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scMRI Reveals Large-Scale Brain Network Abnormalities in Autism

Overview of attention for article published in PLOS ONE, November 2012
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Title
scMRI Reveals Large-Scale Brain Network Abnormalities in Autism
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049172
Pubmed ID
Authors

Brandon A. Zielinski, Jeffrey S. Anderson, Alyson L. Froehlich, Molly B. D. Prigge, Jared A. Nielsen, Jason R. Cooperrider, Annahir N. Cariello, P. Thomas Fletcher, Andrew L. Alexander, Nicholas Lange, Erin D. Bigler, Janet E. Lainhart

Abstract

Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a 'posteriorization' of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI.

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The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
China 1 <1%
United States 1 <1%
Unknown 164 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 20%
Researcher 27 16%
Student > Bachelor 14 8%
Student > Master 13 8%
Professor 13 8%
Other 37 22%
Unknown 31 18%
Readers by discipline Count As %
Psychology 47 28%
Neuroscience 23 14%
Medicine and Dentistry 17 10%
Agricultural and Biological Sciences 12 7%
Social Sciences 5 3%
Other 23 14%
Unknown 42 25%