{
  "annotation_id": "03c14447-0f64-4b64-bf69-7b95e13a6803",
  "date_created": "2026-03-02T18:01:31.933000Z",
  "date_modified": "2026-03-02T18:01:31.933000Z",
  "file_hash": "19e9c2fb529ddab43fda520ca83e5e76e2025f8e349a3c78e3fc72de620492c6",
  "private": false,
  "record": {
    "abstract": "This article discusses how the individual morphological properties of basic\nobjects (e.g. neurons, molecules and aggregates), jointly with their particular\nspatial distribution, can determine the connectivity and dynamics of systems\ncomposed by those objects. This problem is characterized as a particular case\nof the more general shape and function paradigm, which emphasizes the interplay\nbetween shape and function in nature and evolution. Five key issues are\naddressed: (a) how to measure shapes; (b) how to obtain stochastic models of\nclasses of shapes; (c) how to simulate morphologically realistic systems of\nmultiple objects; (d) how to characterize the connectivity and topology of such\nsystems in terms of complex network concepts and measurements; and (e) how the\ndynamics of such systems can be ultimately affected, and even determined, by\nthe individual morphological features of the basic objects. Although emphasis\nis placed on neuromorphic systems, the presented concepts and methods are\nuseful also for several other multiple object systems, such as protein-protein\ninteraction, tissues, aggregates and polymers.",
    "arxiv_id": "q-bio/0503041",
    "authors": [
      "Luciano da Fontoura Costa"
    ],
    "categories": [
      "q-bio.MN",
      "cond-mat.dis-nn"
    ],
    "title": "Morphological complex networks: Can individual morphology determine the   general connectivity and dynamics of networks?",
    "url": "https://arxiv.org/abs/q-bio/0503041"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3d4ca1dc-9dbf-4e86-a97b-0040f1b81e0c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}