Effects of semantic constraint and doze probability on Chinese classifier-noun agreement

This study aims to examine when and how readers make use of top-down information to predict or integrate upcoming words by utilizing the characteristics of Chinese classifier-noun agreement, as measured by event-related potentials (ERPs). Constraint strength of classifiers (strong and weak) and doze probability of the pairing noun (high, low, implausible) was manipulated. Weakly constrained classifiers elicited a less positive P200 and an enhanced frontal negativity than strongly constrained classifiers, suggesting that readers used the preceding classifier to predict the upcoming noun, even before the pairing noun appeared. For ERPs elicited by the pairing nouns, there was a significant interaction between semantic constraint and doze probability for the N400. For nouns following the weakly constrained classifiers, there was a graded doze probability effect on the N400 (High < Low < Imp). For nouns following the strongly constrained classifiers, both low doze and implausible nouns elicited larger N400s than high doze nouns; however, there was no difference between low doze and implausible nouns. The critical comparison for the constraint effect of low doze nouns was found for the N400 but not for frontal positivity, suggesting that the N400 reflects a joint effect of both benefit and cost of prediction. (C) 2014 Elsevier Ltd. All rights reserved.