An EEG-based study on coherence and brain networks in mild depression cognitive process

Xiaowei Li, Zhuang Jing, Bin Hu*, Shuting Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)

Abstract

Depression is a common mental disorder, and in recent years, there has been an increasing trend of mild to moderate depression among college students. Additionally, effective detection of mild depression at an earlier stage remains an urgent problem that must be solved. In this study, electroencephalography (EEG) activities were recorded from 37 participants during processing of facial expression stimuli. With both high-gamma and low-gamma bands, the coherence in the right hemisphere of normal controls was greater than that of mildly depressive subjects, especially for electrodes P8, TP8, C4, FC4, and F8. In the low gamma band, the clustering coefficients of healthy controls in the prefrontal lobe (AF4, AFz, AF3, FC5, F4, and F6) and the parietal lobe (PO3, PO4, and P2) were significantly higher than those of mildly depressive subjects. The ratio of the characteristic path length between the functional network of the mildly depressed group and the small-world network was greater than 1. For the normal group, the ratio was near 1. This research contributes to the study of the cognitive process of mild depression. In our study, the results show closer cooperation in the brain areas of right hemisphere in normal controls during the cognitive process compared with the mildly depressed group, while the activity of the prefrontal and parietal regions in mild depression was significantly lower than that of normal controls. At the same time, in terms of the characteristic path length, the functional network of the mildly depressed group deviates from the small-world network.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
EditorsKevin Burrage, Qian Zhu, Yunlong Liu, Tianhai Tian, Yadong Wang, Xiaohua Tony Hu, Qinghua Jiang, Jiangning Song, Shinichi Morishita, Kevin Burrage, Guohua Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1275-1282
Number of pages8
ISBN (Electronic)9781509016105
DOIs
Publication statusPublished - 17 Jan 2017
Externally publishedYes
Event2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China
Duration: 15 Dec 201618 Dec 2016

Publication series

NameProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

Conference

Conference2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Country/TerritoryChina
CityShenzhen
Period15/12/1618/12/16

Keywords

  • EEG coherence
  • GTA
  • Small-world network

Fingerprint

Dive into the research topics of 'An EEG-based study on coherence and brain networks in mild depression cognitive process'. Together they form a unique fingerprint.

Cite this