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Analysis Of The Key Neurocognitive Features Of AttentionDeficit/Hyperactivity Disorder (ADHD).
Definition Attention-deficit/hyperactivity disorder (ADHD) is defined and characterised based upon a pattern of behaviour which is present in an individual in multiple different settings (American Psychiatric Association, 2013). ADHD is neurodevelopmental in character and as such the pattern of behaviour which is seen to indicate the presence of the disorder is relative to the age of individual in question (Sroubek et al., 2013). In order for the disorder to be diagnosed, there must be substantial behavioural problems of attention deficit and/or hyperactivity/impulsive action which are judged to be inappropriate for the age of the individual in question (Childress & Berry, 2012). Children must present with a minimum of six symptoms relating to attention deficit and/or hyperactivity/impulsivity criteria, whereas more developed adolescents and adults (individuals over the age of seventeen) must present with a minimum of five symptoms (American Psychiatric Association, 2013). This is a useful way of defining and characterising ADHD in that these behavioural symptoms can be easily identified by observation without the need for any specialised equipment; however there is a significant overlap of behavioural symptoms indicative of ADHD with behavioural symptoms indicative of other conditions (Lake & Dulcan, 2011), and this can lead to difficulty and confusion when it comes to diagnosis. For example, some of the other prevalent conditions which are characterised by many of the same symptoms as ADHD include bipolar disorder, anxiety disorder, dissociative disorder, and personality disorder (American Psychiatric Association, 2013).
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Aetiology The aetiology of ADHD is a source of contention (Thapar et al., 2013). Both genetic and environmental factors have been strongly correlated with the symptoms of ADHD (Millichap & Gordon, 2010). The results of twin studies have been suggested to indicate that genetics represent the primary causal factor in up to 70% of ADHD cases (Naele et al., 2010). One gene alone, the LPHN3 gene, is suggested to be the cause behind 9% of all cases of ADHD (Arcos-Burgos & Muenke, 2010). In general, environmental factors are seen to be a lesser predictor; however there are still many different environmental risk factors which have been strongly and significantly linked to the development of ADHD (Arcos-Burgos & Muenke, 2010). For example, being exposed to smoke from tobacco during pregnancy has been shown to increase the risk of a child going on to develop ADHD (Abbott & Winzer-Serhan, 2012). Likewise, premature birth has been linked to increased risk (Thapar et al., 2012). However, it is important to remember that ADHD is a condition characterised by a number of different behavioural symptoms (as I have previously outlined). Both the genetic and environmental factors positively correlated with the development of ADHD are in fact positive correlates of various combinations of different behavioural symptoms of ADHD – each one essentially the product of a pattern of cognitive functioning. As such, each of the different genes which have been positively correlated with the development of ADHD may only promote a specific area of neurocognitive development, which can be related to the development of specific traits, which in turn can present as symptoms of ADHD (Cardo et al., 2010). Thus, it can be explained why the presence of an individual gene associated with the development of ADHD does not always lead to the development of ADHD, as the neurocognitive traits promoted by the gene in question may be seen to be non-problematic on their own and only indicative of ADHD when combined with other neurocognitive traits promoted by other genes (Cardo et al., 2010). Likewise, regular consumption of alcohol during pregnancy can cause foetal
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alcohol spectrum disorder which involve many behavioural symptoms of ADHD but does not necessarily lead to the development of ADHD (Burger et al., 2010). Once again, this is because ADHD involves a number of different neurocognitive functions being affected and the neurodevelopmental damage done by foetal alcohol spectrum disorder will not necessarily affect enough of these neurocognitive functions to lead to the range of behavioural symptoms required to diagnose ADHD. As such, it is evident that in order to establish a clearer aetiology of ADHD, we must direct our focus to the specifics of the neurological structures and processes which underlie the various combinations of different behavioural symptoms of ADHD. Once these neurological structures and neurocognitive processes are better understood, we can potentially seek to establish a common link which would represent a more clearly defined aetiology of ADHD.
