A computational approach to control in complex cognition.

Full Abstract

Cognitive deficits associated with dorsolateral prefrontal cortex (DLPFC) damage are often most apparent in higher cognitive tasks that involve problem solving and managing multiple goals. However, computational models of prefrontal deficits on such tasks are difficult to construct. Problem solving is most naturally modeled with symbolic systems (e.g. production systems), but the effects of lesions are most naturally modeled with subsymbolic systems (neural networks). We show that when we adopt a simple and plausible model of neural computation, there is a natural and explicit mapping from symbolic, goal-driven cognition onto neural computation. We exploit this mapping to construct a neural network model that is capable of solving complex problems in the Tower of London task. The model leads to a specific hypothesis about the role of DLPFC in such tasks, namely, that DLPFC represents internally generated subgoals that modulate competition among posterior representations. When intact, the model accurately simulates the behavior of college students even on the most difficult problems. Furthermore, when the subgoal component is lesioned, it accurately simulates the behavior of prefrontal patients, including the fact that their deficits are most apparent on the most difficult tasks and that they have special difficulty with tasks that require inhibiting a prepotent response.

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Author information

Author/s: Polk, Thad A (TA); Simen, Patrick (P); Lewis, Richard L (RL); Freedman, Eric (E);

Affiliation: Department of Psychology, University of Michigan, 525 E. University, Ann Arbor, MI 48109-1109, USA. tpolk(-atsign-)umich.edu

Journal and publication information

Publication Type: Comparative Study; Journal Article; Review

Journal: Brain research. Cognitive brain research (Brain Res Cogn Brain Res), published in Netherlands. (Language: eng)

Reference: 2002-Dec; vol 15 (issue 1) : pp 71-83

Dates: Created 2002/11/15; Completed 2003/02/07; Revised 2006/11/15;

PMID: 12433383, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Cognition - physiology
Computer Simulation
Goals
Humans
Models, Neurological

Neural Networks (Computer)
Neuropsychological Tests
Prefrontal Cortex - injuries; physiology
Problem Solving - physiology
Task Performance and Analysis

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