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We review evidence that in the course of reading, the visual system computes abstract letter identities (ALIs): a representation of letters that encodes their identity but that abstracts away from their visual appearance. How could the visual system learn such a seemingly nonvisual representation? We propose that different forms of the same letter tend to appear in similar distributions of contexts (in the same words written in different ways) and that this environmental correlation interacts with correlation-based learning mechanisms in the brain to lead to the formation of ALIs. We review a neural network model that demonstrates the feasibility of this common contexts hypothesis and present two experiments confirming some novel predictions: (a) repeatedly presenting arbitrary visual stimuli in common contexts leads those stimuli to be confusable with each other, and (b) different forms of the same letter are more confusable with each other in word-like contexts than in nonword-like contexts. We then extend the model to use real pictures of letters as input and simulate some of the novel empirical findings from the experiments.

This paper presents the results of a study addressing the effect of hands-free cellular phone conversation complexity on choice response time in a detection task. The study utilized an open-loop simulation technique to study four different levels of the secondary task of using a hands-free cellular telephone and their effect on the primary task of responding to stimuli presented through a driving scene. Results from the study showed that the inclusion of the secondary task had a significant effect on choice response time. Also, choice response time associated with complex conversations involving visual scanning was found to be significantly different from that when the phone was not used. The implications of the use of hands-free phones are also discussed.

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