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Abstract
In recent years, there has been a growing interest in the issue of orthographic processing in visual word recognition. We compare the SERIOL model to parallel models in their ability to explain experimental data at the lexical and sub-lexical levels. We find that the parallel models have difficulty accounting for position-independent letter priming, letter perceptibility patterns, and temporal effects.