| --- |
| license: cc-by-nc-4.0 |
| pretty_name: AxoBench v2 |
| task_categories: |
| - time-series-forecasting |
| - tabular-regression |
| tags: |
| - neuroscience |
| - computational-neuroscience |
| - neuron-simulation |
| - single-cell |
| - benchmark |
| - dendrites |
| - interventions |
| --- |
| |
| # AxoBench v2 |
|
|
| AxoBench is a benchmark for data-driven surrogates of layer-5 pyramidal |
| neurons: given six seconds of synaptic input events, predict the somatic |
| voltage and spikes of a detailed NEURON model of the cell. Version 2 covers |
| 15 cells, adds paired interventions at three doses each, and stores the |
| somatic voltage at 4 kHz in addition to the 1 ms targets. |
|
|
| ## Variants |
|
|
| Each variant is a self-contained dataset root in its own top-level folder. |
|
|
| | Folder | Status | Traces per training cell | Size | |
| |---|---|---|---| |
| | `minimal/` | released (tag `minimal-v2.0`) | 2,000 train, 250 val, 250 test | 14.6 GB | |
| | `full/` | released (tag `full-v2.0`) | 8,000 train, 250 val, 250 test | 35.6 GB | |
|
|
| `full/` contains every `minimal/` shard unchanged, plus 6,000 more training |
| traces per training cell. Its `val/`, `test/` and `interventions/` are the |
| same files as in `minimal/`, so scores on the two variants are directly |
| comparable. The extra shards were generated with the same simulator, gains and |
| input statistics, and take shard indices from 20,000 up, so no index or seed |
| of `minimal/` is reused. |
|
|
| Download with the `axobench` package (`axobench download-data --variant full`, |
| or `axobench.hub.download_dataset`), or fetch single folders with |
| `huggingface_hub.snapshot_download(..., allow_patterns=["full/val/*"])`. |
|
|
| ## Cells |
|
|
| - 14 Allen Cell Types all-active models of mouse layer-5 cells with intact |
| apical dendrites (Gouwens et al. 2018), each with its fitted biophysics and |
| a per-cell excitatory gain calibrated to a common firing rate. |
| - The NeuronIO layer-5b cell (Hay et al. 2011, `neuronio_hay_cell1`) as the |
| anchor to earlier work. |
|
|
| Three Allen cells (354190013, 480353286, 488683425) are held out: they appear |
| only in `test` (zero-shot track). `morphologies.json` lists every cell with |
| its source and held-out flag; `morphologies/` holds the Allen SWC files. |
|
|
| ## Layout of `minimal/` and `full/` |
|
|
| | Folder | Content | |
| |---|---| |
| | `train/<cell>/` | `minimal/`: 6,000 shards, 24,000 traces (12 training cells x 2,000); `full/`: 24,000 shards, 96,000 traces (12 x 8,000) | |
| | `val/<cell>/` | 756 shards, 3,000 traces (12 x 250) | |
| | `test/<cell>/` | 945 shards, 3,750 traces (15 x 250) | |
| | `interventions/<condition>_<dose>/` | 15 folders, 600 pairs each (40 per cell), 9,000 pairs in total | |
| | `morphologies/`, `morphologies.json` | cell index and reconstructions | |
| | `dataset_package_manifest.json` | counts per split, cell and condition; generator settings and gains | |
| | `checksums.sha256` | SHA-256 of every file in the variant | |
|
|
| Interventions: event dropout, excitatory dropout and inhibitory dropout at |
| 10, 35 and 70%; site silencing at 10, 25 and 50%; temporal jitter of 1, 2 |
| and 8 ms. |
|
|
| ## Shard schema |
|
|
| Each `.npz` shard has a JSON sidecar with the generator settings. Each split |
| and intervention folder has a `manifest.json` that lists its shards (paths |
| relative to the folder; split shards sit in one subfolder per cell) and sample |
| ids. |
|
|
| - `inputs`: `(n, 6000, 1278)` int8, input events per 1 ms bin on 639 |
| excitatory and 639 inhibitory synapse sites. |
| - `targets`: `(n, 6000, 2)` float32 at 1 ms: spike indicator (0/1) and the |
| NeuronIO-style somatic target, (min(V, -55 mV) + 67.7 mV) / 10. |
| - `soma_mv`: `(n, 6000)` raw somatic voltage (mV) at 1 ms. |
| - `soma_mv_hr`: `(n, 24000)` raw somatic voltage (mV) at 4 kHz. |
| - Intervention shards hold the same arrays with `baseline_` and |
| `intervention_` prefixes, plus `changed_event_mask`. |
|
|
| ## Withheld data |
|
|
| A confirmation split (`private-test`, 125 traces per cell) is not published. |
| Predictions on it are scored on request, rate-limited. |
|
|
| ## License and attribution |
|
|
| The data are released under |
| [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). |
| The Allen cells are simulated on reconstructions and models from the Allen |
| Cell Types Database, whose [Terms of Use](https://alleninstitute.org/terms-of-use/) |
| allow derived works for research and other noncommercial purposes only. |
| Commercial use needs written permission from the Allen Institute. |
|
|
| If you use these data, please cite: |
|
|
| - Allen Institute for Brain Science (2015). Allen Cell Types Database |
| [dataset]. Available from celltypes.brain-map.org. |
| - Gouwens, N. W., et al. (2018). Systematic generation of biophysically |
| detailed models for diverse cortical neuron types. *Nature |
| Communications*, 9, 710. https://doi.org/10.1038/s41467-017-02718-3 |
| - Hay, E., Hill, S., Schürmann, F., Markram, H., & Segev, I. (2011). Models of |
| neocortical layer 5b pyramidal cells capturing a wide range of dendritic and |
| perisomatic active properties. *PLoS Computational Biology*, 7(7), |
| e1002107. https://doi.org/10.1371/journal.pcbi.1002107 |
| - Beniaguev, D., Segev, I., & London, M. (2021). Single cortical neurons as |
| deep artificial neural networks. *Neuron*, 109(17), 2727–2739.e3. |
| https://doi.org/10.1016/j.neuron.2021.07.002 (input statistics and |
| generator design) |
|
|
