From pre-activation to pre-updating: A threshold mechanism for commitment to strong predictions

Graded and ungraded expectation patterns: Prediction dynamics during active comprehension

Language comprehension can be facilitated by the accurate prediction of upcoming words, but prediction effects are not ubiquitous, and comprehenders likely use predictive processing to varying degrees depending on task demands. To ascertain the processing consequences of prioritizing prediction, we here compared ERPs elicited when young adult participants simply read for comprehension with those collected in a subsequent block that required active prediction. We were particularly interested in frontally-distributed post-N400 effects for expected and unexpected words in strongly constraining contexts, which have previously been documented as two distinct patterns: an enhanced positivity ("anterior positivity") observed for prediction violations compared to words that are merely unpredictable (because they occur in weakly constraining sentences) and a distinction between expected endings in more constraining contexts and those same weakly constrained words ("frontal negativity" to the strongly predicted words). We found that the size of the anterior positivity effect was unchanged between passive comprehension and active prediction, suggesting that some processes related to prediction may engage state-like networks. On the other hand, the frontal negativity showed graded patterns from the interaction of task and sentence type. These differing patterns support the hypothesis that there are two separate effects with frontal scalp distributions that occur after the N400 and further suggest that the impact of violating predictions (as long as prediction is engaged at all) is largely stable across varying levels of effort/attention directed toward prediction, whereas other comprehension processes can be modulated by task demands.

Context-specific effects of violated expectations: ERP evidence

A complete understanding of the predictive processing effect in sentence comprehension needs to understand both the facilitation effect of successful prediction and the cost associated with disconfirmed predictions. The current study compares the predictive processing effect across two types of contexts in Mandarin Chinese: the classifier-noun vs. verb-noun phrases, when controlling for the degree of contextual constraints and cloze probability of the target nouns across the two contexts. The two contexts showed similar N400 patterns for expected target nouns, indicative of an identical facilitation effect of confirmed contextual expectation. But in the post-N400 time window, the processing cost associated with the unexpected words differed between the two contexts. Additional differences between the two contexts were also revealed by the neural oscillation patterns obtained prior to the target noun. The differences between the classifier vs. verb contexts shed new light on the revision mechanism that deals with disconfirmed expectations.

Adaptation in Predictive Prosodic Processing in Bilinguals

Native language listeners engage in predictive processing in many processing situations and adapt their predictive processing to the statistics of the input. In contrast, second language listeners engage in predictive processing in fewer processing situations. The current study uses eye-tracking data from two experiments in bilinguals’ native language (L1) and second language (L2) to explore their predictive processing based on contrastive pitch accent cues, and their adaptation in the face of prediction errors. The results of the first experiment show inhibition effects for unpredicted referents in both the L1 and the L2 that can be modeled with a Bayesian adaptation model, suggesting that bilinguals adapt their prediction in the face of prediction errors in a way that is compatible with the model. In contrast, the results of the second experiment, after a training phase that increased the predictive validity of the cue, show inhibition effects for unpredicted referents only in the L1, but not in the L2. In addition, the Bayesian adaptation model significantly predicts only the L1, but not the L2 data. The results are discussed with respect to adaptation to the statistical properties of the input.

Rational Adaptation in Lexical Prediction: The Influence of Prediction Strength

Recent studies indicate that the processing of an unexpected word is costly when the initial, disconfirmed prediction was strong. This penalty was suggested to stem from commitment to the strongly predicted word, requiring its inhibition when disconfirmed. Additional studies show that comprehenders rationally adapt their predictions in different situations. In the current study, we hypothesized that since the disconfirmation of strong predictions incurs costs, it would also trigger adaptation mechanisms influencing the processing of subsequent (potentially) strong predictions. In two experiments (in Hebrew and English), participants made speeded congruency judgments on two-word phrases in which the first word was either highly constraining (e.g., “climate,” which strongly predicts “change”) or not (e.g., “vegetable,” which does not have any highly probable completion). We manipulated the proportion of disconfirmed predictions in highly constraining contexts between participants. The results provide additional evidence of the costs associated with the disconfirmation of strong predictions. Moreover, they show a reduction in these costs when participants experience a high proportion of disconfirmed strong predictions throughout the experiment, indicating that participants adjust the strength of their predictions when strong prediction is discouraged. We formulate a Bayesian adaptation model whereby prediction failure cost is weighted by the participant’s belief (updated on each trial) about the likelihood of encountering the expected word, and show that it accounts for the trial-by-trial data.