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A hierarchical neuronal network for planning behavior

S Dehaene1, J P Changeux

  • 1Institut National de la Santé et de la Recherche Médicale Unité 344, Service Hospitalier Frédéric Joliot, CEA/DRM/DSV, Orsay, France. dehaene@shfj.cea.fr

Proceedings of the National Academy of Sciences of the United States of America
|December 16, 1997
PubMed
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This study presents a neuronal network model for sequence planning, mimicking human prefrontal cortex functions. The model successfully navigates the Tower of London test and replicates deficits observed in patients with prefrontal cortex lesions.

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Goal-directed behavior planning is a complex cognitive function dependent on prefrontal cortex integrity.
  • Prefrontal cortex lesions impair sequential planning, as evidenced by deficits in tasks like the Tower of London test.

Purpose of the Study:

  • To propose and validate a neuronal network model capable of simulating sequence planning.
  • To demonstrate that the model replicates the planning deficits observed in patients with prefrontal cortex lesions.

Main Methods:

  • Development of a hierarchical neuronal network model with descending planning (plan, operation, gesture levels) and ascending evaluative systems.
  • The model incorporates internal reward signals for plan evaluation and adaptation.

Related Experiment Videos

  • Testing the model's performance on the Tower of London task and simulating lesion effects.

    • Main Results:

    • The proposed neuronal network model successfully passes the Tower of London test.
    • Simulated lesions to the model's prefrontal cortical areas result in planning deficits analogous to those seen in human patients.

    Conclusions:

    • The model provides a computational framework for understanding sequence planning and executive functions.
    • Hierarchically organized neuronal assemblies can collectively emulate central executive functions of the brain.