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Minds and Machines

, Volume 17, Issue 3, pp 287–309 | Cite as

Automatic Generation of Cognitive Theories using Genetic Programming

  • Enrique Frias-Martinez
  • Fernand Gobet
Article

Abstract

Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming (GP). Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories.

Keywords

Cognitive neuroscience Computational neuroscience Automatic generation of cognitive theories Genetic programming Delayed-match-to-sample 

Notes

Acknowledgment

We thank Guillermo Campitelli for providing advice on the delayed-match-to-sample task, as well as Veronica Dark and anonymous referees for useful comments.

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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.Department of Information Systems and ComputingBrunel UniversityUxbridgeUK
  2. 2.Centre for Cognition and NeuroimagingBrunel UniversityUxbridgeUK

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