London

Previous studies have shown that comprehenders use rich contextual information to anticipate upcoming input on the fly, but less is known about how comprehenders integrate different sources of information to generate predictions in real time. The current study examines the time course with which the lexical meaning and structural roles of preverbal arguments impact comprehenders ’ verb predictions in two event-related potential (ERP) experiments that use the N400 amplitude as a measure of online predictability. Experiment 1 showed that the N400 was sensitive to the cloze probability of a verb when one of the arguments was substituted (e.g., “The superintendent overheard which tenant/realtor the landlord had evicted…”), but not when the roles of the arguments were simply swapped (e.g., “The restaurant owner forgot which customer/waitress the waitress/customer had served …”). Experiment 2 showed that argument substitution elicited an N400 effect even when the original argument appeared elsewhere in the sentence, indicating that verb predictions are specifically driven by the arguments in the same clause as the verb, rather than by a simple ‘bag-of-words ’ mechanism. We propose that initial verb predictions rely on a ‘bag-of-arguments ’ mechanism, which specifically relies on the lexical meaning, but not the structural roles, of the arguments in a clause