{
  "annotation_id": "77359750-e247-4778-b601-115146aeb89a",
  "date_created": "2026-03-02T18:00:43.215000Z",
  "date_modified": "2026-03-02T18:00:43.215000Z",
  "file_hash": "993e67e31958f639e1e915e68448296a67d456b29c5f3d9eb995b30eccece1fb",
  "private": false,
  "record": {
    "abstract": "This paper summarizes a research program to express the organization of\nsensorimotor control by specifying physiological states and the conditions for\ntransitions among them. By a slight change in standard notation, conditional\ndynamics provides a moving spotlight, focussing on salient subspaces within a\nhigh-dimensional space. This mathematical approach serves as a window on the\norganization of sensorimotor neurobiology. The intertwined efforts to express\nthe intrinsic organization of neurobiology and to clarify it mathematically are\nyielding a mathematical structure that is growing on fertile empirical ground.",
    "arxiv_id": "physics/0211068",
    "authors": [
      "Gin McCollum"
    ],
    "categories": [
      "physics.bio-ph",
      "q-bio"
    ],
    "title": "Developing Mathematics for Insight into Sensorimotor Neurobiology",
    "url": "https://arxiv.org/abs/physics/0211068"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "dcc7aa3b-34fd-4315-9367-4e79d9cd4ada",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}