategies (Ross & Tabrizi, 2011). While some cell lines are used for biochemical analysis of the HTT and mHTT protein conformation, other uses of cell lines include investigation of HTT protein interactions with other molecular factors in vitro. Primary neurons share many features of neurons in vivo, therefore cultures, co-cultures, or mixed cultures of neuronal cells can reproduce some of the cellular interactions (Ross & Tabrizi, 2011). However this method will most likely not display the complex interaction of a fullyfledged neuronal circuit. Relatively recent development of pluripotent stem cells derived from Huntingtonâ&#x20AC;&#x2122;s patients are being explored for possible therapeutic screening and disease pathogenesis (Devine, Ryten, Vodicka, Thomson & Figure 1: Possible Huntingtonâ&#x20AC;&#x2122;s disease pathogenesis in brain cell. mHTT (blue structure) with expanded polyglutamine repeat (red fragment) undergoes conformational change and interferes with cellular trafficking, including BDNF (brain-derived neurotrophic factor). mHTT is then cleaved into toxic fragments in beta conformation, which then can form oligomers and inhibit dendrites, chaperones, proteasomes, and autophagy. There might be interactions between mHTT and mitochondria. Pathogenic inclusion bodies have been found at the nucleus. These inclusions have been known to interfere with gene transcription of BDNF. Other interactions of mHTT and other proteins are currently unknown.

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review Burdon, 2011) . A goal will be to determine if the affected individuals who carry the mutant allele show any cellular phenotypic changes prior to onset of the disease symptoms.

II. Animal models Animal models allow for a wide array of in vivo/in vitro studies not possible in any other research models. Some of the methods used to investigate HD today include: electrophysiology, pharmacology, immunoblotting, confocal microscopy, and in situ hybridization (Ross & Tabrizi, 2011). Large mammalian models similar in anatomy to humans could have advantages for studying behaviors and motor symptoms of HD (Ross & Tabrizi, 2011). However this paper will focus on the mouse model as it is the one of the most widely used for studying various facets of HD. After all, the first intranuclear inclusions were discovered in mouse models prior to their discovery in human postmortem brain (Ross & Tabrizi, 2011). The primary goal of using mouse models has been to determine the therapeutic window of efficacy due to decreased mHTT and adverse effects that might be triggered by insufficient wild type HTT (Ross & Tabrizi, 2011). Another prevalent question regarding the mouse model has been to try to determine the differential effects of the full-length HTT and the Nterminal fragments of HTT (Ross & Tabrizi, 2011). Mice expressing full-length HTT have shown to generally have slightly more subtle phenotypes of HD, and have more selective neurodegeneration (Ross & Tabrizi, 2011). On the other hand, mice expressing N-terminal fragments of HTT seem to have more rapid progression of the disease phenotype (Ross & Tabrizi, 2011). All of these studies however, require significant commitment of time and resources since the disease phenotype progresses slowly and is often subtle (Ross & Tabrizi, 2011). Slightly more mechanistic studies of Huntington pathogenesis using mouse models have revealed the neuronal signaling deficiencies present in HD. Bibb et al. performed a number of investigations on the striatal medium spiny neurons that showed consistently that these neurons were dysfunctional in presymptomatic mice (Bibb, Yan, Svenningsson, Snyder & Pieribone, 2000). These defects most likely contribute to aberrant dopaminergic neurotransmission, as can be seen from Bibb et al’s data that clearly show wild-type mice’s D1 dopamine receptor reduces the calcium current when dopamine is applied (Bibb, Yan, Svenningsson, Snyder & Pieribone, 2000) . For mice with HD, the D1 dopamine receptor is barely able to alter the calcium current (Bibb, Yan, Svenningsson, Snyder & Pieribone, 2000).

