Determining Properties of Synaptic Structure in a Neural Network through Spike Train Analysis
Description:
A "complex" system typically has a relatively large number of dynamically interacting components and tends to exhibit emergent behavior that cannot be explained by analyzing each component separately. A biological neural network is one example of such a system. A multi-agent model of such a network is developed to study the relationships between a network's structure and its spike train output. Using this model, inferences are made about the synaptic structure of networks through cluster analys…
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Date:
May 2007
Creator:
Brooks, Evan
Partner:
UNT Libraries