Functional network connectivity in early-stage schizophrenia.


Journal

Schizophrenia research
ISSN: 1573-2509
Titre abrégé: Schizophr Res
Pays: Netherlands
ID NLM: 8804207

Informations de publication

Date de publication:
04 2020
Historique:
received: 21 12 2018
revised: 16 01 2020
accepted: 20 01 2020
pubmed: 11 2 2020
medline: 22 6 2021
entrez: 11 2 2020
Statut: ppublish

Résumé

Schizophrenia is a disorder of altered neural connections resulting in impaired information integration. Whole brain assessment of within- and between-network connections may determine how information processing is disrupted in schizophrenia. Patients with early-stage schizophrenia (n = 56) and a matched control sample (n = 32) underwent resting-state fMRI scans. Gray matter regions were organized into nine distinct functional networks. Functional connectivity was calculated between 278 gray matter regions for each subject. Network connectivity properties were defined by the mean and variance of correlations of all regions. Whole-brain network measures of global efficiency (reflecting overall interconnectedness) and locations of hubs (key regions for communication) were also determined. The control sample had greater connectivity between the following network pairs: somatomotor-limbic, somatomotor-default mode, dorsal attention-default mode, ventral attention-limbic, and ventral attention-default mode. The patient sample had greater variance in interactions between ventral attention network and other functional networks. Illness duration was associated with overall increases in the variability of network connections. The control group had higher global efficiency and more hubs in the cerebellum network, while patient group hubs were more common in visual, frontoparietal, or subcortical networks. Thus, reduced functional connectivity in patients was largely present between distinct networks, rather than within-networks. The implications of these findings for the pathophysiology of schizophrenia are discussed.

Identifiants

pubmed: 32037204
pii: S0920-9964(20)30039-6
doi: 10.1016/j.schres.2020.01.023
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107-115

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors report no direct conflicts of interest with this study. AB serves as a consultant for Karuna Pharmaceuticals and BioXcel Therapeutics. NM is currently an employee with Eli Lilly and Company. During data collection and analysis, she was employed by the Indiana University School of Medicine, where she maintains an affiliation.

Auteurs

Tom A Hummer (TA)

Department of Psychiatry, Indiana University School of Medicine, United States of America; Indiana University Psychotic Disorders Program, Indiana University School of Medicine, United States of America. Electronic address: thummer@iupui.edu.

Matthew G Yung (MG)

Department of Psychiatry, Indiana University School of Medicine, United States of America.

Joaquín Goñi (J)

Center for Neuroimaging, Indiana University School of Medicine, United States of America; Weldon School of Biomedical Engineering, Purdue University, United States of America.

Susan K Conroy (SK)

Department of Psychiatry, Indiana University School of Medicine, United States of America.

Michael M Francis (MM)

Department of Psychiatry, Indiana University School of Medicine, United States of America.

Nicole F Mehdiyoun (NF)

Department of Psychiatry, Indiana University School of Medicine, United States of America.

Alan Breier (A)

Department of Psychiatry, Indiana University School of Medicine, United States of America.

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Classifications MeSH