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Related Experiment Videos

Computational approaches to cognition: top-down approaches

J L McClelland1, D C Plaut

  • 1Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890.

Current Opinion in Neurobiology
|April 1, 1993
PubMed
Summary

Connectionist computational models offer new insights into human cognition and brain function. These models link cognitive processes to physiology and help understand cognitive disorders.

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Computational Neuroscience

Background:

  • Computational models are essential for understanding human cognitive processes.
  • Connectionist models provide novel frameworks for cognitive research.
  • These models bridge the gap between cognitive functions and brain mechanisms.

Purpose of the Study:

  • To explore the utility of computational models in cognitive science.
  • To highlight the role of connectionist models in understanding cognition.
  • To demonstrate how computational approaches can link cognitive processes to neural implementation.

Main Methods:

  • Utilizing connectionist modeling to simulate cognitive functions.
  • Linking computational outputs to underlying physiological mechanisms.

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  • Applying models to explain perception, memory, language, and development.

    • Main Results:

    • Connectionist models offer new explanations for core cognitive functions.
    • These models facilitate the integration of cognitive processes with brain mechanisms.
    • The approach aids in understanding the cognitive consequences of brain dysfunction.

    Conclusions:

    • Computational models, particularly connectionist ones, are powerful tools for cognitive research.
    • They provide a framework for linking cognitive phenomena to neural substrates.
    • These models enhance our understanding of both normal cognition and cognitive disorders.