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Abstract
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| Conductance-based compartmental neuron models are traditionally used to investigate the electrophysiological properties of neurons. These models require a number of parameters to be adjusted to biological experimental data and this question can be posed as an optimization problem. In this paper we investigate the behavior of different estimation of distribution algorithms (EDAs) for this problem. We focus on studying the influence that the interactions between the neuron model conductances have in the complexity of the optimization problem. We support evidence that the use of these interactions during the optimization process can improve the EDA behavior. | |
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International
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Si |
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Congress
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8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2010 |
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960 |
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Place
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Estambul, Turquía |
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Reviewers
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Si |
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ISBN/ISSN
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3-642-12210-8 |
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10.1007/978-3-642-12211-8_15 |
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Start Date
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07/04/2010 |
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End Date
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09/04/2010 |
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From page
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170 |
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To page
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181 |
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Proceedings of the 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics |