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Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder
Published on: April 22, 2015
Dynamic functional connectivity in schizophrenia and autism spectrum disorder: Convergence, divergence and
Liron Rabany1, Sophy Brocke1, Vince D Calhoun2
1Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA.
Background:
Over the recent years there has been a growing debate regarding the extent and nature of the overlap in neuropathology between schizophrenia (SZ) and autism spectrum disorder (ASD). Dynamic functional network connectivity (dFNC) is a recent analysis method that explores temporal patterns of functional connectivity (FC). We compared resting-state dFNC in SZ, ASD and healthy controls (HC), characterized the associations between temporal patterns and symptoms, and performed a three-way classification analysis based on dFNC indices.
Methods:
Resting-state fMRI was collected from 100 young adults: 33 SZ, 33 ASD, 34 HC. Independent component analysis (ICA) was performed, followed by dFNC analysis (window = 33 s, step = 1TR, k-means clustering). Temporal patterns were compared between groups, correlated with symptoms, and classified via cross-validated three-way discriminant analysis.
Results:
Both clinical groups displayed an increased fraction of time (FT) spent in a state of weak, intra-network connectivity [p < .001] and decreased FT in a highly-connected state [p < .001]. SZ further showed decreased number of transitions between states [p < .001], decreased FT in a widely-connected state [p < .001], increased dwell time (DT) in the weakly-connected state [p < .001], and decreased DT in the highly-connected state [p = .001]. Social behavior scores correlated with DT in the widely-connected state in SZ [r = 0.416, p = .043], but not ASD. Classification correctly identified SZ at high rates (81.8%), while ASD and HC at lower rates.
Conclusions:
Results indicate a severe and pervasive pattern of temporal aberrations in SZ (specifically, being "stuck" in a state of weak connectivity), that distinguishes SZ participants from both ASD and HC, and is associated with clinical symptoms.
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