Cognitive Deficits Broadly speaking, the cognitive deficits involved in ADHD have to do with an individual’s capacity to be attentive, and an individual’s impulsiveness (Gray, 2010). However, each of these cognitive features can be broken down further into more elemental cognitive processes. Attention can be broken down into three sub-domains including “alerting, orienting and executive attention” (Van Leishout et al., 2013), and individuals with ADHD may display deficits in any or all of these areas. Alerting is “the ability to attain and maintain a state of high sensitivity in anticipation of a stimulus” (Van Leishout et al., 2013) and it is essential in allowing an individual to react efficiently to an incoming stimulus. Orienting is the ability to scan and select relevant information from one’s sensory input (Van Leishout et al., 2013). Executive attention is strongly related to, and often wholly equated to, interference control – which is also an important cognitive process in determining an individual’s impulsiveness (Van Leishout et al., 2013). However, with the exception of executive attention, deficits with
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the cognitive processes of attention are not seen to be as significant a predictor of ADHD as deficits with processes involved with impulsiveness (Gray, 2010). The cognitive processes involved with impulsiveness are vast; including the ability to suppress a potentially distracting stimulus, the ability to temporarily store and manipulate information which is useful for achieving a certain goal, and the ability to plan and sequence behaviour and alter it based upon perceived errors (Van Leishout et al., 2013). Deficits in these areas are seen to have a strong correlation with ADHD (Van Leishout et al., 2013). Furthermore, there are cognitive processes involved with impulsiveness whereby deficits are seen to have a strong negative correlation with ADHD, such as the ability to quickly alternate between mental sets (Van Lieshout et al., 2013). It has been suggested that it is these cognitive deficits (the ones that lead to impulsiveness) which underlie “all or most of the distinguishing behavioural characteristics (shown by individuals with ADHD)” (Grey, 2010). This notion can be roughly summarised as follows: Impulsiveness leads to individuals being easily distracted and so they are seen to be inattentive; it leads them to be impatient and unable to sit still and so they are seen to be hyperactive (Grey, 2010).
Structural Brain Abnormalities Structurally, the areas of the brain that appear to be most essential to the cognitive capacities (or a lack thereof) which are related to ADHD lie “within the prefrontal lobes of the cerebral cortex and in connections between the prefrontal cortex and other parts of the brain – including the striatum and the basal ganglia” (Grey, 2010). These areas are known to be involved in initiating and inhibiting actions (Haines, 2013) and as such they are involved with the cognitive processes that determine whether or not an individual is impulsive (and to what degree). This is congruent with the notion that impulsiveness is a stronger predictor of ADHD than attention deficit. Research has suggested that individuals who are seen to have
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ADHD may often have slightly diminished neural mass within the areas of the prefrontal cortex relative to other people who do not have ADHD (Grey, 2010). However, it must be noted that the vast majority of the individuals in the ADHD groups who have been used in this research have a history of being treated with (anti-ADHD) stimulant drugs which operate primarily within the prefrontal cortex, and so Grey (2010) suggests that we cannot be sure whether the observed brain differences correlate to the condition of ADHD or the long-term effects of the stimulant drugs. The involvement of the prefrontal cortex in cases of ADHD is not in question here, and drug treatments which target the dopamine pathways of this area have been seen to be effective in treating the condition (Huang et al., 2012). Rather, it simply casts doubt over whether or not the neuro-structural differences noted in individuals with ADHD are actually down to the condition itself. Recent research has suggested that structural damage/abnormality in areas outside of the prefrontal cortex may also be linked to ADHD, with Lee & Goto (2013) noting a correlation between damage to the habenula and certain behavioural symptoms of ADHD. This area is associated with reward processing (Haines, 2013) which, once again, is a cognitive process that suggested to be significantly involved in determining the impulsivity of an individual (Ripke et al., 2012). As such, this is further evidence of the significance of neurocognitive areas relating to impulsive behaviour and their strong relation to cases of ADHD. It is also worth noting, however, that other recent studies have linked the presence of ADHD to reduced bilateral thalamic volumes, and this is suggested to be a result of the thalamus’ involvement in visual attention (Xia et al., 2012). As such, the significance of neurocognitive areas relating to attention and their relation to cases of ADHD cannot be ignored.
