Trial-by-Trial Variability of TMS-EEG in Healthy Controls and Patients With Depressive Disorder

IF 4.8 2区医学 Q2 ENGINEERING, BIOMEDICAL

IEEE Transactions on Neural Systems and Rehabilitation Engineering Pub Date : 2024-10-28 DOI:10.1109/TNSRE.2024.3486759

Zikang Niu;Lina Jia;Yang Li;Lijuan Yang;Yi Liu;Siyuan Lian;Dan Wang;Wen Wang;Liu Yang;Weigang Pan;Xiaoli Li

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引用次数: 0

Abstract

Depressive disorder has been known to be associated with high variability in resting-state electroencephalography (EEG) signals. However, this phenomenon is often ignored in stimulus-related brain activities. This study proposed a new method to explore the EEG variability evoked by transcranial magnetic stimulation (TMS, TMS-EEG) in depressive disorder (DE) patients. The TMS-EEG data were collected from 34 DE patients and 36 healthy controls (HC). The maximum eigenvalue of the real binary correlation matrix, calculated between different trials using cross-correlation and surrogate methods, was extracted to assess trial-by-trial variability (TTV) of TMS-EEG. The new method was found to more sensitive and reliable than the standard deviation method. DE patients exhibited significantly smaller TTV in Gamma band and greater TTV in Delta band than HC. Furthermore, the HAMD-17 scores were negatively correlated with TTV values in Gamma band. This study represented the first investigation into the TTV in TMS-EEG data and revealed abnormal values in DE patients. Those findings enhance our understanding of TMS-EEG technology and provide valuable insights for studying the characteristics of DE.

查看原文本刊更多论文

健康对照组和抑郁症患者的 TMS-EEG 逐次试验变异性。

目的：众所周知，抑郁症与静息状态脑电图（EEG）信号的高变异性有关。然而，这种现象在与刺激相关的大脑活动中往往被忽视。本研究提出了一种新方法来探索经颅磁刺激（TMS，TMS-EEG）在抑郁障碍（DE）患者中诱发的脑电图变异性：方法：收集了34名抑郁症患者和36名健康对照组（HC）的TMS-EEG数据。方法：收集 34 名抑郁症患者和 36 名健康对照组（HC）的 TMS-EEG 数据，利用交叉相关法和替代法计算出不同试验间真实二元相关矩阵的最大特征值，以评估 TMS-EEG 的逐次试验变异性（TTV）：结果发现，新方法比标准偏差法更灵敏、更可靠。与 HC 相比，DE 患者在 Gamma 波段的 TTV 明显较小，而在 Delta 波段的 TTV 则较大。此外，HAMD-17 评分与伽马波段的 TTV 值呈负相关：本研究首次对 TMS-EEG 数据中的 TTV 进行了调查，发现 DE 患者的 TTV 值异常。这些发现加深了我们对 TMS-EEG 技术的理解，并为研究 DE 的特征提供了有价值的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Neural Systems and Rehabilitation Engineering 医学-工程：生物医学

CiteScore

8.60

自引率

8.20%

发文量

479

审稿时长

6-12 weeks

期刊介绍： Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.