Timing is everything: the temporal dynamics of word prediction

Much recent work indicates that anticipating upcoming input is critical to the speed and accuracy of language comprehension, but little is known about how quickly the predictions themselves are generated in real time, and based on what information sources. The current study demonstrates a new method for isolating sub-components of predictive processes and provides some of the first insights into how these processes unfold in real time. In three ERP experiments we took advantage of the word order properties of Mandarin Chinese to examine the time course with which argument role information impacts verb prediction. We isolated the contribution of argument role information by manipulating the order of pre-verbal noun phrase arguments while holding lexical information constant, and we examined its effects on accessing the verb in long-term semantic memory by measuring the amplitude of the N400 component. Experiment 1 showed that when the verb appeared immediately after its arguments, even strongly constraining argument role information failed to modulate the N400 response to the verb. An N400 effect emerged in Experiment 2 when the verb appeared at a greater delay. Experiment 3 corroborated the contrast between the first two experiments through a within-participants manipulation of the time interval between the arguments and the verb, by varying the position of an adverbial phrase. These findings indicate that prediction is not instantaneous, contrary to what is implicitly assumed by many existing computational models, and suggest that the time course with which different sources of information become available to predictive mechanisms may be key to understanding variation in online comprehension success within different speaker populations and communicative contexts.