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Alec Scharff, John Palmer; Distinguishing serial and parallel models using variations of the simultaneous-sequential paradigm. Journal of Vision 2008;8(6):981. doi: https://doi.org/10.1167/8.6.981.
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© ARVO (1962-2015); The Authors (2016-present)
The simultaneous-sequential paradigm employs a visual search task to distinguish alternative models of visual attention. It has been successful at distinguishing unlimited-capacity, parallel models from other alternatives. Here, this paradigm is expanded to also distinguish between serial and limited-capacity, parallel models. The simultaneous-sequential paradigm compares accuracy performance between simultaneous and sequential presentations of otherwise equivalent stimuli. When processing capacity is unlimited, accuracy performance is equivalent for simultaneous and sequential presentations. When capacity is limited, performance improves in sequential presentations. We developed variations on the simultaneous-sequential method to distinguish between other alternative models. One comparison tests for fixed capacity models and another comparison distinguishes serial from limited-capacity, parallel models. In this study, these methods are applied to two test cases: (a) simple feature detection and (b) semantic word categorization. The results provide evidence that contrast increment detection is an unlimited capacity process. The semantic word categorization experiment is in progress.
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