Resting state with dataset and example #400
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fix: inversion 12 blocks of 5 repetitions
# Conflicts: # moabb/tests/datasets.py
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
- add comments
| if "Target" in event_id and "NonTarget" in event_id: | ||
| if ( | ||
| type(event_id["Target"]) is list | ||
| and type(event_id["NonTarget"]) == list | ||
| ): | ||
| event_id_new = dict(Target=1, NonTarget=0) | ||
| events = mne.merge_events(events, event_id["Target"], 1) | ||
| events = mne.merge_events(events, event_id["NonTarget"], 0) | ||
| event_id = event_id_new |
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@Sara04, is this related to your issue with the p300?
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@gcattan, I must say, your code looks really cool!
I have a few questions rather than requests for changes.
First, I would like you to create some testing for the new paradigm. Additionally, could you modify the "dataset_summary" file in the documentation to incorporate information about the new paradigm?
As we plan to expand this dataset category, it would be beneficial to include some introductory text about the new paradigm in this file, maybe a figure if you have it easy. This way, we can attract new users to utilize it.
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Thanks, @bruAristimunha. I put here some more comments and additional testing. I do not have a figure ready at the moment, unfortunately. |
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Firstly, I want to express my gratitude to both @gcattan and @plcrodrigues for introducing this new paradigm. I have reviewed the tutorial and made a few minor adjustments. These changes primarily focus on improving the formatting and markdown style of the tutorial. I hope you don't mind these final modifications 🙏🏽. Once everything is green, I'll apply the merge =) |
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All good to me :) thank you for the last changes :) |
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Hey @dengemann, I was thinking, and I think you might like to know that moabb has resting stage dataset, I hope that in the future we can put more public dataset in this category, maybe on your side :) |
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I'm not sure if this is well known, but in the They are the runs 1 and 2 as explained here. This might be useful for the I won't have time to do much about it now, but I will leave this low hanging fruit here :-) |
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Sounds like a good use case for the GoShoppingDataset ^^ |
This PR introduces a resting state paradigm and a new dataset. An example is provided.
The code is adapted from @plcrodrigues's repository: https://github.com/plcrodrigues/py.PHMDML.EEG.2017-GIPSA
@bruAristimunha @sylvchev FYI