Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Coordinate-based coactivation-based parcellation #260

Open
tsalo opened this issue Jun 21, 2020 · 2 comments · May be fixed by #533
Open

Coordinate-based coactivation-based parcellation #260

tsalo opened this issue Jun 21, 2020 · 2 comments · May be fixed by #533
Labels
cbma Issues/PRs pertaining to coordinate-based meta-analysis effort: high Estimated high effort task enhancement New feature or request impact: low Estimated low impact task parcellate Issues/PRs related to the parcellate module. priority: low Not urgent

Comments

@tsalo
Copy link
Member

tsalo commented Jun 21, 2020

Add coactivation-based parcellation algorithm, as described in Bzdok et al. (2013).

References

Bzdok, D., Laird, A. R., Zilles, K., Fox, P. T., & Eickhoff, S. B. (2013). An investigation of the structural, connectional, and functional subspecialization in the human amygdala. Human brain mapping, 34(12), 3247-3266. https://doi.org/10.1002/hbm.22138

@tsalo tsalo added the enhancement New feature or request label Jun 21, 2020
@tsalo
Copy link
Member Author

tsalo commented Jul 8, 2020

Here's a draft of my understanding of the necessary steps:

  1. For each voxel in the mask, identify studies in dataset corresponding to that voxel. Selection criteria can be either based on a distance threshold (e.g., all studies with foci within 5mm of voxel) or based on a minimum number of studies (e.g., the 50 studies reporting foci closest to the voxel).
  2. For each voxel, perform MACM (meta-analysis) using the identified studies.
  3. Correlate statistical maps between voxel MACMs to generate n_voxels X n_voxels correlation matrix.
  4. Convert correlation coefficients to correlation distance (1 - r) values.
  5. Perform clustering on correlation distance matrix.

@tsalo tsalo changed the title Coactivation-based parcellation Coordinate-based coactivation-based parcellation Jul 23, 2020
@tsalo tsalo added the cbma Issues/PRs pertaining to coordinate-based meta-analysis label Apr 20, 2021
@tsalo tsalo linked a pull request Jun 30, 2021 that will close this issue
11 tasks
@tsalo
Copy link
Member Author

tsalo commented Jun 30, 2021

Will compare Bzdok 2013 approach to Chase 2020.

@tsalo tsalo added priority: low Not urgent effort: high Estimated high effort task impact: low Estimated low impact task parcellate Issues/PRs related to the parcellate module. labels Jan 5, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
cbma Issues/PRs pertaining to coordinate-based meta-analysis effort: high Estimated high effort task enhancement New feature or request impact: low Estimated low impact task parcellate Issues/PRs related to the parcellate module. priority: low Not urgent
Projects
None yet
Development

Successfully merging a pull request may close this issue.

1 participant