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Triple network hypothesis-related disrupted connections in schizophrenia: A spectral dynamic causal modeling analysis with functional magnetic resonance imaging.
- Source :
-
Schizophrenia research [Schizophr Res] 2021 Jul; Vol. 233, pp. 89-96. Date of Electronic Publication: 2021 Jul 09. - Publication Year :
- 2021
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Abstract
- Objective: The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients.<br />Methods: We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS).<br />Results: We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS.<br />Conclusions: Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.<br /> (Copyright © 2021. Published by Elsevier B.V.)
Details
- Language :
- English
- ISSN :
- 1573-2509
- Volume :
- 233
- Database :
- MEDLINE
- Journal :
- Schizophrenia research
- Publication Type :
- Academic Journal
- Accession number :
- 34246865
- Full Text :
- https://doi.org/10.1016/j.schres.2021.06.024