Name
Abstract | ||
|---|---|---|
In this paper, we symbolize two kinds of different channels of Magnetoencephalography(MEG) and analyze their coupling relationship using symbolic transfer entropy algorithm. We record MEG signals from six depressive disorders and nine healthy subjects stimulated by positive, neutral, and negative emotional pictures and explore coupling relationship of different MEG channels. The results show that there are obvious differences on correlations between two channels of MLP32 and MRP32 with positive emotional stimulus, MLP31 and MRP31 with neutral emotional stimulus, MLP53 and MRP53 with negative emotional stimulus. In general, these channels have more correlation in patients with major depression, and can be able to distinguish depression patient from crowd. It also shows that the research of symbolic transfer entropy in MEG channel can distinguish the difference between normal and case samples, which of significance for clinical pathological estimation and diagnosis. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI) | MEG, depression, symbolic transfer entropy |
Field | DocType | Citations |
Transfer entropy,Pattern recognition,Computer science,Cognitive psychology,Correlation,Artificial intelligence,Stimulus (physiology),Magnetoencephalography,Parietal lobe | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bihan Zhang | 1 | 0 | 0.34 |
| Chuchu Ding | 2 | 0 | 0.68 |
| Wei Yan | 3 | 38 | 23.56 |
| Li Guo | 4 | 58 | 18.35 |
| Jun Wang | 5 | 0 | 3.38 |
| Fengzhen Hou | 6 | 0 | 1.69 |