Autism spectrum disorders (ASD) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, life-long nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. While the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE) – a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) datasets with corresponding structural MRI and phenotypic information from 539 individuals with ASD and 573 age-matched typical controls (TC; 7–64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 males with ASD and 403 male age-matched TC. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo and hyperconnectivity in the ASD literature; both were detected, though hypoconnectivity dominated, particularly for cortico-cortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASD (mid and posterior insula, posterior cingulate cortex), and highlighted less commonly explored regions such as thalamus. The survey of the ABIDE R-fMRI datasets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international datasets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Summary The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here we used repeated-measurement resting-state functional MRI to explore inter-subject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Inter-subject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.

Deletions and duplications of the recurrent ϳ600 kb chromosomal BP4 -BP5 region of 16p11.2 are associated with a broad variety of neurodevelopmental outcomes including autism spectrum disorder. A clue to the pathogenesis of the copy number variant (CNV)'s effect on the brain is that the deletion is associated with a head size increase, whereas the duplication is associated with a decrease. Here we analyzed brain structure in a clinically ascertained group of human deletion (N ϭ 25) and duplication (N ϭ 17) carriers from the Simons Variation in Individuals Project compared with age-matched controls (N ϭ 29 and 33, respectively). Multiple brain measures showed increased size in deletion carriers and reduced size in duplication carriers. The effects spanned global measures of intracranial volume, brain size, compartmental measures of gray matter and white matter, subcortical structures, and the cerebellum. Quantitatively, the largest effect was on the thalamus, but the collective results suggest a pervasive rather than a selective effect on the brain. Detailed analysis of cortical gray matter revealed that cortical surface area displays a strong dose-dependent effect of CNV (deletion Ͼ control Ͼ duplication), whereas average cortical thickness is less affected. These results suggest that the CNV may exert its opposing influences through mechanisms that influence early stages of embryonic brain development.

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Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) time-series reveals distinct coactivation patterns in the resting brain representing spatially coherent spontaneous fluctuations of the fMRI signal. Among these patterns, the so-called default-mode network (DMN) has been attributed to the ongoing mental activity of the brain during wakeful resting state. Studies suggest that many neuropsychiatric diseases disconnect brain areas belonging to the DMN. The potential use of the DMN as functional imaging marker for individuals at risk for these diseases, however, requires that the components of the DMN are reproducible over time in healthy individuals. In this study, we assessed the reproducibility of the DMN components within and between imaging sessions in 18 healthy young subjects (mean age, 27.5 years) who were scanned three times with two resting state scans during each session at 3.0 T field strength. Statistical analysis of fMRI time-series was done using ICA implemented with BrainVoyager QX. At all three sessions the essential components of the DMN could be identified in each individual. Spatial extent of DMN activity and size of overlap within and between sessions were most reproducible for the anterior and posterior cingulate gyrus. The degree of reproducibility of the DMN agrees with the degree of reproducibility found with motor paradigms. We conclude that DMN coactivation patterns are reproducible in healthy young subjects. Therefore, these data can serve as basis to further explore the effects of aging and neuropsychiatric diseases on the DMN of the brain.

Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration.

The connectivity architecture of the human brain varies across individuals. Mapping functional anatomy at the individual level is challenging, but critical for basic neuroscience research and clinical intervention. Using resting-state functional connectivity, we parcellated functional systems in an "embedding space" based on functional characteristics common across the population, while simultaneously accounting for individual variability in the cortical distribution of functional units. The functional connectivity patterns observed in resting-state data were mapped in the embedding space and the maps were aligned across individuals. A clustering algorithm was performed on the aligned embedding maps and the resulting clusters were transformed back to the unique anatomical space of each individual. This novel approach identified functional systems that were reproducible within subjects, but were distributed across different anatomical locations in different subjects. Using this approach for intersubject alignment improved the predictability of individual differences in language laterality when compared with anatomical alignment alone. Our results further revealed that the strength of association between function and macroanatomy varied across the cortex, which was strong in unimodal sensorimotor networks, but weak in association networks.