add a notebook for comparing cbmr and cbma on neurosynth - #835
add a notebook for comparing cbmr and cbma on neurosynth#835yifan0330 wants to merge 12 commits into
Conversation
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #835 +/- ##
=========================================
+ Coverage 0 89.07% +89.07%
=========================================
Files 0 48 +48
Lines 0 6113 +6113
=========================================
+ Hits 0 5445 +5445
- Misses 0 668 +668 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
|
jdkent
left a comment
There was a problem hiding this comment.
just some spelling errors to fix for now!
| # of spatial intensity between pain studies and non-pain studies in Neurosynth. | ||
| # The null hypothesis assumes spatial intensity estimations of two groups are equal | ||
| # at voxel level, $H_0: \mu_{1j}=\mu_{2j}, j=1,\cdots,N$, where $N$ is number of | ||
| # voxels within brain mask, $j$ is the index of voxel. Areas with significant p-vaules |
There was a problem hiding this comment.
| # voxels within brain mask, $j$ is the index of voxel. Areas with significant p-vaules | |
| # voxels within brain mask, $j$ is the index of voxel. Areas with significant p-values |
| # The null hypothesis assumes spatial intensity estimations of two groups are equal | ||
| # at voxel level, $H_0: \mu_{1j}=\mu_{2j}, j=1,\cdots,N$, where $N$ is number of | ||
| # voxels within brain mask, $j$ is the index of voxel. Areas with significant p-vaules | ||
| # (siginificant difference in spatial intensity estimation between two groups) are |
There was a problem hiding this comment.
| # (siginificant difference in spatial intensity estimation between two groups) are | |
| # (significant difference in spatial intensity estimation between two groups) are |
| # voxels within brain mask, $j$ is the index of voxel. Areas with significant p-vaules | ||
| # (siginificant difference in spatial intensity estimation between two groups) are | ||
| # highlighted. We found that estimated activation level are significantly different | ||
| # in ... between pain group and non-pain group. |
There was a problem hiding this comment.
| # in ... between pain group and non-pain group. | |
| # in ... between the pain group and non-pain group. |
| # Run MKDA on Neurosynth dataset | ||
| # ----------------------------------------------------------------------------- | ||
| # For the purpose of justifying the validity of CBMR framework, we compare the estimated | ||
| # spatial covergence of activation regions between pain studies and non-pain fMRI studies |
There was a problem hiding this comment.
| # spatial covergence of activation regions between pain studies and non-pain fMRI studies | |
| # spatial convergence of activation regions between pain studies and non-pain fMRI studies |
| ) | ||
|
|
||
| ############################################################################### | ||
| # This figure (displayed as z-statistics map) shows MKDA spatial covergence of |
There was a problem hiding this comment.
| # This figure (displayed as z-statistics map) shows MKDA spatial covergence of | |
| # This figure (displayed as a z-statistic map) shows MKDA spatial convergence of |
| coordinate-based meta-analysis (CBMA) in NiMARE | ||
|
|
||
| CBMR is a generative framework to approximate smooth activation intensity function and investigate | ||
| the effect of study-level moderators (e.g., year of pubilication, sample size, subtype of stimuli). |
There was a problem hiding this comment.
| the effect of study-level moderators (e.g., year of pubilication, sample size, subtype of stimuli). | |
| the effect of study-level moderators (e.g., year of publication, sample size, subtype of stimuli). |
| This tutorial is intended to provide an intuitive comparison of CBMA and MKDA results on | ||
| neurosynth dataset. | ||
|
|
||
| For more detailed introduction to CBMR implementation in NiMARE, see the `CBMR tutoral |
There was a problem hiding this comment.
| For more detailed introduction to CBMR implementation in NiMARE, see the `CBMR tutoral | |
| For more detailed introduction to CBMR implementation in NiMARE, see the `CBMR tutorial |
|
|
||
| For more detailed introduction to CBMR implementation in NiMARE, see the `CBMR tutoral | ||
| <https://nimare.readthedocs.io/en/latest/auto_examples/02_meta-analyses/11_plot_cbmr.html>`_ and | ||
| `documatation <https://nimare.readthedocs.io/en/latest/generated/nimare.meta.cbmr.html>`_. |
There was a problem hiding this comment.
| `documatation <https://nimare.readthedocs.io/en/latest/generated/nimare.meta.cbmr.html>`_. | |
| `documentation <https://nimare.readthedocs.io/en/latest/generated/nimare.meta.cbmr.html>`_. |
| ############################################################################### | ||
| # Download the Neurosynth Dataset | ||
| # ----------------------------------------------------------------------------- | ||
| # Neurosynth is a large-scale functional magnetic resonance imaing (fMRI) database. |
There was a problem hiding this comment.
| # Neurosynth is a large-scale functional magnetic resonance imaing (fMRI) database. | |
| # Neurosynth is a large-scale functional magnetic resonance imaging (fMRI) database. |
Sorry for the spelling errors! I've fixed them now |
| neurosynth_dset = download_abstracts(neurosynth_dset, "example@example.edu") | ||
| neurosynth_dset.save(os.path.join(out_dir, "neurosynth_dataset_with_abstracts.pkl.gz")) |
There was a problem hiding this comment.
think this bit can be removed, we are not using abstracts for this notebook
jdkent
left a comment
There was a problem hiding this comment.
Sorry for changing my mind about this, could you add a .ipynb notebook to misc-notebooks with the cells executed? Since this notebook is a bit intensive it would be nice to have a version of this where the code is already run and visible.
Closes # .
Changes proposed in this pull request: