Language and the brain: Implications from new computer models

Abstract

Computer systems for processing and “understanding” natural language have, up to now, used semantic and syntactic procedures that provide meanings of words in terms only of other words or some structural algorithms that ultimately relate to other words. There is a long-standing and widely held belief that words, or their unknown neuronal correlates, are fundamental to verbal meaning, concepts, and thought but over the last decade, evidence has been accumulating in neurology and psychology to indicate that this is not so. We have developed a new computer system for representing the meaning of words and sentences, by which word meanings are described non-verbally in terms of sensorimotor and other modality codes. It is suggested here that the principles of this system might usefully be applied to understanding the cerebral mechanisms of some verbal and cognitive processes and their disorders. In particular the hypothesis is proposed that verbal meaning is essentially non-verbal, and that it may be represented, for both words and sentences in terms of interassociated modal percepts or their neuronal correlates.