I want to compare two independent groups (Group X1 has N=12 participants and Group X2 has N=13 participants)
The data I want to compare is decoding accuracy over time. Therefore, for each group I have an array of N participants X Time-points.

I want to run a cluster permutation test to compare the independent groups, but I am unsure how to set-up the treshold and statsfun parameters for the ne.stats.permutation_cluster_test. At the moment, I have the following call:

From my understanding you need the evoked objects from each participant rather than the grand average object, as you need both the difference between groups at a given time point but also the variation within each group - just like you would when performing a standard t-test or similar. So you will need to supply the function with a 3d array for each group, each containing the evoked objects that went into the grand average.
If I remember right you can use np.dstack(evoked_data_list) to stack you data