Electroencephalography decoding of Chinese characters in primary school children and its prediction for word reading performance and development

Research on what neural mechanisms facilitate word reading development in non-alphabetic scripts is relatively rare. The present study was among the first to adopt a multivariate pattern classification analysis to decode electroencephalographic signals recorded for primary school children (N = 236) while performing a Chinese character decision task. Chinese is an ideal script for studying the relationship between neural discriminability (i.e., decodability) of the orthography and behavioral word reading skills since the mapping from orthography to phonology is relatively arbitrary in Chinese. This was also among the first empirical attempts to examine the extent to which decoding performance can predict current and subsequent word reading skills using a longitudinal design. Results showed that neural activation patterns of real characters can be distinguished from activation patterns for pseudo-characters, non-characters, and random stroke combinations in both younger and older children. Topography of the transformed classifier weights revealed two distinct cognitive sub-processes underlying single character recognition, but temporal generalization analysis suggested common neural mechanisms between the distinct cognitive sub-processes. Suggestive evidence from correlational and hierarchical regression analyses showed that decoding performance, assessed on average 2 months before the year 2 behavioral testing, predicted both year 1 word reading performance and the development of word reading fluency over the year. Results demonstrate that decoding performance, one indicator of how the neural system is functionally organized in processing characters and character-like stimuli, can serve as a useful neural marker in predicting current word reading skills and the capacity to learn to read.