{"title":"Cognitive Decision-Making Mechanisms in Schizophrenia based on Dynamic Amplitude-Locked Value and Theta-Band Brain Network Analysis.","authors":"Shuman Huang,Jintao Yao,Wanru Li,Yichen Yao,Zhengwei Xu,Zhenmeng Zhao","doi":"10.1111/nyas.70098","DOIUrl":null,"url":null,"abstract":"Schizophrenia is a severe psychiatric disorder that involves disrupted cognition, emotion, and behavior. Growing evidence links its pathophysiology to the impaired coupling of large-scale brain networks. Previous studies have shown that phase synchronization effectively maps functional connectivity in neuronal populations. However, amplitude-based approaches to constructing functional brain networks remain comparatively rare. To address this gap, this study employed the dynamic amplitude-locked value (DALV) method to construct functional connectivity networks from scalp electroencephalogram (EEG) signals and systematically analyzed abnormal neural oscillations of people with schizophrenia (PSZ, N = 46) and healthy controls (HC, N = 31). The experimental results showed that compared with HC: (1) P300 components were significantly elicited at the CPz and FCz electrode sites, with the amplitude markedly reduced in the PSZ. (2) The average power of the whole brain exhibited significantly increased activity in the theta frequency band (p < 0.001) in PSZ and increases within the theta band for the parietal, prefrontal, and left temporal regions. (3) The results of brain network analysis based on DALV showed that there was a significantly reduced node degree, clustering coefficient, local efficiency, and global efficiency of the network in PSZ.","PeriodicalId":8250,"journal":{"name":"Annals of the New York Academy of Sciences","volume":"16 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2025-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of the New York Academy of Sciences","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1111/nyas.70098","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Schizophrenia is a severe psychiatric disorder that involves disrupted cognition, emotion, and behavior. Growing evidence links its pathophysiology to the impaired coupling of large-scale brain networks. Previous studies have shown that phase synchronization effectively maps functional connectivity in neuronal populations. However, amplitude-based approaches to constructing functional brain networks remain comparatively rare. To address this gap, this study employed the dynamic amplitude-locked value (DALV) method to construct functional connectivity networks from scalp electroencephalogram (EEG) signals and systematically analyzed abnormal neural oscillations of people with schizophrenia (PSZ, N = 46) and healthy controls (HC, N = 31). The experimental results showed that compared with HC: (1) P300 components were significantly elicited at the CPz and FCz electrode sites, with the amplitude markedly reduced in the PSZ. (2) The average power of the whole brain exhibited significantly increased activity in the theta frequency band (p < 0.001) in PSZ and increases within the theta band for the parietal, prefrontal, and left temporal regions. (3) The results of brain network analysis based on DALV showed that there was a significantly reduced node degree, clustering coefficient, local efficiency, and global efficiency of the network in PSZ.
精神分裂症是一种严重的精神疾病,涉及认知、情感和行为的紊乱。越来越多的证据将其病理生理学与大规模大脑网络的受损耦合联系起来。先前的研究表明,相同步可以有效地映射神经元群体的功能连接。然而,基于振幅的方法来构建功能性大脑网络仍然相对罕见。为了解决这一空白,本研究采用动态锁幅值(DALV)方法从头皮脑电图(EEG)信号构建功能连接网络,系统分析了精神分裂症患者(PSZ, N = 46)和健康对照(HC, N = 31)的异常神经振荡。实验结果表明,与HC相比:(1)P300在CPz和FCz电极位置被显著激发,而在PSZ电极位置振幅明显降低。(2)全脑平均功率在PSZ的θ频带活动显著增加(p < 0.001),顶叶、前额叶和左颞叶的θ频带内活动显著增加。(3)基于DALV的脑网络分析结果表明,PSZ的节点度、聚类系数、局部效率和全局效率显著降低。
期刊介绍:
Published on behalf of the New York Academy of Sciences, Annals of the New York Academy of Sciences provides multidisciplinary perspectives on research of current scientific interest with far-reaching implications for the wider scientific community and society at large. Each special issue assembles the best thinking of key contributors to a field of investigation at a time when emerging developments offer the promise of new insight. Individually themed, Annals special issues stimulate new ways to think about science by providing a neutral forum for discourse—within and across many institutions and fields.