Dataset Information

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

ABSTRACT: BACKGROUND:Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). METHODS:We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. RESULTS:As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. CONCLUSIONS:Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

SUBMITTER: Keown CL

PROVIDER: S-EPMC5607014 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

Keown Christopher L CL Datko Michael C MC Chen Colleen P CP Maximo José Omar JO Jahedi Afrooz A Müller Ralph-Axel RA

Biological psychiatry. Cognitive neuroscience and neuroimaging 20170101 1

<h4>Background</h4>Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of <i>atypical network distribution</i> in ASD (i.e., participation of unusual loci in distributed functional networks).<h4>Methods</h4>We used a selective high-quality data subset from the ABIDE dat ...[more]

PMID: 28944305

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Project description:Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6?±?1.8 years old) and 31 healthy controls (15.4?±?1.6 years old). Data from 22 participants with ASD (13.1?±?3.1 years old) and 21 healthy controls (12.9?±?2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy?=?83%; ASD dataset: accuracy?=?80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p?=?0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776-1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY:Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders.

Dataset Information

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

Publications

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

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