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Neuroimaging-based phenotyping of the autism spectrum

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Bernhardt,  Boris C.
Department Social Neuroscience, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, Canada;

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Valk,  Sofie L.
Department Social Neuroscience, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Bernhardt, B. C., Di Martino, A., Valk, S. L., & Wallace, G. L. (2017). Neuroimaging-based phenotyping of the autism spectrum. In Current Topics in Behavioral Neurosciences (pp. 341-355). Berlin: Springer. doi:10.1007/7854_2016_438.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002A-10EF-A
Abstract
Recent advances in neuroimaging have offered a rich array of structural and functional markers to probe the organization of regional and large-scale brain networks. The current chapter provides a brief introduction into these techniques and overviews their contribution to the understanding of autism spectrum disorder (ASD), a neurodevelopmental condition associated with atypical social cognition, language function, and repetitive behaviors/interests. While it is generally recognized that ASD relates to structural and functional network anomalies, the extent and overall pattern of reported findings have been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD (e.g., ‘early brain overgrowth hypothesis’, ‘amygdala theory’, ‘disconnectivity hypothesis’), none of these frameworks has been without controversy. Methodological sources of inconsistent results may include differences in subject inclusion criteria, variability in image processing, and analysis methodology. However, inconsistencies may also relate to high heterogeneity across the autism spectrum itself. It, therefore, remains to be investigated whether a consistent imaging phenotype that adequately describes the entire autism spectrum can, in fact, be established. On the other hand, as previous findings clearly emphasize the value of neuroimaging in identifying atypical brain morphology, function, and connectivity, they ultimately support its high potential to identify biologically and clinically relevant endophenotypes.