The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language (e.g., Griffiths, Steyvers,…

Expertise in Chinese character recognition is marked by reduced holistic processing (HP), which depends mainly on writing rather than reading experience. Here we show that, while simplified and traditional Chinese readers demonstrated a similar level of HP when processing characters shared between the simplified and traditional scripts, simplified…

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face…