An ERP megastudy of Chinese word recognition

Abstract This article reports the first ERP (event‐related potential) megastudy in traditional Chinese word recognition. Fifty‐one native Chinese undergraduates in Hong Kong, who were native Cantonese speakers, provided ERP data to 1020 two‐character words and 204 two‐character pseudowords in a go/no‐go lexical decision task (go trials: pseudowords). The item list and the ERP data were compiled into a database called “E‐MELD” (ERP MEgastudy of Lexical Decision). To illustrate how E‐MELD can be utilized in research of traditional Chinese word recognition, a series of linear mixed‐effects (LME) models were conducted to examine how properties at word (contextual diversity, number of strokes, and concreteness) and character (contextual diversity, number of homophones, and semantic transparency ratings) levels influenced the ERP amplitudes in different time windows. The results showed that in all time windows, both word and character variables influenced the amplitudes of ERP signals, which argued against the proposal that Chinese two‐character words are recognized holistically. At the same time, there was no evidence that character effects preceded word effects (i.e., no evidence of character‐mediated word recognition). Overall, the pattern suggests that characters and words are accessed simultaneously in Chinese word recognition. E‐MELD is made available online, such that interested researchers can download it and use the data innovatively for their research purpose.