ME-ICA / ME-ICA/open-multi-echo-data
Exemplar dataset and derivatives
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Description
I haven't made any progress on processing and sharing derivatives for the open multi-echo datasets, but I was thinking that an easier lift that might be useful for testing and for the multi-echo-data-analysis Jupyter Book.
I see this as resulting in three OpenNeuro datasets:
- The raw OpenNeuro dataset, with one subject (and maybe limited to one session?) from each open multi-echo dataset.
- This will require some curation, to deal with any inheritance issues.
- fMRIPrep derivatives
- AFNI derivatives
Contributor guide
No contributing guide indexed for this repository
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 by inventorying the open multi-echo datasets and the inheritance issues mentioned in the issue, then review the multi-echo-data-analysis Jupyter Book to understand its testing needs. Define the scope for one subject or session per source and the expected raw, fMRIPrep, and AFNI OpenNeuro datasets; done means the three curated datasets are shared and usable for those tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100