The P600 as a continuous index of integration effort.

The integration of word meaning into an unfolding utterance representation is a core operation of incremental language comprehension. There is considerable debate, however, as to which component of the ERP signal-the N400 or the P600-directly reflects integrative processes, with far reaching consequences for the temporal organization and architecture of the comprehension system. Multi-stream models maintaining the N400 as integration crucially rely on the presence of a semantically attractive plausible alternative interpretation to account for the absence of an N400 effect in response to certain semantic anomalies, as reported in previous studies. The single-stream Retrieval-Integration account posits the P600 as an index of integration, further predicting that its amplitude varies continuously with integrative effort. Here, we directly test these competing hypotheses using a context manipulation design in which a semantically attractive alternative is either available or not, and target word plausibility is varied across three levels. An initial self-paced reading study revealed graded reading times for plausibility, suggesting differential integration effort. A subsequent ERP study showed no N400 differences across conditions, and that P600 amplitude is graded for plausibility. These findings are inconsistent with the interpretation of the N400 as an index of integration, as no N400 effect emerged even in the absence of a semantically attractive alternative. By contrast, the link between plausibility, reading times, and P600 amplitude supports the view that the P600 is a continuous index of integration effort. More generally, our results support a single-stream architecture and eschew the need for multi-stream accounts.

Retrieval (N400) and integration (P600) in expectation-based comprehension.

Expectation-based theories of language processing, such as Surprisal theory, are supported by evidence of anticipation effects in both behavioural and neurophysiological measures. Online measures of language processing, however, are known to be influenced by factors such as lexical association that are distinct from-but often confounded with-expectancy. An open question therefore is whether a specific locus of expectancy related effects can be established in neural and behavioral processing correlates. We address this question in an event-related potential experiment and a self-paced reading experiment that independently cross expectancy and lexical association in a context manipulation design. We find that event-related potentials reveal that the N400 is sensitive to both expectancy and lexical association, while the P600 is modulated only by expectancy. Reading times, in turn, reveal effects of both association and expectancy in the first spillover region, followed by effects of expectancy alone in the second spillover region. These findings are consistent with the Retrieval-Integration account of language comprehension, according to which lexical retrieval (N400) is facilitated for words that are both expected and associated, whereas integration difficulty (P600) will be greater for unexpected words alone. Further, an exploratory analysis suggests that the P600 is not merely sensitive to expectancy violations, but rather, that there is a continuous relation. Taken together, these results suggest that the P600, like reading times, may reflect a meaning-centric notion of Surprisal in language comprehension.

Evaluating information-theoretic measures of word prediction in naturalistic sentence reading.

We review information-theoretic measures of cognitive load during sentence processing that have been used to quantify word prediction effort. Two such measures, surprisal and next-word entropy, suffer from shortcomings when employed for a predictive processing view. We propose a novel metric, lookahead information gain, that can overcome these short-comings. We estimate the different measures using probabilistic language models. Subsequently, we put them to the test by analysing how well the estimated measures predict human processing effort in three data sets of naturalistic sentence reading. Our results replicate the well known effect of surprisal on word reading effort, but do not indicate a role of next-word entropy or lookahead information gain. Our computational results suggest that, in a predictive processing system, the costs of predicting may outweigh the gains. This idea poses a potential limit to the value of a predictive mechanism for the processing of language. The result illustrates the unresolved problem of finding estimations of word-by-word prediction that, first, are truly independent of perceptual processing of the to-be-predicted words, second, are statistically reliable predictors of experimental data, and third, can be derived from more general assumptions about the cognitive processes involved.