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. 2022 Jul 20:2022:7516627.
doi: 10.1155/2022/7516627. eCollection 2022.

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

Xinyu Zhang  1   2 , Jicheng Xie  1   2 , Changyu Fan  1   2 , Jun Wang  1   2
Affiliations

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

Xinyu Zhang et al. Comput Intell Neurosci. .

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 t-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 γ frequency band and the largest in the frontal region.

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Conflict of interest statement

The authors declare that there are no conflicts of interest.

Figures

Figure 1
Figure 1
Algorithm flowchart.
Figure 2
Figure 2
Filter frequency response.
Figure 3
Figure 3
Time domain diagram of original EEG signal.
Figure 4
Figure 4
Time domain diagram of filtered b-band EEG signal.
Figure 5
Figure 5
Differences of symmetrical brain regions in θ frequency band.
Figure 6
Figure 6
Differences of various frequency bands in the central region.
Figure 7
Figure 7
Relative difference between left frontal area and left central area under each frequency band.
Figure 8
Figure 8
Relative difference between temporal region and central region in δ band.
Figure 9
Figure 9
Multivariate transfer entropy of left and right symmetrical frontal region in band γ.
Figure 10
Figure 10
Multivariate transfer entropy of left temporal and left central region under γ band.
Figure 11
Figure 11
Multivariate transfer entropy of left occipital and left frontal region under γ band.
See this image and copyright information in PMC

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