Does entropy modulate the prediction of German long-distance verb particles?

• Published in: PloS one 2022-08, Vol.17 (8), p.e0267813
• Main Authors: Stone, Kate, Vasishth, Shravan, von der Malsburg, Titus
• Format: Article
• Language: English
• Subjects: Bayes Theorem; Bayesian analysis; Biology and Life Sciences; Context effects (Psychology); Electroencephalography; Entropy; Entropy (Information theory); Evaluation; Event-related potentials; Evoked Potentials; Female; Humans; Language; Male; Medicine and Health Sciences; Physical Sciences; Predictions; Reading; Research and Analysis Methods; Semantics; Social Sciences; Uncertainty
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0267813

In this paper we examine the effect of uncertainty on readers' predictions about meaning. In particular, we were interested in how uncertainty might influence the likelihood of committing to a specific sentence meaning. We conducted two event-related potential (ERP) experiments using particle verbs such as turn down and manipulated uncertainty by constraining the context such that readers could be either highly certain about the identity of a distant verb particle, such as turn the bed […] down, or less certain due to competing particles, such as turn the music […] up/down. The study was conducted in German, where verb particles appear clause-finally and may be separated from the verb by a large amount of material. We hypothesised that this separation would encourage readers to predict the particle, and that high certainty would make prediction of a specific particle more likely than lower certainty. If a specific particle was predicted, this would reflect a strong commitment to sentence meaning that should incur a higher processing cost if the prediction is wrong. If a specific particle was less likely to be predicted, commitment should be weaker and the processing cost of a wrong prediction lower. If true, this could suggest that uncertainty discourages predictions via an unacceptable cost-benefit ratio. However, given the clear predictions made by the literature, it was surprisingly unclear whether the uncertainty manipulation affected the two ERP components studied, the N400 and the PNP. Bayes factor analyses showed that evidence for our a priori hypothesised effect sizes was inconclusive, although there was decisive evidence against a priori hypothesised effect sizes larger than 1μV for the N400 and larger than 3μV for the PNP. We attribute the inconclusive finding to the properties of verb-particle dependencies that differ from the verb-noun dependencies in which the N400 and PNP are often studied.