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Neuron PRM: a framework for constructing cortical networks

delete2003-06-01
delete5
PRE
AI
J
Jyh-Ming Lien
M
Marco Morales
N
Nancy M. Amato
DOI：10.1016/S0925-2312(02)00728-2delete
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Abstract

Abstract

En 中文
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. (C) 2003 Elsevier Science B.V. All rights reserved.
Keywords:
cortical networks
PRM
BTS
L-system
rectangle tree

Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

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No organization information available