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Initial results from the use of learning classifier systems to control in vitro neuronal networks

Published: 07 July 2007 Publication History

Abstract

In this paper we describe the use of a learning classifier system to control the electrical stimulation of cultured neuronal networks. The aim is to manipulate the environment of the cells such that they display elementary learning, i.e., so that they respond to a given input signal in a pre-specified way. Results indicate that this is possible and that the learned stimulation protocols identify seemingly fundamental properties of in vitro neuronal networks.allUse of another learning scheme and simpler stimulation confirms these properties.

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 July 2007

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Author Tags

  1. XCS
  2. multi-electrode array
  3. unconventional computation

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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