III. Clinical trials No amount of cell and animal models of disease can be truly helpful to patients with HD, unless they are shown to lead to beneficial effects in human clinical trials. Currently, clinical trials for HD are aimed at symptom treatment and

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disease modification. Symptoms management treatment options are aimed at improving patients’ quality of life, by using drugs or behavioral therapies that help curtail the disease symptoms (Novak & Tabrizi, 2011). Disease-modifying treatments aim to halt or to slow the progression of the disease (Novak & Tabrizi, 2011). Unfortunately, so far there have been no disease-modifying clinical trials that have shown efficacy (Novak & Tabrizi, 2011). A variety of symptom management treatment options do exist for patients, but there is little basic science literature to support them, and they are given to patients based on clinical data (Novak & Tabrizi, 2011). One treatment that has shown to work consistently is tetrabenazine, which has shown efficacy in reducing chorea in HD patients (Novak & Tabrizi, 2011). However this only addresses a motor symptom of HD, and there are other classes of drugs designed to alleviate cognitive and psychiatric symptoms with wide array of side effects (Novak & Tabrizi, 2011).

A relatively new branch of clinical study that has garnered attention is identification of biomarkers for HD before the actual onset of the disease (Bohanna, Georgiou-Karistianis, Hannan & Egan, 2008). MRI, fMRI, and DTI are tools already used in clinical settings and it is possible that using these neuroimaging techniques could yield biomarkers that are consistent with early HD progression.

Possible treatment approaches and future directions I. Targeting the mHTT While the mechanism for mHTT protein’s toxicity remains elusive to investigators, nevertheless it makes sense that getting rid of mHTT protein should be a viable option for treatment. Since the genetic nature of HD is monogenic, somehow modifying the mutations on just the HTT gene seems like a right direction for potential treatments. One approach to modifying the mHTT gene is to use gene silencing techniques to selectively control the aberrant mHTT protein expression (Andre, Wild & Tabrizi, 2012). While there are different techniques for gene silencing, two most prominent ones are using RNA interference and antisense oligonucleotide compounds (Carroll, Warby, Southwell, Doty & Greenlee, 2011). The chemistry involved is slightly different between the two but the essential principle is same in that they both modify the gene expression and reduce the selected gene’s protein translation by binding to the mRNA (Franich, Fitzsimons, Fong, Klugmann, During & Young, 2008). However targeting the mHTT gene presents a whole host of new difficulties. The most pressing issue is safety of the gene silencing techniques. While there is little debate in utility of silencing the mHTT gene, there are questions that remain regarding the safety of silencing normal HTT gene as well. While it is possible to use SNPs as bio markers and hit the mutant HTT, that limits treatable patients with those who have those specific SNPs (Nasir, Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 49

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Floresco, Okusky, Diewert & Richman, 1995). Previous studies have shown that complete knockout of HTT is lethal for embryos, thus this approach warrants further caution and research in animal models before implementing in clinical trials (Nasir, Floresco, Okusky, Diewert & Richman, 1995). While a study with Rhesus macaques successfully maintained partial HTT suppression without any negative effects, there might be a role for human HTT not present in other primates (McBride, Pitzer, Boudreau, Dufour & Hobbs, 2011). Therefore, further insight of human HTT function is needed from cell models for this approach to proceed to actual clinical stages.

II. Restoring protein homeostasis Another possible approach to reduce the amount of aberrant mHTT protein from forming is to help the HTT protein fold correctly in the first place using chaperone proteins. Labbadia et al. has developed transgenic mice that overexpress the DNAJB2, gene that codes for HSJ1 chaperone protein (Labbadia, Novoselov, Bett, Weiss & Paganetti, 2012). Immunohistochemistry assays performed on these mice showed that overexpression of molecular chaperone HSJ1 protein can facilitate correct folding of mHTT protein and suppress the aggregation of the mutant HTT complexes (Labbadia, Novoselov, Bett, Weiss & Paganetti, 2012). In-vitro studies on mouse cell lines also demonstrated that overexpression of bacterial chaperone proteins GroEL, MC7, and Hsp104 reduce mHTT aggregation and neuronal death (Carmichael, Chatellier, Woolfson, Milstein, Fersht & Rubinsztein, 2000). Reducing the expression of mHTT has corresponded to modest recovery of behavioral and pathological function (Ross & Tabrizi, 2011). Overall, these studies show that modifying chaperone function and expression could be a valid therapeutic strategy by increasing the ratio of normal HTT protein to abnormal mHTT protein.

