Proposal for Enhanced EEG Dataset Comparison Across Different Montages

[incubodac]

Describe the new feature or enhancement

Dear MNE Community,
I hope this message finds you well. I am currently working with two EEG datasets stemming from the same experimental paradigm, acquired using different caps (biosemi128/64). During my analysis, I encountered a challenge in facilitating a spatial downsampling of the 128-channel montage to enable a meaningful comparison of results between both datasets.
Given that only 34 electrode locations coincide between the two montages, I devised a solution by creating a virtual montage. This involved incorporating the 30 non-matching locations onto the 128-channel head, utilizing spline interpolation to obtain data for these additional points, and subsequently discarding the unwanted channels, then resulting in a 64-channel montage dataset.
While my specific case addresses only biosemi caps, I believe this approach could be valuable in a broader context. It may not be uncommon to compare EEG datasets acquired using different montages. Therefore, I propose the inclusion of a more generalized version of this downsampling method to accommodate various montages.However, perhaps the effectiveness of this enhancement may be limited to montages with electrode locations calculated from a sphere, like the biosemi setup.
I welcome feedback and collaboration from the community to refine and implement this proposed feature.

Describe your proposed implementation

Maybe as a method of DigMontage class.

Describe possible alternatives

Not sure.

Additional context

No response

[welcome]

Hello! 👋 Thanks for opening your first issue here! ❤️ We will try to get back to you soon. 🚴

[agramfort]

you could start by making an example doing this?

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Message ID: ***@***.***>

[incubodac]

Yes, I've already prepared an example utilizing a BioSemi montage. You can find it here <https://github.com/incubodac/Cross-MontageComparison>. I'm eager to hear any feedback or suggestions you may have regarding it. Thank you!

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On Thu, 1 Feb 2024 at 18:10, Alexandre Gramfort ***@***.***> wrote: you could start by making an example doing this? > Message ID: ***@***.***> > — Reply to this email directly, view it on GitHub <#12409 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AHYZHDB7F76XTBQE2MULHBLYRQAGBAVCNFSM6AAAAABCVQB5TWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSMRSGI2TCNJTGE> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[agramfort]

I see. You could make a new file in https://github.com/mne-tools/mne-python/tree/main/examples/preprocessing that is a full example.

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On Thu, Feb 15, 2024 at 9:58 PM dac9000 ***@***.***> wrote: Yes, I've already prepared an example utilizing a BioSemi montage. You can find it here <https://github.com/incubodac/Cross-MontageComparison>. I'm eager to hear any feedback or suggestions you may have regarding it. Thank you! On Thu, 1 Feb 2024 at 18:10, Alexandre Gramfort ***@***.***> wrote: > you could start by making an example doing this? > > > Message ID: ***@***.***> > > > > — > Reply to this email directly, view it on GitHub > < #12409 (comment)>, > or unsubscribe > < https://github.com/notifications/unsubscribe-auth/AHYZHDB7F76XTBQE2MULHBLYRQAGBAVCNFSM6AAAAABCVQB5TWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSMRSGI2TCNJTGE> > . > You are receiving this because you authored the thread.Message ID: > ***@***.***> > — Reply to this email directly, view it on GitHub <#12409 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABHKHEK7BIBRLFSPJRLC3LYTZZIJAVCNFSM6AAAAABCVQB5TWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSNBXGMZDSMRQHE> . You are receiving this because you commented.Message ID: ***@***.***>