Modelling Rat Behavior in an Elevated Plus-Maze Confronted with Experimental Data

  • Cristiane Salum
  • Silvio Morato
  • Antônio C. Roque-da-Silva-Filho

Abstract

This work describes a neural network model of rat exploratory behavior in the elevated plus-maze, a test used to study anxiety. It involves three parameters: drive to explore, drive to avoid aversive stimuli and spontaneous locomotive activity. Competitive learning is used to generate a sequence of network states each corresponding to a place in the maze. The work also presents experiments made with real rats providing data to be compared with the simulation results. The simulations are consistent with the experimental evidence, and may provide an efficient way of describing anxiety-like behaviors of rats in the elevated plus-maze.

Keywords

Exploratory Behavior Competitive Learning Exploratory Motivation Virtual Animal Virtual Maze 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Cristiane Salum
    • 1
  • Silvio Morato
    • 1
  • Antônio C. Roque-da-Silva-Filho
    • 1
  1. 1.Faculdade de Filosofia, Ciências e Letras de Ribeirão PretoUniversidade de São PauloRibeirão PretoBrazil

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