III. Other possible targets The approaches suggested so far have directly targeted the mHTT, and manipulated its expression in neuronal cells. However knowing there are varieties of molecular complexes that interact with the HTT protein, a viable approach might be to target these complexes to possibly attenuate the mHTT toxicity in neurons. Downstream effects of targeting such molecules have shown possible therapeutic effects. One such candidate molecule that has shown promising results for HD therapy is methylene blue.

Methylene blue has shown to have several roles in cellular processes, including as a modulator of protein aggregation (Gura, 2008). Methylene blue also has qualities that make it ideal for human brain treatment. Not only is it soluble in aqueous solutions and able to cross blood-brain barrier, but its toxicity is very low (Gura, 2008). While the specific biochemical mechanisms are currently unknown, data 50 | neurogenesisjournal.com | Spring 2013 | Vol 2 Issue 2

review from mice models consistently showed that methylene blue not only decreased levels of aggregation of HTT, but also decreased the size of the aggregations as well (Gura, 2008). In AD, Methylene blue has already successfully completed Phase IIb clinical trials and patients exhibited improved cognitive function after 6 months of treatment and slowed progression of the disease by 81 % over a 1 year period (Gura, 2008). All of these results strengthen the overall therapeutic potential of methylene blue for HD. Another alternative approach for disease intervention is to look for physiological conditions that have an effect on disease pathogenesis and investigate the factors affecting those conditions. One example of this approach in practice is the investigation of calorie restriction ameliorating HD pathogenesis (Duan, Guo, Jiang, Ware, Li & Mattson, 2003). In mouse models, calorie restriction has shown to attenuate HTT toxicity and slow HD progression (Duan, Guo, Jiang, Ware, Li & Mattson, 2003).

Overexpression of sirtuin1 (Sirt1), which mediates calorie restriction in cellular metabolism, was found to protect neurons against mHTT toxicity in mice models ( Jiang, Wang, Fu, Du & Jeong, 2012). Sirt1 overexpression also improved motor function and reduced metabolic abnormalities in HD mice ( Jiang, Wang, Fu, Du & Jeong, 2012). These findings support Sirt1 has a neuroprotective role in HD pathogenesis and points way for future research in association studies that could possibly reveal other factors that could mediate HD pathogenesis.

Conclusion While there are few successful treatment options for HD, current research demonstrates possible approaches that can lead to therapeutic interventions. Cell line and animal models are currently being utilized for identification of elusive mechanisms of HD pathogenesis, while clinical trials are attempting to find treatment options that can alleviate disease symptoms. While current treatment options are mostly not effective at curtailing disease symptoms, possible candidates are currently being targeted for research. Researchers have attempted to target the mHTT protein by reducing its translation in cells via gene silencing techniques. Another possible approach under investigation is to restore cellular protein homeostasis by overexpressing chaperone proteins that could aid in correct folding of mHTT proteins. While both approaches show signs of possible clinical utility, the most promising therapy candidates consist of Sirt1 and methylene blue, both of which have shown to improve symptoms of HD in animal trials and clinical trials. Further investigation of specific functions of HTT and mHTT can shed insight into other possible therapeutic agents that might be able to mediate the toxic effects of mHTT. Andre R, Wild EJ, Tabrizi SJ. 2012. Huntingtonâ&#x20AC;&#x2122;s disease: fighting on many fronts. Brain 135:998-1001

review

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Bibb JA, Yan Z, Svenningsson P, Snyder GL, Pieribone VA, et al. 2000. Severe deficiencies in dopamine signaling in presymptomatic Huntington’s disease mice. Proceedings of the National Academy of Sciences of the United States of America 97:6809-14 Bohanna I, Georgiou-Karistianis N, Hannan AJ, Egan GF. 2008. Magnetic resonance imaging as an approach towards identifying neuropathological biomarkers for Huntington’s disease. Brain research reviews 58:209-25 Carmichael J, Chatellier J, Woolfson A, Milstein C, Fersht AR, Rubinsztein DC. 2000. Bacterial and yeast chaperones reduce both aggregate formation and cell death in mammalian cell models of Huntington’s disease.