Functional Brain Abnormalities Functionally, the prefrontal cortex has also been widely observed to play an important role in
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cases of ADHD. Groom et al. (2010) used EEG to measure the neural response to errors in participants with ADHD as opposed to a control group. It was noted that, in participants with ADHD, there were significantly weaker error-related signals traveling from the anterior cingulate cortex to the pre-frontal cortex (Groom et al., 2010). It was suggested that these weaker error-related signals traveling to the pre-frontal cortex might signify a difficulty to process and adapt one’s responses in relation to poor performance and that this may be a significant underlying factor of general poor inhibitory performance in individuals with ADHD (Groom et al., 2010). Fallgatter et al. (2013) used EEG in a similar study, however this time the abnormal error-related signals were also positively correlated with the presence of the LPHN3 gene, perhaps giving us an insight into why the gene has long been seen to play a role in the development of ADHD (Arcos-Burgos & Muenke, 2010). Abnormal functional activations in many areas of the pre-frontal cortex have also been noted in a number of fMRI studies. For example, abnormal functional activations have been demonstrated in the orbitofrontal cortex (Bush, 2010), which has been linked to impulse control (De La Fuente et al., 2013); and in structures of the cingulo-fronto-pariental network (Bush, 2011), within which the fronto-striatal and fronto-parietal pathways “are thought to be the primary substrate for most attention functions” (De La Fuente et al., 2013). This again serves as evidence for the significance of neurocognitive areas relating to not just impulsiveness, but also attention, in cases of ADHD. However, there are also a number of areas outside the region of the prefrontal cortex which have been shown to play a role in ADHD… In a meta-analytic review of diffusor tensor imaging studies, Van Ewijk (2012) identified functional deficits in the basal ganglia (particularly in the striatum) as a significant correlate of ADHD. De La Fuente et al. (2013) suggest that these “impairments of the striatum and its brain connections are associated with the hyperactivity/impulsivity component” of ADHD. Additionally, a series of fMRI studies by Li et al. (2012), Xia et al.
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(2012), and Shaw (2012) have collectively demonstrated a very strong correlation between abnormal connectivity in thalamic regions and the development of ADHD. Conclusion I have explained how ADHD is characterised by a number of different and distinct behavioural symptoms. Various cognitive deficits underlie these different and distinct behavioural symptoms, and these cognitive deficits are themselves the result of various structural and/or functional brain abnormalities. However, these behavioural symptoms, cognitive deficits, and structural and/or functional brain abnormalities are often not specific to the condition of ADHD (Lake & Dulcan, 2011; American Psychiatric Association, 2013). As such, there is a common issue which undermines the method behind of all of the studies which I have referred to in this essay; each study attempts to look at specific genetic/environmental/neuro-structural/neuro-functional features and link them in general to the condition of ADHD. However, as a condition which is defined by a vague assemblage of different behavioural symptoms, it is inept to attempt to link such specific causes to what is in fact a highly variable behavioural effect. Rather than seeking to project these specific genetic/environmental/neuro-structural/neuro-functional features towards a correlation with the vague condition of ADHD, we should pay closer attention the specific cognitive deficits with which they correlate – cognitive deficits which may play an elemental role in many conditions other than the umbrella-like ADHD.
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Reference List:Abbott, LC; Winzer-Serhan, UH (Apr 2012). "Smoking during pregnancy: lessons learned from epidemiological studies and experimental studies using animal models". Crit Rev Toxicol 42 (4): 279–303. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. Arcos-Burgos M, Muenke M (November 2010). "Toward a better understanding of ADHD: LPHN3 gene variants and the susceptibility to develop ADHD". Atten Defic Hyperact Disord 2 (3): 139–47. Burger, PH; Goecke, TW; Fasching, PA; Moll, G; Heinrich, H; Beckmann, MW; Kornhuber, J (Sep 2011). "Einfluss des mütterlichen Alkoholkonsums während der Schwangerschaft auf die Entwicklung von ADHS beim Kind" [How does maternal alcohol consumption during pregnancy affect the development of attention deficit/hyperactivity syndrome in the child]. Fortschr Neurol Psychiatr (in German) 79 (9): 500–6. Bush G. (2010). Attention-deficit/hyperactivity disorder and attention networks. Neuropsychopharmacology 35 278–300. Bush G. (2011). Cingulate, frontal, and parietal cortical dysfunction in attentiondeficit/hyperactivity disorder. Biol. Psychiatry 69 1160–1167. Cardo E, Nevot A, Redondo M, et al. (March 2010). "Trastorno por déficit de atención/hiperactividad: ¿un patrón evolutivo?" [Attention deficit disorder and hyperactivity: a pattern of evolution?]. Rev Neurol (in Spanish; Castilian). 50 Suppl 3: S143–7. Childress, AC; Berry, SA (2012 Feb 12). "Pharmacotherapy of attention-deficit hyperactivity disorder in adolescents". Drugs 72 (3): 309–25. De La Fuente, A., Xia, S., Branch, C., & Li, X. (2013). A Review of AttentionDeficit/Hyperactivity Disorder From the Perspective of Brain Networks. Front Hum Neurosci. 2013; 7: 192. Fallgatter, A. J., Ehlis, A. C., Dresler, T., Reif, A., Jacob, C. P., Arcos-Burgos, M., Muenke, M., & Lesch, K. P. (2013). Influence of a Latrophilin 3 (LPHN3) risk haplotype on eventrelated potential measures of cognitive response control in attention-deficit hyperactivity disorder (ADHD). Eur Neuropsychopharmacol. 2013 Jun;23(6): pp.458-68. Gray, P. (2010). The “ADHD Personality”: Its Cognitive, Biological, and Evolutionary Foundations. Retrieved from: http://www.psychologytoday.com/blog/freedomlearn/201008/the-adhd-personality-its-cognitive-biological-and-evolutionary-foundations Groom, M. J., Cahill, J. D., Jackson, G. M., Calton, T. G., Liddle, P. F., & Hollis, C. (2010). Electrophysiological indices of abnormal error-processing in adolescents with attention deficit hyperactivity disorder (ADHD). Journal of Child Psychology & Psychiatry. Jan2010, Vol. 51 Issue 1, p66-76.
