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.

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What this package declares

The file a client reads when it loads this plugin, exactly as this revision carries it.

plugin.json

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "computational-neuroscientist",
  "version": "1.0.0",
  "description": "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.",
  "author": {
    "name": "K-Dense",
    "url": "https://www.k-dense.ai"
  },
  "homepage": "https://github.com/K-Dense-AI/scientific-agents",
  "repository": "https://github.com/K-Dense-AI/scientific-agents",
  "license": "MIT",
  "keywords": [
    "science",
    "agents-md",
    "expert-profile",
    "computational-neuroscientist"
  ]
}