Neuron PRM: A framework for constructing cortical networks

Jyh Ming Lien, Marco Morales, Nancy M. Amato

Research output: Contribution to journalArticlepeer-review


The brain's extraordinary computational power to represent and interpret complex natural environments is essentially determined by the topology and geometry of the brain's architectures. We present a framework to construct cortical networks which borrows from probabilistic roadmap methods developed for robotic motion planning. We abstract the network as a large-scale directed graph, and use L-systems and statistical data to 'grow' neurons that are morphologically indistinguishable from real neurons. We detect connections (synapses) between neurons using geometric proximity tests.

Original languageEnglish (US)
Pages (from-to)191-197
Number of pages7
StatePublished - Jun 2003
Externally publishedYes


  • BTS
  • Cortical networks
  • L-system
  • PRM
  • Rectangle tree

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence


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