Repeated measures ANOVA on source data with spatio-temporal clustering on epochs from Mat files

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Hello everyone;
I am quite new to MNE, since I have used field trip + brainstorm to conduct most of the analysis I?ld done before.

Now, I?d like to use the repeated measures ANOVA tutorial but starting from .mat files instead of the raw fit file;
This is because I already conducted all the pre-processing using field trip and brainstorm, and have already have epochs files per each condition and subject.

Has anybody already done that? Any advice?
I am slowly finding my way through the code, but I am not sure whether there is already some material out there that could shortcut the process or, even worse, some advice like ?no, that?s not possible to do it?.

Thanks, and happy holidays y?all!
Alfredo Spagna, Ph. D.
alfredo.spagna at icm-institute.org<mailto:alfredo.spagna at icm-institute.org>
PICNIC Lab @ Institut du Cerveau
et de la Moelle e?pinie?re
Inserm U 1127, Paris, France

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Hi Alfredo,

you can use scipy.io.load_mat to read a mat file, and then put the
corresponding information into an mne object:

e.g.
import mne
from scipy.io import load_mat
info = mne.create_info(32, sfreq=256., ch_types='eeg') # 32 EEG channels
sampled at 256Hz
mat = load_mat('data.mat') # matrix of32 channels x n time samples
raw = mne.RawArray(mat, info=info)
or
mat = load_mat('data.mat')
epochs = mne.EpochsArray(mat, info=info, tmin=-.500) # first time sample @
-500ms

For the anova you can check
https://martinos.org/mne/stable/auto_tutorials/plot_background_statistics.html?highlight=anova

best regards,

JR