ERP representational similarity analysis reveals the prediction of semantic features in minimal phrasal contexts

Existing studies demonstrate that comprehenders can predict semantic information during language comprehension. Most evidence comes from a highly constraining context and it is less investigated that whether individuals predict following semantic information in a less constraining context. In the present study, we investigated semantic prediction when reading minimal adjective-noun phrases using electroencephalography (EEG) combined with representational similarity analysis (RSA). Native Chinese Mandarin comprehenders were presented with animate-constraining or inanimate-constraining adjectives, followed by animate-congruent or animate-incongruent nouns. EEG amplitude analysis revealed an N400 for incongruent conditions. Critically, we quantified the similarity between patterns of neural activity, and animate-constraining adjectives revealed greater similarity than inanimate-constraining adjectives before the presentation of the nouns. This pre-noun similarity effect suggests pre-activation of animacy-related semantic information of nouns, and provides evidence for the prediction of semantic features of upcoming words, even in minimal phrase contexts.