{
  "annotation_id": "114d3aac-ce5c-41db-b5dd-9284d252bb4a",
  "date_created": "2026-03-02T18:01:35.301000Z",
  "date_modified": "2026-03-02T18:01:35.301000Z",
  "file_hash": "d53560d523844bff1310c1085b954407c5dbcd2c462e587b9fdac88b18177b41",
  "private": false,
  "record": {
    "abstract": "We studied autoassociative networks in which synapses are noisy on a time\nscale much shorter that the one for the neuron dynamics. In our model a\npresynaptic noise causes postsynaptic depression as recently observed in\nneurobiological systems. This results in a nonequilibrium condition in which\nthe network sensitivity to an external stimulus is enhanced. In particular, the\nfixed points are qualitatively modified, and the system may easily scape from\nthe attractors. As a result, in addition to pattern recognition, the model is\nuseful for class identification and categorization.",
    "arxiv_id": "q-bio/0604021",
    "authors": [
      "J. J. Torres",
      "J. M. Cortes",
      "J. Marro"
    ],
    "categories": [
      "q-bio.NC"
    ],
    "journal_ref": "LNCS 3512: 161-167, 2005",
    "title": "Instability of attractors in autoassociative networks with bioinspired   fast synaptic noise",
    "url": "https://arxiv.org/abs/q-bio/0604021"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b6473157-3679-42ab-9749-c2da047da19f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}