Abstract
It has important significance for understanding the brains work and exploring the pathological mechanism of mental disease that research the functional connectivity of the human brain regions from the viewport of brain network. By using the data of resting state functional Magnetic Resonance Imaging (rs-fMRI), this paper calculates the correlation among 264 brain regions. And then, by determining the available threshold of correlation coefficient via three reasonable assumptions, this paper constructs the brain functionality network. The experiment results via computing clustering coefficient and average minimum path length show that the brain functionality network has the feature of small world. Considering the number of brain nodes greater than the length of signal sequence, this paper proposes a matrix transformation algorithm to obtain the partial correlation algorithm and eliminate the indirect effects of other nodes. Finally, the visualization of brain nodes connectivity is constructed based on the standard brain images. The experiments illustrate that the proposed algorithm is feasible and beneficial for the exploration in the field of brain function connectivity.
| Original language | English |
|---|---|
| Pages (from-to) | 821-827 |
| Number of pages | 7 |
| Journal | Huadong Ligong Daxue Xuebao /Journal of East China University of Science and Technology |
| Volume | 41 |
| Issue number | 6 |
| State | Published - 1 Dec 2015 |
| Externally published | Yes |
Keywords
- Brain connectivity
- Correlation coefficient
- Partial correlation
- Resting state
- Small world
