The cortical underconnectivity theory asserts that reduced long-range functional connectivity might contribute to a neural mechanism for autism. We examined resting-state blood oxygen level-dependent interhemispheric correlation in 53 males with high-functioning autism and 39 typically developing males from late childhood through early adulthood. By constructing spatial maps of correlation between homologous voxels in each hemisphere, we found significantly reduced interhemispheric correlation specific to regions with functional relevance to autism: sensorimotor cortex, anterior insula, fusiform gyrus, superior temporal gyrus, and superior parietal lobule. Observed interhemispheric connectivity differences were better explained by diagnosis of autism than by potentially confounding neuropsychological metrics of language, IQ, or handedness. Although both corpus callosal volume and gray matter interhemispheric connectivity were significantly reduced in autism, no direct relationship was observed between them, suggesting that structural and functional metrics measure different aspects of interhemispheric connectivity. In the control but not the autism sample, there was decreasing interhemispheric correlation with subject age. Greater differences in interhemispheric correlation were seen for more lateral regions in the brain. These findings suggest that long-range connectivity abnormalities in autism are spatially heterogeneous and that transcallosal connectivity is decreased most in regions with functions associated with behavioral abnormalities in autism. Autism subjects continue to show developmental differences in interhemispheric connectivity into early adulthood.

The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3-36 years) and 60 males with typical development (mean age = 18 years; range 4-39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and paracentral, lateral orbitofrontal, and lateral occipital regions. We suggest that abnormal cortical development in autism spectrum disorders undergoes three distinct phases: accelerated expansion in early childhood, accelerated thinning in later childhood and adolescence, and decelerated thinning in early adulthood. Moreover, cortical thickness abnormalities in autism spectrum disorders are region-specific, vary with age, and may remain dynamic well into adulthood.

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.

LAY ABSTRACT Since the impairments associated with autism spectrum disorder (ASD) tend to persist or worsen from childhood into adulthood, it is of critical importance to examine how the brain develops over this growth epoch. We report initial findings on whole and regional longitudinal brain development in 100 male participants with ASD (226 high-quality MRI scans) compared to 56 typically developing male controls (TDCs) (117 high-quality scans) from childhood into adulthood, for a total of 156 participants scanned over an eight-year period. We provide volumetric growth curves for the entire brain, total gray matter (GM), frontal GM, temporal GM, parietal GM, occipital GM, total cortical white matter (WM), corpus callosum, caudate, thalamus, total cerebellum, and total ventricles. Mean volume of cortical WM was reduced significantly. Decreases in regional mean volumes in the ASD sample were most often due to decreases during late adolescence and adulthood. The growth curve of whole-brain volume showed increased volumes in young children with autism and subsequently decreased during adolescence to meet the TDC curve between 10 and 15 years of age. The volume of many structures continued to decline atypically into adulthood in the ASD sample. The data suggest that ASD is a dynamic disorder with complex changes in whole and regional brain volumes that change over time from childhood into adulthood. SCIENTIFIC ABSTRACT Since the impairments associated with autism spectrum disorder (ASD) tend to persist or worsen from childhood into adulthood, it is of critical importance to examine how the brain develops over this growth epoch. We report initial findings on whole and regional longitudinal brain development in 100 male participants with ASD (226 high-quality MRI scans; mean inter-scan interval 2.7 years) compared to 56 typically developing male controls (TDCs) (117 high-quality scans; mean inter-scan interval 2.6 years) from childhood into adulthood, for a total of 156 participants scanned over an eight-year period. This initial analysis includes between one and three high-quality scans per participant that have been processed and segmented to date, with 21% having one scan, 27% with two scans and 52% with three scans in the ASD sample; corresponding percentages for the TDC sample are 30%, 30%, and 40%. The proportion of participants with multiple scans (79% of ASDs and 68% of TDCs) was high in comparison to that of large longitudinal neuroimaging studies of typical development. We provide volumetric growth curves for the entire brain, total gray matter (GM), frontal GM, temporal GM, parietal GM, occipital GM, total cortical white matter (WM), corpus callosum, caudate, thalamus, total cerebellum, and total ventricles. Mean volume of cortical WM was reduced significantly. Mean ventricular volume was increased in the ASD sample relative to the TDCs across the broad age range studied. Decreases in regional mean volumes in the ASD sample most often were due to decreases during late adolescence and adulthood. The grow...

The arcuate fasciculus is a white matter fiber bundle of great importance in language. In this study, diffusion tensor imaging (DTI) was used to infer white matter integrity in the arcuate fasciculi of a group of subjects with high-functioning autism and a control group matched for age, handedness, IQ, and head size. The arcuate fasciculus for each subject was automatically extracted from the imaging data using a new volumetric DTI segmentation algorithm. The results showed a significant increase in mean diffusivity (MD) in the autism group, due mostly to an increase in the radial diffusivity (RD). A test of the lateralization of DTI measurements showed that both MD and fractional anisotropy (FA) were less lateralized in the autism group. These results suggest that white matter microstructure in the arcuate fasciculus is affected in autism and that the language specialization apparent in the left arcuate of healthy subjects is not as evident in autism, which may be related to poorer language functioning.