{
  "annotation_id": "69f0a46d-2ee2-4424-b5be-507341b62f4a",
  "date_created": "2026-03-02T18:01:30.961000Z",
  "date_modified": "2026-03-02T18:01:30.961000Z",
  "file_hash": "b44d6c33ef30780aade217e947dae14e1a71c2e5490c9a455b4f2835a1a925f5",
  "private": false,
  "record": {
    "abstract": "Analytical expressions are put forward to investigate the forced spiking\nactivity of abstract neuron models such as the driven leaky integrate-and-fire\n(LIF) model. The method is valid in a wide parameter regime beyond the\nrestraining limits of weak driving (linear response) and/or weak noise. The\nnovel approximation is based on a discrete state Markovian modeling of the full\ndynamics with time-dependent rates. The scheme yields very good agreement with\nnumerical Langevin and Fokker-Planck simulations of the full non-stationary\ndynamics for both, the first-passage time statistics and the interspike\ninterval (residence time) distributions.",
    "arxiv_id": "q-bio/0401015",
    "authors": [
      "Michael Schindler",
      "Peter Talkner",
      "Peter H\u00e4nggi"
    ],
    "categories": [
      "q-bio.NC",
      "cond-mat.dis-nn",
      "cond-mat.stat-mech",
      "nlin.AO"
    ],
    "doi": "10.1103/PhysRevLett.93.048102",
    "journal_ref": "Phys. Rev. Lett 93 (2004) 048102",
    "title": "Switching Time Statistics for Driven Neuron Models: Analytic Expressions   versus Numerics",
    "url": "https://arxiv.org/abs/q-bio/0401015"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e0b5224b-48c8-44aa-afcc-3398498d6102",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}