{
  "annotation_id": "7a7b4a77-af09-45f9-b8a5-65d39ebcbcf4",
  "date_created": "2026-03-02T18:01:35.501000Z",
  "date_modified": "2026-03-02T18:01:35.501000Z",
  "file_hash": "344e9c082132aefb6c989bbf3049f94b32e0c160bf4fa546edd10a58d936f116",
  "private": false,
  "record": {
    "abstract": "We present a neurobiologically--inspired stochastic cellular automaton whose\nstate jumps with time between the attractors corresponding to a series of\nstored patterns. The jumping varies from regular to chaotic as the model\nparameters are modified. The resulting irregular behavior, which mimics the\nstate of attention in which a systems shows a great adaptability to changing\nstimulus, is a consequence in the model of short--time presynaptic noise which\ninduces synaptic depression. We discuss results from both a mean--field\nanalysis and Monte Carlo simulations.",
    "arxiv_id": "q-bio/0604020",
    "authors": [
      "J. Marro",
      "J. J. Torres",
      "J. M. Cortes"
    ],
    "categories": [
      "q-bio.NC"
    ],
    "title": "Chaotic hopping between attractors in neural networks",
    "url": "https://arxiv.org/abs/q-bio/0604020"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "d3beb0ca-ca79-44b8-bcdb-af6b33eb5c9e",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}