Xinyi Hu , Xiangyun Long , Jiaxin Wu , Na Liu , Nan Huang , Fei Liu , Ansi Qi , Qi Chen , Zheng Lu
{"title":"Dynamic modular dysregulation in multilayer networks underlies cognitive and clinical deficits in first-episode schizophrenia","authors":"Xinyi Hu , Xiangyun Long , Jiaxin Wu , Na Liu , Nan Huang , Fei Liu , Ansi Qi , Qi Chen , Zheng Lu","doi":"10.1016/j.neuroscience.2025.03.059","DOIUrl":null,"url":null,"abstract":"<div><div>Schizophrenia has been identified to exhibit significant abnormalities in brain functional networks, which are likely to underpin the cognitive and functional impairments observed in patients. Graph theoretical analysis revealed the disrupted modularity in schizophrenia, however, the dynamic network abnormalities in schizophrenia remains unclear. We collected the resting-state functional magnetic resonance imaging data from 82 first-episode schizophrenia (FES) patients and 55 healthy control (HC) subjects. Dynamic functional connectivity matrices were constructed and a multilayer network model was employed to run the dynamic modularity analysis. We also performed correlation analyses to investigate the relationship between flexibility, cognitive function and clinical symptoms. Our findings indicate that FES patients exhibit higher multilayer modularity. The node flexibility of FES patients were found elevated in several brain regions, which were included in the default mode network, fronto-parietal network, salience network and visual network. The node flexibility metrics in aberrant brain regions were found to demonstrate significant correlations with cognitive function and negative symptoms in patients with FES. These findings suggest a pathological imbalance in brain network dynamics, where abnormal modular organization might contribute to the cognitive impairment and functional deficits in schizophrenia.</div></div>","PeriodicalId":19142,"journal":{"name":"Neuroscience","volume":"573 ","pages":"Pages 315-321"},"PeriodicalIF":2.9000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306452225002611","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Schizophrenia has been identified to exhibit significant abnormalities in brain functional networks, which are likely to underpin the cognitive and functional impairments observed in patients. Graph theoretical analysis revealed the disrupted modularity in schizophrenia, however, the dynamic network abnormalities in schizophrenia remains unclear. We collected the resting-state functional magnetic resonance imaging data from 82 first-episode schizophrenia (FES) patients and 55 healthy control (HC) subjects. Dynamic functional connectivity matrices were constructed and a multilayer network model was employed to run the dynamic modularity analysis. We also performed correlation analyses to investigate the relationship between flexibility, cognitive function and clinical symptoms. Our findings indicate that FES patients exhibit higher multilayer modularity. The node flexibility of FES patients were found elevated in several brain regions, which were included in the default mode network, fronto-parietal network, salience network and visual network. The node flexibility metrics in aberrant brain regions were found to demonstrate significant correlations with cognitive function and negative symptoms in patients with FES. These findings suggest a pathological imbalance in brain network dynamics, where abnormal modular organization might contribute to the cognitive impairment and functional deficits in schizophrenia.
期刊介绍:
Neuroscience publishes papers describing the results of original research on any aspect of the scientific study of the nervous system. Any paper, however short, will be considered for publication provided that it reports significant, new and carefully confirmed findings with full experimental details.