How 'rational' is semantic prediction? A critique and re-analysis of

Abstract

In a recent article in Cognition, Delaney-Busch et al. (2019) claim evidence for 'rational', Bayesian adaptation of semantic predictions, using ERP data from Lau, Holcomb, and Kuperberg (2013). Participants read associatively related and unrelated prime-target word pairs in a first block with only 10% related trials and a second block with 50%. Related words elicited smaller N400s than unrelated words, and this difference was strongest in the second block, suggesting greater engagement in predictive processing. Using a rational adaptor model, Delaney-Busch et al. argue that the stronger N400 reduction for related words in the second block developed as a function of the number of related trials, and concluded therefore that participants predicted related words more strongly when their predictions were fulfilled more often. In this critique, I discuss two critical flaws in their analyses, namely the confounding of prediction effects with those of lexical frequency and the neglect of data from the first block. Re-analyses suggest a different picture: related words by themselves did not yield support for their conclusion, and the effect of relatedness gradually strengthened in othe two blocks in a similar way. Therefore, the N400 did not yield evidence that participants rationally adapted their semantic predictions. Within the framework proposed by Delaney-Busch et al., presumed semantic predictions may even be thought of as 'irrational'. While these results yielded no evidence for rational or probabilistic prediction, they do suggest that participants became increasingly better at predicting target words from prime words.

Keywords: Bayesian adaptation; Expectation adaptation; Forward association; N400; Probabilistic prediction; Rational adaptation; Semantic priming.