McRae, K. 1 , Metusalem, R. 2 , Kutas, M. . 2 , Urbach, T. P. 2 , Hare, M. 3 & Elman, J. L. 2
1 University of Western Ontario
2 University of California, San Diego
3 Bowling Green State University
People possess a wide range of knowledge regarding real-world events, and recent research has demonstrated that this knowledge plays an important role in guiding prediction and integration during incremental language comprehension. However, the nature of event knowledge activation during online language comprehension is not fully understood. The present study focused on the degree of generality of online event knowledge activation. One possibility is that activation is limited to elements of an event that meet the constraints imposed by the local linguistic context (i.e., the concept predicted to occur at a specific point in the linguistic stream). It is also possible that activation extends more generally to knowledge associated with the event, regardless of local contextual fit. The present study addressed this issue by analyzing event-related brain potentials (ERPs) recorded as participants read three-sentence scenarios describing common real-world events. The final sentence of each scenario contained a target word that was either expected, anomalous and unrelated to the event described, or anomalous but related to the event. Analyses of ERPs elicited by these target types showed differences among the three conditions. The N400 was smallest for the expected word, and largest for the anomalous, event-unrelated word, replicating previous effects of prediction during language comprehension. For the condition that is novel in the present study, a zero-cloze anomalous word that is consistent with the event/scenario, the N400 was both larger than for the expected word, and smaller than for the anomalous, event-unrelated word. These results demonstrate that during the course of comprehension, comprehenders activate general knowledge associated with the described event, even when the specific concept is not an appropriate continuation of the linguistic input at that precise point in time. Thus, generalized event knowledge is available to immediately influence language processing, and it drives predictive processing during language comprehension.