Modelling Word Recognition and Reading Aloud

Computational modeling of word recognition is one of the most active and promising areas of Cognitive Psychology. Indeed, over the past 30 years, computational modelling has tremendously advanced our understanding of the core processes involved in normal and impaired reading. The present special issue offers a unique collection of cutting edge research on modeling word recognition and reading aloud. Key issues include self-organized learning of orthographic representations, models of multi-syllabic reading, modelling masked priming and the front-end of reading, rule-based versus statistical learning, and interactive-activation accounts of rapid phonological activation and multi-syllabic processing.