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Breakthrough to awareness: a preliminary neural network model of conscious and unconscious perception in word processing.

J G Taylor

Biological Cybernetics July 1, 1996 DOI: 10.1007/bf00238740 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Humans Consciousness Memory Speech perception Subliminal stimulation Reaction time Models, neurological Cybernetics Neural networks, computer
Key points Proposes a two-module neural network model in which an unconscious semantic memory module and a conscious working memory module, differing in lateral connectivity and output function, account for subliminal effects on reaction time. The authors report the model gives a good fit to Marcel's data on polysemous word processing and suggest further tests and a possible cortical implementation.

Abstract

A neural network model is constructed to mimic the processing involved in semantic and working memory when subliminal effects are involved. These effects involve modifications of reaction time to later inputs, according to whether or not there has been conscious or unconscious processing of the earlier input. The model is constructed of two separate modules: one (a semantic memory module) allowing for processing at a semantic, but unconscious, level, and the other (a working memory module) for conscious experience. The latter module, although a replica of the earlier one, has different lateral connectivity and output function from the former. The model is shown to give a good fit to Marcel's data on the processing of polysemous words. Further tests are suggested for the model, and a possible cortical implementation suggested. The relevance of the model to recent approaches to consciousness is also explored.

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