{
  "annotation_id": "369d3c62-ff43-4140-86be-748ba3cd90c5",
  "date_created": "2026-03-02T18:00:31.991000Z",
  "date_modified": "2026-03-02T18:00:31.991000Z",
  "file_hash": "50865b75657756c166c66546a5a378621d6afeef0ca1341974bf1480d84d9968",
  "private": false,
  "record": {
    "abstract": "The paradigm of stochastic resonance (SR)---the idea that signal detection\nand transmission may benefit from noise---has met with great interest in both\nphysics and the neurosciences. We investigate here the consequences of reducing\nthe dynamics of a periodically driven neuron to a renewal process (stimulation\nwith reset or endogenous stimulation). This greatly simplifies the mathematical\nanalysis, but we show that stochastic resonance as reported earlier occurs in\nthis model only as a consequence of the reduced dynamics.",
    "arxiv_id": "physics/0004075",
    "authors": [
      "Hans E. Plesser",
      "Theo Geisel"
    ],
    "categories": [
      "physics.bio-ph",
      "q-bio"
    ],
    "doi": "10.1103/PhysRevE.63.033101",
    "journal_ref": "Phys Rev E 63:031916",
    "title": "Stochastic Resonance in Neuron Models: Endogenous Stimulation Revisited",
    "url": "https://arxiv.org/abs/physics/0004075"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "46b135cc-5150-4498-a9ea-753c08e3b7d7",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}