Journal
NEUROIMAGE-CLINICAL
Volume 24, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2019.101966
Keywords
Schizophrenia; Autism spectrum disorder; Classification; Dynamic functional connectivity (dFNC); Connectivity dynamics; Social cognition; Resting state fMRI
Categories
Funding
- National Institutes of Health (NIMH) [R01 MH095888]
- National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) [17525]
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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 crossvalidated 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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