Understanding the effects of constraint and predictability in ERP

Abstract

Strongly constraining contexts should lead to stronger probabilistic representations. If so, unexpected words in strongly constraining contexts should trigger costlier shifts in the representation than expected words. However, psycholinguistic measures commonly used to study probabilistic processing, such as the N400 event-related potential (ERP) component, are sensitive to word predictability but not to contextual constraint. Some research suggests that constraint-related processing cost may be measurable via a positive, anterior ERP deflection following the N400, known as the anterior post-N400 positivity (PNP). The PNP is argued to reflect update of a sentence representation and to be distinct from the posterior P600, which reflects conflict detection and reanalysis. However, constraint-related PNP findings are inconsistent. We sought to conceptually replicate Federmeier et al. (2007) and Kuperberg et al. (2020), who observed that the PNP, but not the N400 or the P600, is affected by constraint at unexpected but plausible words. Using a pre-registered design and statistical approach that maximised power, we demonstrated a dissociated effect of predictability and constraint: strong evidence for predictability but not constraint in the N400 window, and strong evidence for constraint but not predictability in the late window. However, the constraint effect was consistent with a P600 and not a PNP. This suggests strong constraint increased sensitivity to unexpected input rather than increased the cost of shifting a probabilistic representation. We conclude that either a simple strong/weak constraint design is not sufficient to elicit the PNP, or that previous PNP constraint findings could be an artifact of low sample size.