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---
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).