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Haines, D. E. (2013). Fundamental neuroscience for basic and clinical applications. Philadelphia: Elsevier/Saunders. Huang, Y. S., Wang, L. J., & Chen, C. K. (2012). Long-term neurocognitive effects of methylphenidate in patients with attention deficit hyperactivity disorder, even at drug-free status. BMC Psychiatry. 2012, Vol. 12 Issue 1, p194-100. Lake, M. K., & Dulcan, M. (2011). Concise guide to child and adolescent psychiatry (4th ed.). Washington, DC: American Psychiatric Pub. p. 34. Lee, Y. A, & Goto, Y. (2013). Habenula and ADHD: Convergence on time. Neuroscience & Biobehavioral Reviews. Sep2013, Vol. 37 Issue 8, p1801-1809. Li X., Sroubek A., Kelly M. S., Lesser I., Sussman E., He Y., et al. (2012). Atypical pulvinarcortical pathways during sustained attention performance in children with attentiondeficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry 51 1197–1207. Millichap, J. Gordon (2010). Attention Deficit Hyperactivity Disorder Handbook a Physician's Guide to ADHD (2nd ed.). New York, NY: Springer Science. p. 26. Neale, BM; Medland, SE; Ripke, S; Asherson, P; Franke, B.; Lesch, KP; Faraone, SV; Nguyen, TT; Schäfer, H et al. (Sep 2010). "Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder". J Am Acad Child Adolesc Psychiatry 49 (9): 884– 97. Ripke, S., Hübner, T., Mennigen, E., Müller, K.U., Rodehacke, S., Schmidt, D., Jacob, M.J., & Smolka, M.N. (2012). Reward Processing and Intertemporal Decision Making in Adults & Adolescents: The Role of Impulsivity and Decision Consistency. Brain Research. Oct 10; 1478, pp.36-47. Shaw P. (2012). Attention-deficit/hyperactivity disorder and the battle for control of attention. J. Am. Acad. Child Adolesc. Psychiatry 51 1116–1118. Sroubek, A; Kelly, M; Li, X (2013 Feb). "Inattentiveness in attention-deficit/hyperactivity disorder". Neuroscience bulletin 29 (1): 103–10. Thapar A, Cooper M, Eyre O, Langley K (January 2013). "What have we learnt about the causes of ADHD?". J Child Psychol Psychiatry 54 (1): 3–16. Thapar, A.; Cooper, M.; Jefferies, R.; Stergiakouli, E. (Mar 2012). "What causes attention deficit hyperactivity disorder?". Arch Dis Child 97 (3): 260–5. Van Ewijk H. (2012). Diffusion tensor imaging in attention deficit/hyperactivity disorder: a systematic review and meta-analysis. Neurosci. Biobehav. Rev. 36 1093–1106. Van Lieshout, M., Luman, M., Buitelaar, J., Rommelse, N. N. J., & Oosterlaan, J. (2013) Does Neurocognitive Functioning Predict Future or Persistence of ADHD? A systematic review. Clinical Psychology Review. Vol. 33, Issue 4, pp.539-560.
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Xia S., Li X., Kimball A. E., Kelly M. S., Lesser I., Branch C. (2012). Thalamic shape and connectivity abnormalities in children with attention-deficit/hyperactivity disorder. Psychiatry Res. 204 161–167.
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