Conscious and unconscious perception: A computational theory
We propose a computational theory of consciousness and model data from three
experiments in visual perception. The central idea of our theory is that the
contents of consciousness correspond to temporally stable states in an
interconnected net work of specialized computational modules. Each module
incorporates a relaxation search that is concerned with achieving
semantically well-formed states. We claim that being an attractor of the
relaxation search is a necessary condition for awareness. We show that the
model provides sensible explanations for the results of three experiments, and
makes testable predictions. The first experiment (Marcel, 1980) found that
masked, ambiguous prime words facilitate lexical decision for targets related
to either prime meaning, whereas consciously perceived primes facilitate only
the meaning that is consistent with prior context. The second experiment
(Fehrer & Raab, 1962) found that subjects can make detection responses in
constant time to simple visual stimuli regardless of whether they are
consciously perceived or masked by metacontrast and not consciously perceived.
The third experiment (Levy & Pashler, 1996) found that visual word
recognition accuracy is lower than baseline when an earlier speeded response
was incorrect, and higher than baseline when the early response was correct,
consistent with a causal relationship between conscious perception and
subsequent processing.
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