精神分裂症 P300 时变定向电子脑电图网络中试验到试验之间的异常变异。

IF 2.6 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Chanlin Yi, Fali Li, Jiuju Wang, Yuqin Li, Jiamin Zhang, Wanjun Chen, Lin Jiang, Dezhong Yao, Peng Xu, Baoming He, Wentian Dong
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引用次数: 0

摘要

精神分裂症(SCH)的典型特征是对突出刺激或新刺激的识别、处理和反应出现认知障碍,而 P300 已被证明是一种可靠的精神病内表型。在揭示精神分裂症患者 "嘈杂 "的大脑在认知过程中是如何组织的过程中,神经处理在不同试验间的不稳定性,即试验间变异性(TTV),正受到越来越多的关注。然而,大脑网络中的TTV仍未被揭示,尤其是它在不同任务阶段是如何变化的。在本研究中,我们借助时变定向脑电图(EEG)网络,研究了唤起 P300 的功能组织的时间分辨 TTV。结果显示,时变网络中的 TTV 在 SCH 的 delta、theta、alpha、beta1 和 beta2 波段中均存在异常。跨波段时变网络特性的 TTV 可以有效识别 SCH(准确率:83.39%,灵敏度:89.22%,特异性:74.55%)和评估精神症状(即汉密尔顿抑郁量表-24,r = 0.430,p = 0.022,RMSE = 4.891;汉密尔顿焦虑量表-14,r = 0.377,p = 0.048,RMSE = 4.575)。我们的研究为探究大脑的时间分辨功能组织带来了新的见解,时变网络中的 TTV 可为挖掘 SCH 的基质和诊断评估 SCH 提供强有力的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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.

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来源期刊
Medical & Biological Engineering & Computing
Medical & Biological Engineering & Computing 医学-工程:生物医学
CiteScore
6.00
自引率
3.10%
发文量
249
审稿时长
3.5 months
期刊介绍: Founded in 1963, Medical & Biological Engineering & Computing (MBEC) continues to serve the biomedical engineering community, covering the entire spectrum of biomedical and clinical engineering. The journal presents exciting and vital experimental and theoretical developments in biomedical science and technology, and reports on advances in computer-based methodologies in these multidisciplinary subjects. The journal also incorporates new and evolving technologies including cellular engineering and molecular imaging. MBEC publishes original research articles as well as reviews and technical notes. Its Rapid Communications category focuses on material of immediate value to the readership, while the Controversies section provides a forum to exchange views on selected issues, stimulating a vigorous and informed debate in this exciting and high profile field. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE).
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