Endogenous pathology in tauopathy mice progresses via brain networks
- 1. Department of Neurology, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center; Dallas, TX, USA.
- 2. Allen Institute for Brain Science; Seattle, WA, USA; Cajal Neuroscience; Seattle, WA, USA
- 3. Allen Institute for Brain Science; Seattle, WA, USA; McConnell Brain Imaging Centre, The Neuro (Montreal Neurological Institute-Hospital), McGill University; Montreal, Quebec, Canada
- 4. Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center; Dallas, TX, USA
- 5. Department of Neurology, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center; Dallas, TX, USA
- 6. Institute Pasteur; Paris, France
- 7. Allen Institute for Brain Science; Seattle, WA, USA
- 8. Allen Institute for Brain Science; Seattle, WA, USA.
- 9. Department of Neuroscience, University of Rochester Medical School; Rochester, NY, USA
Description
This archive contains the data and code used for the analyses in the manuscript: “Endogenous pathology in tauopathy mice progresses via brain networks”.
One-Sentence Summary: Whole brain imaging of tau deposition reveals retrograde-dominant network-based propagation in a tauopathy mouse model.
| File | Description |
|---|---|
| Ramirez_etal_ProbMaps_ccf_10um.zip | Registered 8-bit probability maps in the same dimensions as the 10um resolution Allen Institute for Brain Science Common Coordinate Framework atlas. |
| probability_per_structure_background_subtracted.csv | Background-subtracted p-tau intensity values per brain region |
| File (GH release link) | Description |
|---|---|
| https://github.com/julianmeeks/utsw_wbmf_stpt_tau/releases/tag/v1.0.1 | MATLAB scripts and associated files used to compile sample x region matrices of p-tau density. |
| https://github.com/DrJigsaw/tau_network_analysis/releases/tag/v1.0.0 | Code to quantify tau values per structure contrasted against background levels. |
| https://github.com/nikhil153/tau_network_spread_analysis/releases/tag/v1.0.0 | Python scripts and notebooks to 1) define a network based on directional anatomical connectome and 2) fit and compare diffusion models of tau spread. |
Note: Detailed documentation to reproduce analyses and figures in the manuscript is provided on the individual GitHub code repositories listed in the table (file hyperlinks).
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