TY - GEN
T1 - An EEG-based study on coherence and brain networks in mild depression cognitive process
AU - Li, Xiaowei
AU - Jing, Zhuang
AU - Hu, Bin
AU - Sun, Shuting
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/17
Y1 - 2017/1/17
N2 - 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.
AB - 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.
KW - EEG coherence
KW - GTA
KW - Small-world network
UR - http://www.scopus.com/inward/record.url?scp=85013278145&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2016.7822702
DO - 10.1109/BIBM.2016.7822702
M3 - Conference contribution
AN - SCOPUS:85013278145
T3 - Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
SP - 1275
EP - 1282
BT - Proceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
A2 - Burrage, Kevin
A2 - Zhu, Qian
A2 - Liu, Yunlong
A2 - Tian, Tianhai
A2 - Wang, Yadong
A2 - Hu, Xiaohua Tony
A2 - Jiang, Qinghua
A2 - Song, Jiangning
A2 - Morishita, Shinichi
A2 - Burrage, Kevin
A2 - Wang, Guohua
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Y2 - 15 December 2016 through 18 December 2016
ER -