mne-tools / mne-tools/mne-python

ENH: Deep source modeling

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ENH
Dominant language
Python
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Description

Describe the new feature or enhancement

looking at roadmap and #6784:

now (since 7.x FS) segment_subregions gives proper subsegmentations (hippo, amygdala, thalamic nuclei, and brainstem), also FS 8.x now runs SynthMorph as part of recon-all so every subject already have subject-to-template deformation field saved. So for morphing problem, instead of trying to inflate surfaces to a sphere, we could just take the saved deformation field and apply it directly to the vertex coordinates and then we can find the corresponding template mesh with nearest neighbour or ICP. no?

I mean these files:

mri/transforms/synthmorph.1.0mm.1.0mm/warp.to.mni152.1.0mm.1.0mm.nii.gz        # subject → MNI152
mri/transforms/synthmorph.1.0mm.1.0mm/warp.to.mni152.1.0mm.1.0mm.inv.nii.gz    # MNI152 → subject
Describe your proposed implementation

if yes, then:

  1. we can modify setup_source_space or new setup_subcortical_source_space to create SourceSpaces
  2. morph with saved volumetric warp, not spherical inflation
  3. and a plotting support in Brain
Describe possible alternatives

.

Additional context

Happy to open PRs for that, but better to discuss first. @larsoner

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading the roadmap section on deep source modeling and issue #6784, then inspect setup_source_space, the proposed setup_subcortical_source_space entry point, and Brain plotting support. Review the listed SynthMorph warp and inverse-warp files. Done would mean agreeing on the design and supporting SourceSpaces creation, volumetric morphing, and plotting for deep source models.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
computer-graphics, data
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
35/100

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