Roadmap #1
Description
Roadmap
Goal: develop an open platform with educational resources for algorithmic decision-making in neuroscience
Here is a list of milestones for this project.
Milestone: List of tutorials for EEG data
How to apply common algorithms on electroencephalography (EEG) data?
- Loading and visualization of epoch data
- Pre-processing: What are common artifacts? How to reject them? Filtering.
- Statistics: Contrasts between two conditions at single-electrodes. Permutation statistics.
- Machine learning: What features can we have? How to implement cross-validation?
- Machine learning: Common algorithms: LDA / Logistic Regression
- Machine learning: How to visualize features and classification accuracy
- Expand to a different dataset / application
Milestone: Tutorials for signal processing
e.g. filters, time-frequency transforms
- Filters...
- Time-frequency
Milestone: Bind everything together
e.g. through mybinder or Jupyter book
- Test that MyBinder works
- Implement everything in Jupyter book
- Proof read documentation
Milestone: Community building
e.g. gather contributions and expand to other techniques
- Get feedback from neuroscientists
- Seek additional contributors
- Get feedback from students