Evolving virtual neuronal morphologies: a case study in genetic L-systems programming

Authors:
Benjamin Torben-Nielsen
Affiliations:
Maastricht ICT Competence Centre, Universiteit Maastricht, The Netherlands and Theoretical and Experimental Neurobiology Unit, Okinawa Institute of Science and Technology, Japan
Venue:
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Year:
2007

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Abstract

Virtual neurons are digitized representations of biological neurons, with an emphasis on their morphology. In previous research we presented a proof of principle of reconstructing virtual neuronal morphologies by means of Genetic L-Systems Programming (GLP) [13]. However, the results were limited due to a hard evolutionary search process and a minimalistic fitness function. In this work we analyzed the search process and optimized the GLP configuration to enhance the search process. In addition, we designed a neuron type-specific fitness function which provides an incremental assessment of the evolved structures. The results are significantly better and relevant issues are discussed.