{
  "annotation_id": "685d9b86-c3b4-46e3-9309-ceabcce643b5",
  "date_created": "2026-03-02T18:01:34.948000Z",
  "date_modified": "2026-03-02T18:01:34.948000Z",
  "file_hash": "79ecbcb25ecf307b3e1257763e604a1ae356ae4b5eebff30d7f672102881b19b",
  "private": false,
  "record": {
    "abstract": "We propose a model for description of activity-dependent evolution and\nself-wiring between binary neurons. Specifically, this model can be used for\ninvestigation of growth of neuronal connectivity in the developing neocortex.\nBy using computational simulations with appropriate training pattern sequences,\nwe show that long-term memory can be encoded in neuronal connectivity and that\nthe external stimulations form part of the functioning neocortical circuit. It\nis proposed that such binary neuron representations of point-like cortical\nneurons fail to reproduce cytoarchitectural differences of the neocortical\norganization, which has implications for inadequacies of compartmental models.",
    "arxiv_id": "q-bio/0607002",
    "authors": [
      "Fail M. Gafarov"
    ],
    "categories": [
      "q-bio.NC",
      "cond-mat.dis-nn"
    ],
    "journal_ref": "Journal of Integrative Neuroscience, Vol. 5, No. 2(2006) 159-169",
    "title": "Self-wiring in neural nets of point-like cortical neurons fails to   reproduce cytoarchitectural differences",
    "url": "https://arxiv.org/abs/q-bio/0607002"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "750a38fd-7d46-4169-9c13-35f6aa3fc0cf",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}