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Article Dans Une Revue Neurocomputing Année : 2007

Modeling Self-Developing Biological Neural Networks

Résumé

Recent progress in chips-neuron interface suggests real biological neurons as long-term alternatives to silicon transistors. The first step to designing such computing systems is to build an abstract model of self-assembled biological neural networks, much like computer architects manipulate abstract models of transistors. In this article, we propose a model of the structure of biological neural networks. Our model reproduces most of the graph properties exhibited by Caenorhabditis elegans, including its small-world structure and allows generating surrogate networks with realistic biological structure, as would be needed for complex information processing/computing tasks.
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Dates et versions

inria-00149082 , version 1 (24-05-2007)

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Hugues Berry, Olivier Temam. Modeling Self-Developing Biological Neural Networks. Neurocomputing, 2007, 70 (16-18), pp.2723-2734. ⟨10.1016/j.neucom.2006.06.013⟩. ⟨inria-00149082⟩
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