{
  "annotation_id": "41e7b99a-f99c-45d3-814d-1e0588706771",
  "date_created": "2026-03-02T18:00:47.043000Z",
  "date_modified": "2026-03-02T18:00:47.043000Z",
  "file_hash": "01c6bd58a2c50f63159f4d097774a1d91f99c6dd037571e463fe9d2c70083c07",
  "private": false,
  "record": {
    "abstract": "Learning and memory may rely on the ability of neuronal circuits to\nreorganize by dendritic spine remodeling. We have looked for geometrical\nparameters of cortical circuits, which maximize information storage capacity\nassociated with this mechanism. In particular, we calculated optimal volume\nfractions of various neuropil components. The optimal axonal and dendritic\nvolume fractions are not significantly different from anatomical measurements\nin the mouse and rat neocortex, and the rat hippocampus. This has led us to\npropose that the maximization of information storage capacity associated with\ndendritic spine remodeling may have been an important driving force in the\nevolution of the cortex.",
    "arxiv_id": "physics/0307065",
    "authors": [
      "Armen Stepanyants"
    ],
    "categories": [
      "physics.bio-ph",
      "cond-mat.soft",
      "physics.gen-ph",
      "q-bio.NC"
    ],
    "title": "Has the Brain Maximized its Information Storage Capacity?",
    "url": "https://arxiv.org/abs/physics/0307065"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "ed8571f4-01c6-483e-bed0-ad2ef4aa67b1",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}