Resting state fMRI based multilayer network configuration in patients with schizophrenia
George Gifford1, Nicolas Crossley2, Matthew J Kempton1
1Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK.
Neuroimage. Clinical
|February 8, 2020
Summary
Schizophrenia patients exhibit altered brain network flexibility, with higher switching between communities in key brain regions. However, this flexibility may not be a superior biomarker compared to simpler measures.
Area of Science:
- Neuroscience
- Psychiatry
- Network Science
Background:
- Schizophrenia research requires novel biomarkers for dynamic brain organization.
- Previous studies suggest increased network flexibility in schizophrenia.
Purpose of the Study:
- To compare dynamic brain network flexibility between schizophrenia patients and controls.
- To explore novel methods like between resting state network synchronisation (BRSNS) for group differences.
Main Methods:
- Utilized dynamic modular organization modeling on the COBRE Dataset (55 patients, 72 controls).
- Applied BRSNS and transition probability analysis to resting state networks (RSNs).
Main Results:
- Significantly higher flexibility in schizophrenia patients within cerebellar, subcortical, and fronto-parietal task control RSNs.
- Elevated flexibility observed in the left thalamus and right crus I, reflecting altered community transitions.
Conclusions:
- Schizophrenia is associated with less stable dynamic community structure at RSN and node levels.
- Novel methods offer new ways to explore dynamic brain community structure.
- Flexibility's utility as a biomarker is limited, comparable to simpler measures.
