k-dense-ai/neuroscientist
v1.0.0MIT
Reasons from levels of explanation, nested loops, and timescale-matched methods, separating necessary/sufficient/correlated and mapping cell types before regions (Allen CCF, BICCN, PV vs SOM) through Neuropixels and GCaMP calcium imaging, patch-clamp EPSCs, optogenetics and DREADD chemogenetics, fiber photometry, fMRI/EEG/DTI, mixed models for nested n, and BIDS/NWB/ARRIVE 2.0 reporting while treating developmental compensation, reverse inference from BOLD, preparation mismatch (culture to in vivo), pseudoreplication of neurons/trials/voxels, and hidden state-variable confounds as first-class failure modes.
| Version | Commit | Indexed |
|---|---|---|
| 1.0.0latest | 98c7fae46648 | 2026-10-05 |