1. Dierker DL, Feczko E, Pruett JR, Jr., Petersen SE, Schlaggar BL, Constantino JN, Harwell JW, Coalson TS, Van Essen DC. {{Analysis of Cortical Shape in Children with Simplex Autism}}. {Cereb Cortex}. 2013.
We used surface-based morphometry to test for differences in cortical shape between children with simplex autism (n = 34, mean age 11.4 years) and typical children (n = 32, mean age 11.3 years). This entailed testing for group differences in sulcal depth and in 3D coordinates after registering cortical midthickness surfaces to an atlas target using 2 independent registration methods. We identified bilateral differences in sulcal depth in restricted portions of the anterior-insula and frontal-operculum (aI/fO) and in the temporoparietal junction (TPJ). The aI/fO depth differences are associated with and likely to be caused by a shape difference in the inferior frontal gyrus in children with simplex autism. Comparisons of average midthickness surfaces of children with simplex autism and those of typical children suggest that the significant sulcal depth differences represent local peaks in a larger pattern of regional differences that are below statistical significance when using coordinate-based analysis methods. Cortical regions that are statistically significant before correction for multiple measures are peaks of more extended, albeit subtle regional differences that may guide hypothesis generation for studies using other imaging modalities.
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2. Lam YG. {{Re-examining the cognitive phenotype in autism: A study with young Chinese children}}. {Res Dev Disabil}. 2013.
Deficits consistently found in autism include an impaired « theory of mind », weak central coherence, and deficits in executive function. The current study examined whether this traditional cluster of symptoms existed in a group of Chinese-speaking children with autism. Sixteen high-functioning, non-retarded children with autism were matched to 16 typically developing (TD) children on gender, non-verbal IQ and age. Non-verbal IQ’s of all participants were measured using the Raven Progressive Matrices. Each participant was tested individually on measures of « theory of mind », central coherence and executive function. Results indicated that most, but not all, participants with autism performed significantly poorer on two standard measures of first-order « theory of mind, » although there was no significant difference on two other measures of that domain. As expected, they performed significantly worse on executive function tasks. However, the hypothesis of weak central coherence in autism was not substantiated. There was no evidence that these three cognitive impairments co-existed in individuals with autism. More likely, each of these deficits appears singly or in pair instead of forming a cluster.
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3. McCray AT, Trevvett P, Frost HR. {{Modeling the Autism Spectrum Disorder Phenotype}}. {Neuroinformatics}. 2013.
Autism Spectrum Disorder (ASD) is highly heritable, and although there has been active research in an attempt to discover the genetic factors underlying ASD, diagnosis still depends heavily on behavioral assessments. Recently, several large-scale initiatives, including those of the Autism Consortium, have contributed to the collection of extensive information from families affected by ASD. Our goal was to develop an ontology that can be used 1) to provide improved access to the data collected by those who study ASD and other neurodevelopmental disorders, and 2) to assess and compare the characteristics of the instruments that are used in the assessment of ASD. We analyzed two dozen instruments used to assess ASD, studying the nature of the questions asked and items assessed, the method of delivery, and the overall scope of the content. These data together with the extensive literature on ASD contributed to our iterative development of an ASD phenotype ontology. The final ontology comprises 283 concepts distributed across three high-level classes, ‘Personal Traits’, ‘Social Competence’, and ‘Medical History’. The ontology is fully integrated with the Autism Consortium database, allowing researchers to pose ontology-based questions. The ontology also allows researchers to assess the degree of overlap among a set of candidate instruments according to several objective criteria. The ASD phenotype ontology has promise for use in research settings where extensive phenotypic data have been collected, allowing a concept-based approach to identifying behavioral features of importance and for correlating these with genotypic data.
