Literature DB >> 34119524

Functional brain network dysfunctions in subjects at high-risk for psychosis: A meta-analysis of resting-state functional connectivity.

Lorenzo Del Fabro1, André Schmidt2, Lydia Fortea3, Giuseppe Delvecchio4, Armando D'Agostino5, Joaquim Radua6, Stefan Borgwardt7, Paolo Brambilla8.   

Abstract

Although emerging evidence suggests that altered functional connectivity (FC) of large-scale neural networks is associated with disturbances in individuals at high-risk for psychosis, the findings are still far to be conclusive. We conducted a meta-analysis of seed-based resting-state functional magnetic resonance imaging studies that compared individuals at clinical high-risk for psychosis (CHR), first-degree relatives of patients with schizophrenia, or subjects who reported psychotic-like experiences with healthy controls. Twenty-nine studies met the inclusion criteria. The MetaNSUE method was used to analyze connectivity comparisons and symptom correlations. Our results showed a significant hypo-connectivity within the salience network (p = 0.012, uncorrected) in the sample of CHR individuals (n = 810). Additionally, we found a positive correlation between negative symptom severity and FC between the default mode network and both the salience network (p < 0.001, r = 0.298) and the central executive network (p = 0.003, r = 0.23) in the CHR group. This meta-analysis lends support for the hypothesis that large-scale network dysfunctions represent a core neural deficit underlying psychosis development.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Clinical high risk; Functional connectivity; Large-scale networks; Meta-analysis; Psychosis; Salience network; fMRI

Year:  2021        PMID: 34119524     DOI: 10.1016/j.neubiorev.2021.06.020

Source DB:  PubMed          Journal:  Neurosci Biobehav Rev        ISSN: 0149-7634            Impact factor:   8.989


  4 in total

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2.  Wearing a KN95/FFP2 facemask induces subtle yet significant brain functional connectivity modifications restricted to the salience network.

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3.  Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders.

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4.  Focusing on Comorbidity-A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders.

Authors:  Lydia Fortea; Anton Albajes-Eizagirre; Yuan-Wei Yao; Edu Soler; Norma Verdolini; Alexander O Hauson; Adriana Fortea; Santiago Madero; Aleix Solanes; Scott C Wollman; Maria Serra-Blasco; Toby Wise; Steve Lukito; Maria Picó-Pérez; Christina Carlisi; JinTao Zhang; PingLei Pan; Álvar Farré-Colomés; Danilo Arnone; Matthew J Kempton; Carles Soriano-Mas; Katya Rubia; Luke Norman; Paolo Fusar-Poli; David Mataix-Cols; Marc Valentí; Esther Via; Narcis Cardoner; Marco Solmi; Jae I Shin; Eduard Vieta; Joaquim Radua
Journal:  Front Psychiatry       Date:  2022-01-18       Impact factor: 4.157

  4 in total

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