NiMARE -reporting outputs

Hi Taylor and NiMARE community,
I have some questions regarding the outputs.I have run a coordinate-based ALE,then I try to use the function “get_clusters_table” to get the outputs.I found a lot of NaN in the “Peak Stat” column.I wonder if there are any other ways to get the similar table of outputs as “get_clusters_table” ?

Besides,when I want to use siibra to convert the outputs of NiMARE,but I don’t know whether it is suitable or not?
pip install git+
import siibra
atlas = siibra.atlases.MULTILEVEL_HUMAN_ATLAS
with siibra.QUIET: # suppress progress output
julich_pmaps = atlas.get_map(
point = siibra.Point((0, 58, 16), space=‘mni152’)
with siibra.QUIET: # suppress progress output
assignments = julich_pmaps.assign(point)
assignments.sort_values(by=[‘MaxValue’], ascending=False)


Nilearn’s get_clusters_table can sometimes identify a center of mass outside of the actual cluster, in which case you end up with that NaN value. If you’re comfortable writing Python code, you could maybe clone Nilearn and edit the get_clusters_table function to identify the closest voxel within the cluster. Otherwise, a good workaround might be to just open the map in a viewer like Mango and just select a voxel in the relevant cluster to see what the statistic is.

This problem has come up before, and now that Nilearn supports cluster-level correction in its newest release, it will probably come up more often, so I’ve opened an issue about it: Shift centers of mass outside of clusters to closest in-cluster voxel in get_clusters_table · Issue #3278 · nilearn/nilearn · GitHub.

Unfortunately, I’m not familiar with siibra. What are you trying to accomplish with it?


1 Like

Thanks for your answer.

I want to use siibra to identify the brain regions from the coordinates.

As far as I know, the outputs of NiMARE should be suitable for a use like that.