[Mne_analysis] [fNIRS] Group analysis

[David JULIEN]

        External Email - Use Caution        

Alright things start to get clearer. I'll double-check the other tutorials to see what I can do, but I do think that epoch.average() and grand_average() are what I'm looking for. Thanks ! 

Have a good day, 

David 

> De: "Eric Larson" <larson.eric.d at gmail.com>
> À: "mne_mailing_list" <mne_analysis at nmr.mgh.harvard.edu>
> Envoyé: Mercredi 24 Juin 2020 17:45:05
> Objet: Re: [Mne_analysis] [fNIRS] Group analysis

> External Email - Use Caution

>> They used a NIRSport to get the relevant raw data, which I can process using the
>> fNIRS library, but only one at a time.

> In MNE you should be able to read these directly with [
> https://mne.tools/dev/generated/mne.io.read_raw_nirx.html | read_raw_nirx ] .

>> 1. convert the data from each performance of the experiment into an Epoch

>> 2. squash the results into one single usable object
>> 3. process this object, if needed
>> 4. get figures with the average haemodynamic response of the group

> Can you look at the [
> https://mne.tools/dev/auto_tutorials/preprocessing/plot_70_fnirs_processing.html#sphx-glr-auto-tutorials-preprocessing-plot-70-fnirs-processing-py
> | fNIRS tutorial ] to see if it clears up how you would process a single
> subject's data? From there, you can look into tutorials on how to combine data
> across subjects, which are the same for MEG, EEG, and NIRS data in MNE (so you
> can look at the MEG/EEG tutorials for ideas). There is also the experimental [
> https://github.com/mne-tools/mne-nirs/ | https://github.com/mne-tools/mne-nirs/
> ] repository where experimental APIs are being developed, but it sounds like
> you won't need these (e.g., GLM).

>> Now I could obviously create an Epoch list after processing each set, but then
>> comes the question of *averaging* the results. I tried to use the
>> epoch.add_channels method to have one Epoch object, but then the other methods
>> (such as epoch.plot_image) break because channels are duplicated.

> Sounds like you probably want epochs.average() to get trial-averaged (Evoked)
> results for each subject, then use [
> https://mne.tools/dev/generated/mne.grand_average.html | grand_average ] to
> average across all participants.

> Eric

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