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Related Experiment Videos

A computational model of parallel navigation systems in rodents.

Ricardo Chavarriaga1, Thomas Strösslin, Denis Sheynikhovich

  • 1Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Computer and Communication Sciences and Brain Mind Institute, 1015 Lausanne, Switzerland.

Neuroinformatics
|August 4, 2005
PubMed
Summary

Neural systems compete for action selection. A computational model shows distinct locale and taxon strategies, mediated by different brain regions, can be integrated for navigation tasks.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Animal Behavior

Background:

  • Rats exhibit multiple neural systems for action selection to reach goals.
  • Locale navigation (invisible goals) involves hippocampus and ventral/dorsomedial striatum.
  • Taxon strategies (visible goals) are linked to the dorsolateral striatum.

Purpose of the Study:

  • To present a computational model of action selection.
  • To simulate competition between locale and taxon strategies.
  • To test the model in a robot using a paradigm dissociating cue and spatial information.

Main Methods:

  • Developed a computational model with experts for locale and taxon strategies.
  • Simulated robot testing using an experimental paradigm.

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  • Dissociated the use of cue and spatial information in the task.

    • Main Results:

    • The model successfully integrated competing locale and taxon strategies.
    • Demonstrated how different neural systems can be computationally modeled for action selection.
    • Validated the model's ability to choose appropriate behavior based on task demands.

    Conclusions:

    • Multiple neural systems compete to select goal-directed actions.
    • Computational modeling provides a framework for understanding striatal and hippocampal roles in navigation.
    • The model offers insights into the neural basis of behavioral flexibility.