{
  "id": "cond-mat/0112463",
  "version": "v1",
  "published": "2001-12-26T22:43:27.000Z",
  "updated": "2001-12-26T22:43:27.000Z",
  "title": "Gauge Symmetry and Neural Networks",
  "authors": [
    "Tetsuo Matsui"
  ],
  "comment": "9 pages, 7 figures",
  "journal": "pp. 271-280 in \"Fluctuating Paths and Fields\"ed. by W.Janke et al., World Scientific (2001)",
  "categories": [
    "cond-mat.dis-nn",
    "hep-lat",
    "q-bio"
  ],
  "abstract": "We propose a new model of neural network. It consists of spin variables to describe the state of neurons as in the Hopfield model and new gauge variables to describe the state of synapses. The model possesses local gauge symmetry and resembles lattice gauge theory of high-energy physics. Time dependence of synapses describes the process of learning. The mean field theory predicts a new phase corresponding to confinement phase, in which brain loses ablility of learning and memory.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2001-12-26T22:43:27.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "neural network",
      "model possesses local gauge symmetry",
      "resembles lattice gauge theory",
      "mean field theory predicts",
      "brain loses ablility"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 9,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "inspire": 569046,
      "adsabs": "2001cond.mat.12463M"
    }
  }
}