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Language and the brain: implications from new computer models

D A Young

    Medical Hypotheses
    |July 1, 1982
    PubMed
    Summary
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    This study introduces a novel computer system representing word meanings non-verbally using sensorimotor codes. This challenges traditional views, suggesting verbal meaning is fundamentally non-verbal, potentially aiding understanding of cognitive processes.

    Area of Science:

    • Computational linguistics
    • Cognitive neuroscience
    • Psycholinguistics

    Background:

    • Traditional natural language processing relies on word-to-word semantic and syntactic analysis.
    • A prevailing belief links verbal meaning, concepts, and thought directly to words or their neural correlates.
    • Recent neurological and psychological evidence challenges this word-centric view of meaning.

    Purpose of the Study:

    • To introduce a novel computer system for representing word and sentence meaning.
    • To propose that verbal meaning is essentially non-verbal.
    • To explore applications in understanding cerebral mechanisms of verbal and cognitive processes and their disorders.

    Main Methods:

    • Development of a new computer system for meaning representation.

    Related Experiment Videos

  • Description of word meanings using non-verbal sensorimotor and other modality codes.
  • Hypothesizing the representation of verbal meaning through interassociated modal percepts or their neural correlates.

    • Main Results:

    • A novel computer system has been developed to represent word meanings non-verbally.
    • Word meanings are described using sensorimotor and other modality codes, moving beyond word-to-word definitions.
    • The system provides a framework for understanding verbal meaning as grounded in perception.

    Conclusions:

    • Verbal meaning may be fundamentally non-verbal, represented by interassociated modal percepts.
    • This non-verbal representation system could offer insights into cognitive processes and their disorders.
    • The findings challenge traditional linguistic theories and suggest new avenues for computational and neuroscientific research.