Optimal Processing Times in Reading: A Formal Model and Empirical Investigation

Abstract

It is widely known that humans can respond to events they expect more quickly than to unexpected events, but we still have a poor understanding of why.Models exist that derive a relation between subjective probability and response time on the basis of optimal perceptual discrimination, but these models rely on the ability of the responder control over perceptual sampling of the environment, rendering them problematic for some domains, such as auditory language processing, in which there are nevertheless clear dependencies between probability and response time.We present a new model deriving the relationship between probability and reaction time as a consequence of optimal preparation.This model is valid under very general conditions, requiring only that the results of optimization are invariant across scale of input stimulus granularity.The model makes the strong prediction that response times should scale linearly with the negative conditional log-probability of the stimulus.We present evidence for this prediction in an analysis of an existing database of eye movements in the reading of naturalistic texts.

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