[ENH] cluster threshold for surface GLM #4326
Labels
Enhancement
for feature requests
GLM
Issues/PRs related to the nilearn.glm module.
Surface
Related to surface data or surface analysis.
Is there an existing issue for this?
Describe your proposed enhancement in detail.
As I use these days mostly (if not only) surface analysis of fMRI data, I use to the surface GLM analysis of nilearn, however I couldn't find the cluster_threshold method available for volume analysis.
The idea of cluster analysis for surface would be to discard isolated vertices from the GLM output in order to generate thresholded maps with small cluster of vertices removed following a cluster_threshold argument.
Here is the volume based equivalent:
nilearn/nilearn/glm/thresholding.py
Line 184 in 436cfb2
After early discussion I feel that for this improvement (@Remi-Gau @bthirion, @ulascombes) , we would need first:
Benefits to the change
This analysis is to my opinion an important missing step for the basic GLM surface analysis of nilearn, it will benefit to the community of users who moved toward fMRI surface analyses.
Pseudocode for the new behavior, if applicable
# insert your code below
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