# Question about source adjacency for permutation statistics

**URL:** <https://mne.discourse.group/t/question-about-source-adjacency-for-permutation-statistics/10352>\
**Category:** Support & Discussions\
**Created:** [October 8, 2024, 11:17am UTC](https://mne.discourse.group/t/question-about-source-adjacency-for-permutation-statistics/10352 "2024-10-08T11:17:33Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![DavideTabarelli](https://avatars.discourse-cdn.com/v4/letter/d/977dab/32.png) [@DavideTabarelli](https://mne.discourse.group/u/DavideTabarelli)\
**Post date:** [October 8, 2024, 11:17am UTC](https://mne.discourse.group/t/question-about-source-adjacency-for-permutation-statistics/10352/1 "2024-10-08T11:17:33Z")

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Dear experts,

I’m setting up the code for a statistical comparison between source estimates using the function mne.stats.spatio\_temporal\_cluster\_test(…).

My data consists in brain activations over time (evoked sources) already morphed to the fsaverage template. I have 20484 vertices (ico5) and 601 time points.

I’m struggling in correctly defining an adjacency matrix. I ran the analysis successfully specifying a spatial adjacency matrix obtained from the function mne.spatial\_src\_adjacency(src), where src is the fsaverage source model.

But I’m not sure this is the correct way to consider patio-temporal clusters and, in particular, I don’t understand the difference between the function I used and the function mne.spatio\_temporal\_src\_adjacency().

Thank you in advance for your valuable support !

D.