Enhancing prediction of human traits and behaviors through ensemble learning of traditional and novel resting-state fMRI connectivity analyses
Recent advances in cognitive neuroscience have focused on using resting-state functional connectivity (RSFC) data from fMRI scans to more accurately predict human traits and behaviors. Traditional approaches generally analyze RSFC by correlating averaged time-series data across regions of interest (...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811924004087 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|