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Resting state fMRI based multilayer network configuration in patients with schizophrenia.
Resting state fMRI based multilayer network configuration in patients with schizophrenia.
- Source :
-
NeuroImage. Clinical [Neuroimage Clin] 2020; Vol. 25, pp. 102169. Date of Electronic Publication: 2020 Jan 11. - Publication Year :
- 2020
-
Abstract
- Novel methods for measuring large-scale dynamic brain organisation are needed to provide new biomarkers of schizophrenia. Using a method for modelling dynamic modular organisation (Mucha et al., 2010), evidence suggests higher 'flexibility' (switching between multilayer network communities) to be a feature of schizophrenia (Braun et al., 2016). The current study compared flexibility between 55 patients with schizophrenia and 72 controls (the COBRE Dataset). In addition, novel methods of 'between resting state network synchronisation' (BRSNS) and the probability of transition from one community to another were used to further describe group differences in dynamic community structure. There was significantly higher schizophrenia group flexibility scores in cerebellar (F (1124) = 9.33, p (FDR) = 0.017), subcortical (F (1124) = 13.14, p (FDR) = 0.005), and fronto-parietal task control (F (1124) = 7.19, p (FDR) = 0.033) resting state networks (RSNs), as well as in the left thalamus (MNI XYZ: -2, -13, 12; F(1, 124) = 17.1, p (FDR) < 0.001) and the right crus I (MNI XYZ: 35, -67, -34; F (1, 124) = 19.65, p (FDR) < 0.001). Flexibility in the left thalamus reflected transitions between communities covering default mode and sensory-somatomotor RSNs. BRSNS scores suggested altered dynamic inter-RSN modular configuration in schizophrenia. This study suggests less stable community structure in a schizophrenia group at an RSN and node level and provides novel methods of exploring dynamic community structure. Mediation of group differences by mean time window correlation did however suggest flexibility to be no better as a schizophrenia biomarker than simpler measures and a range of methodological choices affected results.<br />Competing Interests: Declarations of Competing Interest The authors declare no competing interests for the current study.<br /> (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Adult
Cerebellum diagnostic imaging
Cerebral Cortex diagnostic imaging
Female
Gray Matter diagnostic imaging
Humans
Male
Middle Aged
Nerve Net diagnostic imaging
Schizophrenia diagnostic imaging
Cerebellum physiopathology
Cerebral Cortex physiopathology
Connectome methods
Gray Matter physiopathology
Magnetic Resonance Imaging methods
Nerve Net physiopathology
Schizophrenia physiopathology
Subjects
Details
- Language :
- English
- ISSN :
- 2213-1582
- Volume :
- 25
- Database :
- MEDLINE
- Journal :
- NeuroImage. Clinical
- Publication Type :
- Academic Journal
- Accession number :
- 32032819
- Full Text :
- https://doi.org/10.1016/j.nicl.2020.102169