Comparison Between Gradients and Parcellations for Functional Connectivity Prediction of Behavior
Ru Kong, Yan Rui Tan, Naren Wulan, Leon Qi Rong Ooi, Seyedeh-Rezvan Farahibozorg, Samuel J. Harrison, Janine Diane Bijsterbosch, Boris C. Bernhardt, Simon Bodo Eickhoff, B.T. Thomas Yeo
This study compares parcellation and gradient methods for predicting behavior from resting-state functional connectivity in two datasets, finding that individual-specific hard parcellations perform best in HCP and principal gradients perform similarly in ABCD.
NeuroImage · Mar 20, 2023Peer-reviewedNeuroscience