[Mne_analysis] [fNIRS] Group analysis

[Eric Larson]

        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 read_raw_nirx
<https://mne.tools/dev/generated/mne.io.read_raw_nirx.html>.


> 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 fNIRS tutorial
<https://mne.tools/dev/auto_tutorials/preprocessing/plot_70_fnirs_processing.html#sphx-glr-auto-tutorials-preprocessing-plot-70-fnirs-processing-py>
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/ 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 grand_average
<https://mne.tools/dev/generated/mne.grand_average.html> to average across
all participants.

Eric
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