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How Sequential Interactive Processing Within Frontostriatal Loops Supports a Continuum of Habitual to Controlled

Randall C O'Reilly1,2, Ananta Nair2, Jacob L Russin1

  • 1Computational Cognitive Neuroscience Lab, Department of Psychology, Computer Science, and Center for Neuroscience, University of California, Davis, Davis, CA, United States.

Frontiers in Psychology
|March 27, 2020
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Summary
This summary is machine-generated.

This study presents a computational model of frontostriatal loops, showing behavior exists on a continuum between automatic and goal-directed actions. Key differences lie in decision-making iterations and predictive process engagement.

Keywords:
automatic processingbasal gangliacomputational modelingcontrolled processingfrontal cortexgoalshabits

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Area of Science:

  • Computational neuroscience
  • Cognitive neuroscience
  • Neuroscience

Background:

  • Traditional distinctions separate habitual/automatic from goal-directed/controlled behaviors.
  • Frontostriatal loops are critical for action selection and control.
  • Existing frameworks may not fully capture the nuances of behavior regulation.

Purpose of the Study:

  • To propose a computational model of frontostriatal loops that integrates habitual and goal-directed behaviors.
  • To explore the continuum of behavior regulation through iterative decision-making.
  • To re-evaluate the model-based vs. model-free distinction in behavior.

Main Methods:

  • Developed a computational model simulating frontostriatal loop dynamics.
  • Incorporated iterative, multi-step decision-making processes.
  • Modeled basal ganglia's role in evaluating action plans.

Main Results:

  • The model demonstrates a behavioral continuum, blurring traditional distinctions.
  • Habitual actions require an initial 'allowance' decision from an outer loop.
  • Differences in behavior are linked to the number of decision iterations and predictive processing.

Conclusions:

  • Behavioral control exists on a continuum, influenced by frontostriatal loop dynamics.
  • The basal ganglia's dopamine-trained evaluation serializes neural processing.
  • Goal-based inputs challenge the strict model-free categorization of basal ganglia functions.