Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.

The processing of changing nonverbal social signals such as facial expressions is poorly understood, and it is unknown if different pathways are activated during effortful (explicit), compared to implicit, processing of facial expressions. Thus we used fMRI to determine which brain areas subserve processing of high-valence expressions and if distinct brain areas are activated when facial expressions are processed explicitly or implicitly. Nine healthy volunteers were scanned (1.5T GE Signa with ANMR, TE/TR 40/3,000 ms) during two similar experiments in which blocks of mixed happy and angry facial expressions ("on" condition) were alternated with blocks of neutral faces (control "off" condition). Experiment 1 examined explicit processing of expressions by requiring subjects to attend to, and judge, facial expression. Experiment 2 examined implicit processing of expressions by requiring subjects to attend to, and judge, facial gender, which was counterbalanced in both experimental conditions. Processing of facial expressions significantly increased regional blood oxygenation level-dependent (BOLD) activity in fusiform and middle temporal gyri, hippocampus, amygdalohippocampal junction, and pulvinar nucleus. Explicit processing evoked significantly more activity in temporal lobe cortex than implicit processing, whereas implicit processing evoked significantly greater activity in amygdala region. Mixed high-valence facial expressions are processed within temporal lobe visual cortex, thalamus, and amygdalohippocampal complex. Also, neural substrates for explicit and implicit processing of facial expressions are dissociable: explicit processing activates temporal lobe cortex, whereas implicit processing activates amygdala region. Our findings confirm a neuroanatomical dissociation between conscious and unconscious processing of emotional information.

BackgroundHuntington's disease (HD) is a fatal inherited neurodegenerative disease, caused by a

There is increasing evidence that children with autism spectrum disorder (ASD) have age-related differences from controls in cortical volume (CV). It is less clear, however, if these persist in adulthood and whether these reflect alterations in cortical thickness (CT) or cortical surface area (SA). Hence, we used magnetic resonance imaging to investigate the relationship between age and CV, CT, and SA in 127 males aged 10 through 60 years (76 with ASD and 51 healthy controls). "Regional" analyses (using cortical parcellation) identified significant age-by-group interactions in both CV and CT (but not SA) in the temporal lobes and within these the fusiform and middle temporal gyri. Spatially nonbiased "vertex-based" analysis replicated these results and identified additional "age-by-group" interactions for CT within superior temporal, inferior and medial frontal, and inferior parietal cortices. Here, CV and CT were 1) significantly negatively correlated with age in controls, but not in ASD, and 2) smaller in ASD than controls in childhood but vice versa in adulthood. Our findings suggest that CV dysmaturation in ASD extends beyond childhood, affects brain regions crucial to social cognition and language, and is driven by CT dysmaturation. This may reflect primary abnormalities in cortical plasticity and/or be secondary to disturbed interactions between individuals with ASD and their environment.

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