Name
Abstract | ||
|---|---|---|
The functional connectivity of the resting state, or default mode, of the human brain has been a research focus, because it is reportedly altered in many neurological and psychiatric disorders. Among the methods to assess the functional connectivity of the resting brain, independent component analysis (ICA) has been very useful. But how to choose the optimal number of separated components and the best-fit component of default mode network are still problems left. In this paper, we used three different numbers of independent components to separate the fMRI data of resting brain and three criterions to choose the best-fit component. Furthermore, we proposed a new approach to get the best-fit component. The result of the new approach is consistent with the default-mode network. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11893028_20 | ICONIP (1) |
Keywords | Field | DocType |
resting state,functional connectivity,default mode,human brain,resting brain,independent component analysis,best-fit component,separated component,new approach,independent component,default mode network | Default mode network,Pattern recognition,Computer science,Neurological disorder,Resting state fMRI,Human brain,Independent component analysis,Artificial intelligence,Artificial neural network | Conference |
Volume | ISSN | ISBN |
4232 | 0302-9743 | 3-540-46479-4 |
Citations | PageRank | References |
1 | 0.35 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xia Wu | 1 | 14 | 4.41 |
| Li Yao | 2 | 54 | 23.68 |
| Zhi-ying Long | 3 | 29 | 7.52 |
| Jie Lu | 4 | 51 | 6.19 |
| Kun-cheng Li | 5 | 399 | 40.88 |