Proceedings of the National Academy of Sciences of the United States of America 97:9701-5 Carroll JB, Warby SC, Southwell AL, Doty CN, Greenlee S, et al. 2011. Potent and Selective Antisense Oligonucleotides Targeting Single-Nucleotide Polymorphisms in the Huntington Disease Gene/Allele-Specific Silencing of Mutant Huntingtin. Mol Ther 19:2178-85 Cisbani G, Cicchetti F. 2012. An in vitro perspective on the molecular mechanisms underlying mutant huntingtin protein toxicity. Cell Death Dis 3:e382 Devine MJ, Ryten M, Vodicka P, Thomson AJ, Burdon T, et al. 2011. Parkinson’s disease induced pluripotent stem cells with triplication of the alpha-synuclein locus. Nat Commun 2 Duan WZ, Guo ZH, Jiang HY, Ware M, Li XJ, Mattson MP. 2003. Dietary restriction normalizes glucose metabolism and BDNF levels, slows disease progression, and increases survival in huntingtin mutant mice.

Proceedings of the National Academy of Sciences of the United States of America 100:2911-6 Franich NR, Fitzsimons HL, Fong DM, Klugmann M, During MJ, Young D. 2008. AAV vector-mediated RNAi of mutant huntingtin expression is neuroprotective in a novel genetic rat model of Huntington’s disease.

Mol Ther 16:947-56 Gura T. 2008. Hope in Alzheimer’s fight emerges from unexpected places.

Nat Med 14:894 Jiang ML, Wang JW, Fu JR, Du L, Jeong H, et al. 2012. Neuroprotective role of Sirt1 in mammalian models of Huntington’s disease through activation of multiple Sirt1 targets. Nat Med 18:153-8 Labbadia J, Novoselov SS, Bett JS, Weiss A, Paganetti P, et al. 2012.

Suppression of protein aggregation by chaperone modification of high molecular weight complexes. Brain 135:1180-96 McBride JL, Pitzer MR, Boudreau RL, Dufour B, Hobbs T, et al. 2011. Preclinical Safety of RNAi-Mediated HTT Suppression in the Rhesus Macaque as a Potential Therapy for Huntington’s Disease. Mol Ther 19:2152-62 Munoz-Sanjuan I, Bates GP. 2011. The importance of integrating basic and clinical research toward the development of new therapies for Huntington disease. J Clin Invest 121:476-83 Nasir J, Floresco S, Okusky J, Diewert V, Richman J, et al. 1995. Targeted Disruption of the Huntingtons-Disease Gene Results in Embryonic Lethality in Homozygotes and Behavioral and Neuropathological Defects in Heterozygotes. Am J Hum Genet 57:265 Novak MJ, Tabrizi SJ. 2010. Huntington’s disease. Bmj 340:c3109 Ross CA, Tabrizi SJ. 2011. Huntington’s disease: from molecular pathogenesis to clinical treatment. Lancet Neurol 10:83-98

Vol 2 Issue 2 | Spring 2013 | neurogenesisjournal.com | 51

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Kelly R. Murphy

Rory Lubner

Editor-in-Chief

Editor-in-Chief

Biqi Zhang

Tiffany Chien

Publishing Editor

Ha Tran Managing Editor

Design Editor

Bean Sharif-Askary Managing Editor

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Neurogenesis

Editors Undergraduate Publication Board

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