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The link between brain learning, attention, and consciousness.

S Grossberg1

  • 1Department of Cognitive and Neural Systems, Boston University, MA 02215, USA.

Consciousness and Cognition
|March 12, 1999
PubMed
Summary
This summary is machine-generated.

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Conscious experiences arise from brain processes that learn expectations and match them with sensory input, forming resonant states. Adaptive Resonance Theory (ART) models explain this learning across sensory and cognitive systems.

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • The brain continuously learns about its environment to maintain stable conscious experiences.
  • This learning involves integrating top-down expectations with bottom-up sensory data.
  • Previous models have not fully elucidated the mechanisms underlying stable learning and conscious perception.

Purpose of the Study:

  • To propose a theoretical framework, Adaptive Resonance Theory (ART), explaining how the brain achieves stable learning and conscious experience.
  • To present psychophysical and neurobiological evidence supporting ART across various sensory and cognitive domains.
  • To explore the neural implementation of ART mechanisms in cortical circuits.

Main Methods:

  • Review and synthesis of psychophysical and neurobiological data.

Related Experiment Videos

  • Development of computational models based on ART principles.
  • Analysis of neural circuit mechanisms in visual cortex and prediction for other neocortical areas.

    • Main Results:

    • ART models explain conscious experience as resonant states between top-down expectations and bottom-up data.
    • Evidence from vision, audition, somatosensation, and speech perception supports ART.
    • ART mechanisms are proposed to be realized by laminar circuits in the visual cortex and predicted for other neocortical areas.

    Conclusions:

    • Conscious states are resonant states that drive learning of sensory and cognitive representations.
    • ART provides a unified framework for understanding stable learning and perception.
    • Complementary learning laws in 'What' and 'Where' processing streams allow for stable cognition and adaptive motor control.