Sources and labels for reconstruct time course label from EEG

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Hi MNE users,

I'm currently working on mixed source space connectivity and I would like to reconstruct time course label from EEG recordings. I am confronted with 2 problems:
    - Is it possible to create a volume source space which does not creates sources inside white matter ? ( I followed this exemple <https://martinos.org/mne/stable/auto_tutorials/source-modeling/plot_forward.html#sphx-glr-auto-tutorials-source-modeling-plot-forward-py> and had a look at the API, but I didn't find a way to do what I want )
    - When using mne.extract_label_time_course<https://martinos.org/mne/stable/generated/mne.extract_label_time_course.html#mne.extract_label_time_course> , how MNE assigns label for volume source space ? I'm working with a custom atlas, should I use my specific atlas aparc+asef:mgz when setting the volume sources<https://martinos.org/mne/stable/generated/mne.setup_volume_source_space.html#mne.setup_volume_source_space> as volume label ?

Thanks for your help,

Best,
Victor

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    - Is it possible to create a volume source space which does not
creates sources inside white matter ? ( I followed this exemple
<https://martinos.org/mne/stable/auto_tutorials/source-modeling/plot_forward.html#sphx-glr-auto-tutorials-source-modeling-plot-forward-py&gt;and
had a look at the API, but I didn't find a way to do what I want )

Implicitly, yes. You can choose which volume labels to use (and thus not
include cortex), see for example
https://mne.tools/dev/auto_examples/inverse/plot_mixed_source_space_inverse.html

    - When using mne.extract_label_time_course

<https://martinos.org/mne/stable/generated/mne.extract_label_time_course.html#mne.extract_label_time_course&gt; ,
how MNE assigns label for volume source space ? I'm working with a custom
atlas, should I use my specific atlas aparc+asef:mgz when setting the volume
sources
<https://martinos.org/mne/stable/generated/mne.setup_volume_source_space.html#mne.setup_volume_source_space&gt;
as volume label ?

We do not currently have an API for this so you'll need to write custom
code. See the ongoing discussion (and some usable code snippets) in:

https://github.com/mne-tools/mne-python/issues/6278
https://github.com/mne-tools/mne-python/issues/6155

HTH,
Eric
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Hi,

Thanks for you answer Eric,

If I understand well, in the connectivity source space exemple<https://martinos.org/mne/stable/auto_examples/connectivity/plot_mixed_source_space_connectivity.html#sphx-glr-auto-examples-connectivity-plot-mixed-source-space-connectivity-py>, the volume sources are not taken into account when using mne.extract_label_time_course<https://martinos.org/mne/stable/generated/mne.extract_label_time_course.html#mne.extract_label_time_course> ?
It may be confusing because in the previous exemple, we provide both Volume and Surface sources to compute the label time course. If it's the case perhaps the name of the example is misleading as the connectivity is only evaluated on the surface source space.

About assigning label for volume source space, I proposed a workaround on this issue<https://github.com/mne-tools/mne-python/issues/6155>,

Thanks again,

Regards,
Victor<https://github.com/mne-tools/mne-python/issues/6155>