| --- |
| license: mit |
| task_categories: |
| - tabular-regression |
| language: |
| - en |
| tags: |
| - neuroscience |
| - computational-neuroscience |
| - acetylcholine |
| - neuromodulation |
| - sim-to-real |
| - jaxley |
| - allen-brain-observatory |
| - neuropixels |
| - biophysical-simulation |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # ACh Cortical Circuits: Cross-Cortical Transfer Dataset |
|
|
| 15,000 simulated cortical microcircuits with acetylcholine (ACh) modulation + 2,678 real mouse V1 recording epochs from the Allen Brain Observatory. |
|
|
| ## Dataset Description |
|
|
| This dataset accompanies the paper **"Cross-Cortical Transfer of Cholinergic Modulation Principles via Biophysical Simulation Surrogates"** (CAISc 2026). |
|
|
| ### Simulated Circuits (15,000 total) |
|
|
| Three mechanistic variants of ACh modulation, each with 5,000 circuits × 11 ACh levels = 55,000 simulations per variant: |
|
|
| | Variant | ACh Mechanism | File | |
| |---------|--------------|------| |
| | **v14a** | Synaptic suppression only (E2 dose-response) | `v14a_circuits.tar.gz` | |
| | **v14b** | Depolarization only (OU mean shift) | `v14b_circuits.tar.gz` | |
| | **v14c** | Both mechanisms combined | `v14c_circuits.tar.gz` | |
|
|
| **Parameters source:** Ramaswamy, Colangelo & Markram (2018), *Frontiers in Neural Circuits* — rat somatosensory cortex (S1). |
|
|
| **Simulator:** [Jaxley](https://github.com/jaxleyverse/jaxley) (JAX-based, GPU-accelerated) |
|
|
| Each circuit JSON contains: |
| - Circuit parameters (n_neurons, connectivity, synaptic conductances, OU noise params) |
| - ACh level (0.0 to 1.0 in 0.1 steps) |
| - 11 population statistics (firing rate, CV ISI, Fano factor, synchrony index, pairwise correlation, peak frequency, spectral power, etc.) |
| |
| ### Allen Brain Observatory Epochs (2,678 total) |
| |
| Real mouse V1 (area VISp) neural recordings from the Allen Brain Observatory Visual Coding Neuropixels dataset: |
| - 2,325 running epochs + 353 stationary epochs |
| - 44 sessions, 16 with both behavioral states |
| - Quality filtered (presence_ratio > 0.95, ISI violations < 0.5) |
| - Same 11 population statistics as simulated data |
|
|
| File: `allen_epochs.tar.gz` |
|
|
| ### Model Checkpoints |
|
|
| 12 trained surrogate models (3 architectures × 3 ACh variants + 3 baselines): |
| - CircuitTransformer (222K params) |
| - CircuitMLP (5.6K params) |
| - XGBoost |
|
|
| File: `checkpoints.tar.gz` |
|
|
| ## Key Results |
|
|
| | Statistic | Model S (syn) | Model D (depol) | Model SD (both) | |
| |-----------|:---:|:---:|:---:| |
| | Pairwise correlation | **75.0%** | 25.0% | 25.0% | |
| | Mean firing rate | 12.5% | **87.5%** | **87.5%** | |
| | Spectral power | **68.8%** | **68.8%** | **68.8%** | |
|
|
| **Key finding:** Synaptic suppression captures correlation structure; depolarization captures rate modulation. The mechanisms are dissociable in sim-to-real transfer. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{neuropeek2026crosstransfer, |
| title={Cross-Cortical Transfer of Cholinergic Modulation Principles via Biophysical Simulation Surrogates}, |
| author={NeuroPeek AI and Basak, Sohan}, |
| booktitle={1st Conference for AI Scientists (CAISc 2026)}, |
| year={2026} |
| } |
| ``` |
|
|
| ## License |
|
|
| MIT |
|
|
| ## Acknowledgments |
|
|
| - Simulation parameters from [Ramaswamy et al. 2018](https://www.frontiersin.org/articles/10.3389/fncir.2018.00077/full) |
| - Real data from [Allen Brain Observatory](https://portal.brain-map.org/) |
| - Simulation engine: [Jaxley](https://github.com/jaxleyverse/jaxley) (Deistler et al., Nature Methods 2025) |
| - Compute: [Modal](https://modal.com/) cloud GPUs (~$230 total) |
| - Built with NeuroPeek AI Agents |
|
|
