{
  "id": "1507.06331",
  "version": "v1",
  "published": "2015-07-22T20:19:55.000Z",
  "updated": "2015-07-22T20:19:55.000Z",
  "title": "A continuous time stochastic model for biological neural nets",
  "authors": [
    "Leonardo Nagami Coregliano"
  ],
  "comment": "17 pages",
  "categories": [
    "math.PR"
  ],
  "abstract": "We propose a new stochastic model for biological neural nets which is a continuous time version of the model proposed by Galves and L\\\"ocherbach in [A. Galves and E. L\\\"ocherbach, \"Infinite systems of interacting chains with memory of variable length - a stochastic model for biological neural nets\", J. Stat. Phys. 151 (2013), no. 5, 896-921]. We also show how to computationally simulate such model for easy neuron potential decays and probability functions and characterize when the model has a finite time of death almost surely.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-07-22T20:19:55.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "60K35",
      "60G99"
    ],
    "keywords": [
      "biological neural nets",
      "continuous time stochastic model",
      "neuron potential decays",
      "infinite systems",
      "continuous time version"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 17,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}