--- 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//` | `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//` | 756 shards, 3,000 traces (12 x 250) | | `test//` | 945 shards, 3,750 traces (15 x 250) | | `interventions/_/` | 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)