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基于多元传递熵的抑郁症患者脑磁图研究。

Research on the MEG of Depression Patients Based on Multivariate Transfer Entropy.

机构信息

School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, China.

Smart Health Big Data Analysis and Location Services Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing, China.

出版信息

Comput Intell Neurosci. 2022 Jul 20;2022:7516627. doi: 10.1155/2022/7516627. eCollection 2022.

DOI:10.1155/2022/7516627
PMID:35909866
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9328977/
Abstract

The pathogenesis of depression is complex, and the current means of medical diagnosis is single. Patients with severe depression may even have great physical pain and suicidal tendencies. Magnetoencephalography (MEG) has the characteristics of ultrahigh spatiotemporal resolution and safety. It is a good medical means for the diagnosis of depression. In this paper, multivariate transfer entropy algorithm is used to study MEG of depression. In this paper, the subjects are divided into the same brain region and the multichannel combination between different brain regions, and the multivariate transfer entropy of patients with depression and healthy controls under different EEG signal frequency bands is calculated. Finally, the significant difference between the two groups of experimental samples is verified by the results of independent sample -test. The experimental results show that for the same combination of brain channels, the multivariate transfer entropy in the depression group is generally lower than that in the healthy control group, and the difference is the best in frequency band and the largest in the frontal region.

摘要

抑郁症的发病机制复杂，目前的医学诊断手段单一。重度抑郁症患者甚至可能会出现极大的身体疼痛和自杀倾向。脑磁图（MEG）具有超高时空分辨率和安全性的特点，是一种用于诊断抑郁症的良好医学手段。本文使用多元传递熵算法对抑郁症的 MEG 进行研究。本文将被试分为相同脑区以及不同脑区间的多通道组合，计算抑郁症患者和健康对照者在不同脑电信号频段下的多元传递熵。最后，通过独立样本 t 检验的结果验证两组实验样本的显著性差异。实验结果表明，对于相同的脑通道组合，抑郁症组的多元传递熵普遍低于健康对照组，且在频带和额叶的差异最大。

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