Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Using probabilistic dependencies improves the search of conductance-based compartmental neuron models
Year:2010
Research Areas
  • Artificial intelligence
Information
Abstract
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.
International
Si
Congress
8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2010
960
Place
Estambul, Turquía
Reviewers
Si
ISBN/ISSN
3-642-12210-8
10.1007/978-3-642-12211-8_15
Start Date
07/04/2010
End Date
09/04/2010
From page
170
To page
181
Proceedings of the 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Participants
  • Autor: Roberto Santana Hermida (UPM)
  • Autor: Maria Concepcion Bielza Lozoya (UPM)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
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