How to use cluster-based permutation statistics on spatio-temporal data?

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Toby W
Toby W on 11 Nov 2018
I am analyzing high density surface electromyography (HD-sEMG) data, where I am calculating the similarities between each channel in the sensor grid using normalised mutual information (NMI). I have two different outcome measures from my calculations. NMI heatmaps (12x5 matrices) and connectivity maps (60x60 matrices). I have attached examples of the data, so you get the idea. I am trying to find a way to compare this data, which has a spatio-temporal pattern.
So my question is: How can I use cluster-based permutation statistics when I have the heatmaps and connectivity maps, without starting from the time domain signals?
A simple approach that I have tried, is to compare the mean levels of the data, though this is a big reduction of information, because it reduces the matrices into just 1 number.
Thank you

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