| --- |
| license: mit |
| tags: |
| - connectomics |
| - simulation-based-inference |
| - neuroscience |
| - computational-biology |
| pretty_name: SBI for Connectomics - Data and Results |
| --- |
| |
| # Dataset Card: SBI for Connectomics — Data and Results |
|
|
| This dataset contains the binary data, inference results, and figures accompanying the paper |
| [Simulation-based inference for efficient identification of generative models in connectomics](https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1). |
|
|
| It is the companion data repository for the code at |
| [github.com/mackelab/sbi-for-connectomics](https://github.com/mackelab/sbi-for-connectomics), which uses |
| [simulation-based inference (SBI)](http://simulation-based-inference.org) to infer parameters of computational |
| wiring-rule models of the rat barrel cortex used in connectomics research. |
|
|
| These files were previously distributed via `git-lfs` in the code repository and have been moved here to keep the |
| git repository lightweight. |
|
|
| ## Dataset structure |
|
|
| ~3.0 GB across 219 binary files, organized into three top-level folders that mirror the paths expected by the |
| code and notebooks in the companion repository: |
|
|
| ``` |
| data/ |
| ├── structural_model/ # masks and feature tables for the structural (barrel cortex) model |
| ├── subcellular_features/ # masks and feature tables for the subcellular model |
| ├── cube_model/ # masks, feature tables, and depth-profile data for the cube model |
| └── presimulated_dso_*.p # presimulated prior/posterior samples for various wiring-rule parameterizations |
| |
| figures/ |
| ├── fig2_structural_model.pdf |
| ├── fig3/ # main-text figure 3 (SBI results) source data/renders |
| ├── fig4-5/ # main-text figures 4-5 (distance-rule results) |
| └── supplementary_figures/ # supplementary figure renders |
| |
| results/ |
| ├── amortized_posterior_*.p # amortized NPE posteriors |
| ├── npe_*.p # NPE posteriors trained on various wiring-rule datasets |
| ├── prior_predictive_*.p / posterior_predictive_*.p |
| ├── sbc_results_*.p # simulation-based calibration results |
| ├── cross_validation_results_*.p |
| └── tutorial_posterior_*.p # posteriors used in the tutorial notebooks |
| ``` |
|
|
| File formats: |
| - `.p` — Python pickle files (mostly `torch`/`sbi` posterior objects and sample arrays; see the companion |
| repository's `consbi` package and notebooks for how they're loaded) |
| - `.txt` / `.tsv` — mask and feature tables for the structural/subcellular/cube models |
| - `.pdf` / `.png` / `.eps` — rendered paper figures |
|
|
| Code, notebooks, and small config/log files (plotting scripts, `.ipynb` notebooks, `.hydra` run configs, etc.) |
| are **not** included here — those remain version-controlled in the |
| [GitHub repository](https://github.com/mackelab/sbi-for-connectomics). |
|
|
| ## How to use |
|
|
| Download directly into a local clone of the [companion repository](https://github.com/mackelab/sbi-for-connectomics) |
| so the folder layout matches what the code expects: |
|
|
| ```shell |
| pip install -U huggingface_hub |
| hf download mackelab/sbi-for-connectomics-data --repo-type dataset --local-dir . |
| ``` |
|
|
| This populates `data/`, `figures/`, and `results/` in the current directory. |
|
|
| ## Citation |
|
|
| If you use this data, please cite the associated paper: |
|
|
| > Simulation-based inference for efficient identification of generative models in connectomics. |
| > https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1 |
|
|
| ## License |
|
|
| MIT License, matching the [companion code repository](https://github.com/mackelab/sbi-for-connectomics/blob/main/LICENSE.md). |
|
|