Python based demo for
Fast Connectivity Gradient Approximation: Maintaining spatially fine-grained connectivity gradients while reducing computational costs.
Karl-Heinz Nenning, Ting Xu, Arielle Tambini, Alexandre R. Franco, Daniel S. Margulies, Stanley J. Colcombe, Michael P. Milham
bioRxiv 2023.07.22.550017; https://www.biorxiv.org/content/10.1101/2023.07.22.550017v2.full
Packages used for the FCGA demo are stored in conda_env_fcga_demo.txt
create a Conda environment with:
conda create --name demo_fcga --file conda_env_fcga_demo.txt