Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia

被引:0
作者
Yi, Chanlin [1 ,2 ]
Li, Fali [1 ,2 ,3 ,4 ]
Wang, Jiuju [5 ]
Li, Yuqin [1 ,2 ]
Zhang, Jiamin [1 ,2 ]
Chen, Wanjun [1 ,2 ]
Jiang, Lin [1 ,2 ]
Yao, Dezhong [1 ,2 ,3 ,6 ]
Xu, Peng [1 ,2 ,5 ,7 ,8 ]
He, Baoming [9 ,10 ]
Dong, Wentian [5 ]
机构
[1] Univ Elect Sci & Technol China, Chengdu Brain Sci Inst, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu 611731, Peoples R China
[2] Univ Elect Sci & Technol China, Ctr Informat Med, Sch Life Sci & Technol, Chengdu 611731, Peoples R China
[3] Chinese Acad Med Sci, Res Unit NeuroInformat, 2019RU035, Chengdu, Peoples R China
[4] Univ Macau, Fac Sci & Technol, Dept Elect & Comp Engn, Taipa, Peoples R China
[5] Peking Univ, Inst Mental Hlth, Natl Clin Res Ctr Mental Disorders,Hosp 6, NHC Key Lab Mental Hlth, Beijing 100191, Peoples R China
[6] Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450001, Peoples R China
[7] Radiat Oncol Key Lab Sichuan Prov, Chengdu 610041, Peoples R China
[8] Shandong Univ, Qilu Hosp, Rehabil Ctr, Jinan 250012, Peoples R China
[9] Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Dept Neurol, Chengdu 610072, Peoples R China
[10] Chinese Acad Sci Sichuan Translat Med Res Hosp, Chengdu 610072, Peoples R China
基金
中国国家自然科学基金;
关键词
Trial-to-trial variability; Time-varying directed networks; P300; Schizophrenia; Classification; WORKING-MEMORY; BRAIN NETWORKS; MODULATION; CONNECTIVITY; METAANALYSIS; ANXIETY; OSCILLATIONS; ASSOCIATION; DYSFUNCTION; ALGORITHMS;
D O I
10.1007/s11517-024-03133-9
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cognitive disturbance in identifying, processing, and responding to salient or novel stimuli are typical attributes of schizophrenia (SCH), and P300 has been proven to serve as a reliable psychosis endophenotype. The instability of neural processing across trials, i.e., trial-to-trial variability (TTV), is getting increasing attention in uncovering how the SCH "noisy" brain organizes during cognition processes. Nevertheless, the TTV in the brain network remains unrevealed, notably how it varies in different task stages. In this study, resorting to the time-varying directed electroencephalogram (EEG) network, we investigated the time-resolved TTV of the functional organizations subserving the evoking of P300. Results revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. The TTV of cross-band time-varying network properties can efficiently recognize SCH (accuracy: 83.39%, sensitivity: 89.22%, and specificity: 74.55%) and evaluate the psychiatric symptoms (i.e., Hamilton's depression scale-24, r = 0.430, p = 0.022, RMSE = 4.891; Hamilton's anxiety scale-14, r = 0.377, p = 0.048, RMSE = 4.575). Our study brings new insights into probing the time-resolved functional organization of the brain, and TTV in time-varying networks may provide a powerful tool for mining the substrates accounting for SCH and diagnostic evaluation of SCH.Graphical abstractSchematic view of the TTV in time-varying networks, as well as the patient's recognition and psychiatric symptoms prediction based on the anomalous TTV of SCH. The TTV is getting increasing attention in understanding the "noise" brain of SCH, whereas a perspective in a time-varying directed network still lacking. We proposed to focus on the TTV in a time-varying directed EEG electroencephalogram (EEG) network to uncover how the brain unstably organizes during cognition processes and probe the instability of neural processing across trials during the P300 task process to find the potential mechanisms that account for the cognitive disturbance of SCH. Based on the P300 task EEG of SCHs and HCs, we revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. And the TTV of cross-band time-varying network properties can efficiently recognize SCH and evaluate the psychiatric symptoms.
引用
收藏
页码:3327 / 3341
页数:15
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