A biologically based model for the integration of sensory–motor contingencies in rules and plans: A prefrontal cortex based extension of the Distributed Adaptive Control architecture

Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologicall...

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Bibliographic Details
Published inBrain research bulletin Vol. 85; no. 5; pp. 289 - 304
Main Authors Duff, Armin, Sanchez Fibla, Marti, Verschure, Paul F.M.J.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 30.06.2011
Subjects
Animals
Autonomous synthetic agents
Distributed Adaptive Control
Humans
Intelligence
Learning - physiology
Models, Neurological
Neurology
Neuropsychological Tests
Planning
Prefrontal cortex
Prefrontal Cortex - anatomy & histology
Prefrontal Cortex - physiology
Psychomotor Performance - physiology
Rule learning and switching
User-Computer Interface
Distributed Adaptive Control
Model
Rule learning and switching
Planning
Prefrontal cortex
Autonomous synthetic agents
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Summary:Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents.
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ISSN:0361-9230
1873-2747
1873-2747
DOI:10.1016/j.brainresbull.2010.11.008