{
  "annotation_id": "f0b2c5e7-6282-4260-a31f-4ea4699aeed5",
  "date_created": "2026-03-02T18:01:32.355000Z",
  "date_modified": "2026-03-02T18:01:32.355000Z",
  "file_hash": "d379812312f210a0a0ca8b349a6e25a3ff26ee954fbee5b5d666c5ec37c41bad",
  "private": false,
  "record": {
    "abstract": "The analysis of complex networks has revealed patterns of organization in a\nvariety of natural and artificial systems, including neuronal networks of the\nbrain at multiple scales. In this paper, we describe a novel analysis of the\nlarge-scale connectivity between regions of the mammalian cerebral cortex,\nutilizing a set of hierarchical measurements proposed recently. We examine\npreviously identified functional clusters of brain regions in macaque visual\ncortex and cat cortex and find significant differences between such clusters in\nterms of several hierarchical measures, revealing differences in how these\nclusters are embedded in the overall cortical architecture. For example, the\nventral cluster of visual cortex maintains structurally more segregated, less\ndivergent connections than the dorsal cluster, which may point to functionally\ndifferent roles of their constituent brain regions.",
    "arxiv_id": "q-bio/0508007",
    "authors": [
      "Luciano da F. Costa",
      "Olaf Sporns"
    ],
    "categories": [
      "q-bio.NC",
      "cond-mat.dis-nn",
      "q-bio.QM"
    ],
    "doi": "10.1140/epjb/e2006-00017-1",
    "journal_ref": "European Physical Journal B, v. 48, n. 4, p. 567-573, 2005",
    "title": "Hierarchical Features of Large-Scale Cortical Connectivity",
    "url": "https://arxiv.org/abs/q-bio/0508007"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3732742a-243b-44a7-9365-2cdd1b6ed2f2",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}