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

[JR KING]

        External Email - Use Caution        

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

On Mon, 24 Dec 2018 at 15:09, SPAGNA Alfredo <
alfredo.spagna at icm-institute.org> wrote:

>         External Email - Use Caution
>
> 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
> PICNIC Lab @ Institut du Cerveau
> et de la Moelle épinière
> Inserm U 1127, Paris, France
>
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