mne-tools / mne-tools/mne-python
Add SSD to the Decoding (MVPA) tutorials
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- Dominant language
- Python
- Stars
- 3.5k
- Forks
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- Avg merge
- 1d 6h
- Merged PRs (30d)
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Description
Proposed documentation enhancement
Add an example of how SSD can be used within a machine-learning pipeline. At the moment we have an example on how SSD enhances oscillatory brain activity, but not how it can be integrated within a decoding pipeline. The examples can then be added in the tutorials/machine-learning/plot_sensors_decoding.py, which are the moment SSD is missing there.
My idea is to show how SSD can be beneficial before applying CSP or SPoC. A brief explanation on the formulation of SSD can be added too, as done for CSP.
What do you think @dengemann @larsoner @sappelhoff @drammock ??
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with tutorials/machine-learning/plot_sensors_decoding.py and the existing auto_examples/decoding/plot_ssd_spatial_filters.py example. Review how CSP and SPoC are explained, then determine how SSD should be demonstrated before them in the decoding pipeline. Done means the tutorial includes an SSD example and a brief formulation explanation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100