Bayesian mixed-effects logistic models of participants' responses (DO or PO) during subsequent free-choice production showed that both the prior and current verb biases affected speakers' construction choice. 
Bayesian mixed-effects logistic models
Updating constructions: additive effects of prior and current experience during sentence production.While much earlier work has indicated that prior verb bias from lifelong language experience influences language processing, recent findings highlight the fact that verb biases induced during lab-based exposure sessions also influence processing.  We investigated the nature of updating, i.e., how prior and current experience might interact in guiding subsequent sentence production.  Participants underwent a short training session where we manipulated the bias of known English dative verbs.  The prior bias of each verb for the double-object (DO) versus the prepositional-object (PO) dative was estimated using a corpus.  Current verb bias was counterbalanced and controlled experimentally.  Bayesian mixed-effects logistic models of participants' responses (DO or PO) during subsequent free-choice production showed that both the prior and current verb biases affected speakers' construction choice.  These effects were additive and not interactive, contrary to the prediction from error-based learning models.  Semantic similarity to other verbs and their experimentally manipulated biases influenced sentence production, consistent with item-based analogy and exemplar theory.  These results shed light on the potential mechanisms underlying language updating and the adaptation of sentence production to ongoing experience.
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