Analysis of Depression Magnetoencephalography Based on Modified Permutation Entropy

Yuan, Zizhen; Yan, Wei; Wang, Jun; Jin, Li; Hou, Fengzhen

doi:10.1109/cisp-bmei.2018.8633155

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…e development of information technology [8][9][10][11] has brought new opportunities and challenges to the diagnosis and treatment of depression [12][13][14]. MEG is a real-time monitoring technology used to record the brain magnetic eld signal generated by neuronal activity and monitor the brain electrophysiological activity through the waveform, amplitude, and frequency of the signal [15][16][17][18][19]. MEG has a time resolution of millisecond, which can record neuron signals in real time without measuring brain metabolism; high spatial resolution of MEG can locate brain lesions accurately.…”

Section: Background Introductionmentioning

confidence: 99%

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

Zhang

Xie

Fan

et al. 2022

Computational Intelligence and Neuroscience

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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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