Abstract Current psycholinguistic research generally acknowledges that aspects of sentence comprehension benefit from neural preactivation of different types of information. However, despite strong support from a number of studies, routine specific word form preactivation has been challenged by Ito, Corley, Pickering, Martin, and Nieuwland (2016). They suggest that word form prediction is contingent upon having enough processing time and resources (afforded by slower input rates) to progress through unidirectional, productionlike stages of comprehension to arrive at word forms via semantic feature preactivation. This conclusion is based on findings from their ERP study, which used a related anomaly paradigm and reported form preactivation at a slow (700 ms) word presentation rate but not a faster one (500 ms). The present experimental design is a conceptual replication of Ito et al. (2016), testing young adults by measuring ERP amplitudes to unpredictable words related either semantically/associatively or orthographically to predictable sentence continuations, relative to unrelated continuations. Results showed that, at a visual presentation rate of two words per second, both types of related words show similarly reduced N400s, as well as varying degrees of increased posterior post‐N400 positivity. These findings indicate that word form preactivation during sentence comprehension is detectable along a similar time course as semantic feature preactivation, and such processing does not necessarily require additional time beyond that afforded by near‐normal reading rates.
Metaphorical expressions very often involve words referring to physical entities and experiences. Yet, figures of speech such as metaphors are not intended to be understood literally, word-by-word. We used event-related brain potentials (ERPs) to determine whether metaphorical expressions are processed more like physical or more like abstract expressions. To this end, novel adjective-noun word pairs were presented visually in three conditions: (1) Physical, easy to experience with the senses (e.g., "printed schedule"); (2) Abstract, difficult to experience with the senses (e.g., "conditional schedule"); and (3) novel Metaphorical, expressions with a physical adjective, but a figurative meaning (e.g., "thin schedule"). We replicated the N400 lexical concreteness effect for concrete vs. abstract adjectives. In order to increase the sensitivity of the concreteness manipulation on the expressions, we divided each condition into high and low groups according to rated concreteness. Mirroring the adjective result, we observed a N400 concreteness effect at the noun for physical expressions with high concreteness ratings vs. abstract expressions with low concreteness ratings, even though the nouns per se did not differ in lexical concreteness. Paradoxically, the N400 to nouns in the metaphorical expressions was indistinguishable from that to nouns in the literal abstract expressions, but only for the more concrete subgroup of metaphors; the N400 to the less concrete subgroup of metaphors patterned with that to nouns in the literal concrete expressions. In sum, we not only find evidence for conceptual concreteness separable from lexical concreteness but also that the processing of metaphorical expressions is not driven strictly by either lexical or conceptual concreteness.
Any proposal for predictive language comprehension must address receipt of less expected information. While a relationship between the N400 and sentence predictability is well established, a clear picture is still emerging of the link between post-N400 positivities (PNPs) and processing of semantically unexpected words, as well as any relation to other not-specifically-linguistic and/or syntactic late positivities. The current study employs event-related brain potentials (ERPs) to congruent and anomalous words to assess the impacts of semantic relatedness and contextual plausibility on processing unpredictable sentences. We observe PNPs with different scalp topographies to plausible unexpected words unrelated to predictable continuations (anterior PNP) and to anomalous words, regardless of, but delayed by, relatedness (posterior PNP). We offer functional explanations that reconcile inconsistencies with reported PNP findings and place added constraints on the anterior PNP's proposed link to inhibitory processing. We also suggest a testable general cognitive account for the posterior PNP.
Significance Complex biological systems do not merely react, they anticipate. In 2005, the human-language comprehension system was considered an exception. We concluded not, based on our recordings of electrical brain activity measured before the critical words arrived during sentence reading, described in a now widely cited report. This, and the emergence of the “statistical crisis” in psychology, led to a large-scale replication attempt that failed. This prompted us to revisit the issue by analyzing our original data and two replication extensions with an exploratory data analysis (EDA) approach, enabled by advances in scientific computing technology. Our original conclusion was supported: Brains can anticipate specific upcoming words. We offer this as a case study in EDA for cognitive neurophysiology, more generally.
Abstract This chapter examines linguistic prediction from multiple perspectives, ranging from theoretical models that analyze predictability at the level of ambiguity resolution, to experimental evidence primarily from event-related brain potentials (ERPs) that supports a “strong” model of prediction in which items are not just incrementally integrated, but are wholly or featurally pre-activated via accruing mental sentential representations. It also explores possible consequences of a neural language parser (aka, brain) that may be prone to mispredicting, and what electrophysiological evidence for such processing may look like. The chapter concludes by arguing for the importance of investigating such linguistic effects as yet another example of a neural system in which probability estimation is inherent. It proposes moving beyond the debate of whether there is linguistic prediction, toward focusing research efforts on how pre-activation may occur and what is pre-activated.
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