k-dense-ai/computational-neuroscientist
v1.0.0MIT
Reasons from encoding/decoding, GLM/LNP spike-train likelihood, mean-field E-I balance, and neural manifolds through NEST/Brian/NEURON/BMTK, GPFA/LFADS, Brain-Score alignment, and trained-RNN reverse engineering while treating spike-sorting contamination, model non-identifiability, nested-CV leakage, and task-optimization≠mechanism as first-class failure modes.
| Version | Commit | Indexed |
|---|---|---|
| 1.0.0latest | 98c7fae46648 | 2026-10-05 |