{
  "annotation_id": "4141ad63-15aa-4b60-9e98-347cac225713",
  "date_created": "2026-03-02T18:01:35.503000Z",
  "date_modified": "2026-03-02T18:01:35.503000Z",
  "file_hash": "e0b233376597174472088cc0521e44b9669398ead33e1fcea5d10d4c7c4b5a54",
  "private": false,
  "record": {
    "abstract": "We study the effect of competition between short-term synaptic depression and\nfacilitation on the dynamical properties of attractor neural networks, using\nMonte Carlo simulation and a mean field analysis. Depending on the balance\nbetween depression, facilitation and the noise, the network displays different\nbehaviours, including associative memory and switching of the activity between\ndifferent attractors. We conclude that synaptic facilitation enhances the\nattractor instability in a way that (i) intensifies the system adaptability to\nexternal stimuli, which is in agreement with experiments, and (ii) favours the\nretrieval of information with less error during short--time intervals.",
    "arxiv_id": "q-bio/0604019",
    "authors": [
      "J. J. Torres",
      "J. M. Cortes",
      "J. Marro",
      "H. J. Kappen"
    ],
    "categories": [
      "q-bio.NC"
    ],
    "title": "Competition between synaptic depression and facilitation in attractor   neural networks",
    "url": "https://arxiv.org/abs/q-bio/0604019"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "bc70940a-05c9-4eff-814a-d81eda752146",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}