{
  "annotation_id": "a5d9ff26-5ecc-4d91-a7a7-8626d062a345",
  "date_created": "2026-03-02T18:01:31.475000Z",
  "date_modified": "2026-03-02T18:01:31.475000Z",
  "file_hash": "768c82ae7d82894295eba9d83e1d3e2ff9577d23dd0c66d1f7775b02adf1a07b",
  "private": false,
  "record": {
    "abstract": "Reduced models of neuronal activity such as Integrate-and-Fire models allow a\ndescription of neuronal dynamics in simple, intuitive terms and are easy to\nsimulate numerically. We present a method to fit an Integrate-and-Fire-type\nmodel of neuronal activity, namely a modified version of the Spike Response\nModel, to a detailed Hodgkin-Huxley-type neuron model driven by stochastic\nspike arrival. In the Hogkin-Huxley model, spike arrival at the synapse is\nmodeled by a change of synaptic conductance. For such conductance spike input,\nmore than 70% of the postsynaptic action potentials can be predicted with the\ncorrect timing by the Integrate-and-Fire-type model. The modified Spike\nResponse Model is based upon a linearized theory of conductance-driven\nIntegrate-and-Fire neuron.",
    "arxiv_id": "q-bio/0407010",
    "authors": [
      "Renaud Jolivet",
      "Wulfram Gerstner"
    ],
    "categories": [
      "q-bio.NC"
    ],
    "doi": "10.1016/j.jphysparis.2005.09.010",
    "journal_ref": "Journal of Physiology - Paris 98 (2004) 442--451",
    "title": "Predicting spike times of a detailed conductance-based neuron model   driven by stochastic spike arrival",
    "url": "https://arxiv.org/abs/q-bio/0407010"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4422f6e3-5c83-47da-b6c6-787fd364f718",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}