Aging and individual differences in binding during sentence understanding: Evidence from temporary and global syntactic attachment ambiguities

Abstract

We report an investigation of aging and individual differences in binding information during sentence understanding. An age-continuous sample of adults (N = 91), ranging from 18 to 81 years of age, read sentences in which a relative clause could be attached high to a head noun NP1, attached low to its modifying prepositional phrase NP2 (e.g., The son of the princess who scratched himself / herself in public was humiliated), or in which the attachment site of the relative clause was ultimately indeterminate (e.g., The maid of the princess who scratched herself in public was humiliated). Word-by-word reading times and comprehension (e.g., who scratched?) were measured. A series of mixed-effects models were fit to the data, revealing: (1) that, on average, NP1-attached sentences were harder to process and comprehend than NP2-attached sentences; (2) that these average effects were independently moderated by verbal working memory capacity and reading experience, with effects that were most pronounced in the oldest participants and; (3) that readers on average did not allocate extra time to resolve global ambiguities, though older adults with higher working memory span did. Findings are discussed in relation to current models of lifespan cognitive development, working memory, language experience, and the role of prosodic segmentation strategies in reading. Collectively, these data suggest that aging brings differences in sentence understanding, and these differences may depend on independent influences of verbal working memory capacity and reading experience.

Revisiting the incremental effects of context on word processing: Evidence from single‐word event‐related brain potentials

“…The use of (generalized) linear mixed-effects models (also known as hierarchical linear models, multilevel models, or variance components models) has been prevalent in social science, biology, education, and behavioral research for some time (e.g., Singer, 1998;Snijders & Bosker, 2011). Recently, these modeling techniques have begun to gain ground in psycholinguistics, cognitive psychology, and cognitive neuroscience research as a tool to accommodate statistical dependency that arises from the kinds of nested and hierarchically structured data that are common in these fields (Aarts, Verhage, Veenvliet, Dolan, & van der Sluis, 2014;Baayen, Davidson, & Bates, 2008;Jaeger, 2008;Lazic, 2010;Locker, Hoffman, & Bovaird, 2007;Payne et al, 2014). The linear mixed-effects model is a special (restricted) case of models that are commonly used in psychophysiology, including repeated measures (mixed-effects) analysis of variance (ANOVA) and ordinary least-squares regression.…”

How aging and bilingualism influence language processing

“…Age-related changes have also been reported in language comprehension, especially for complex sentences (Payne et al, 2014; Wlotko et al, 2010). Given the age-related changes in a number of cognitive abilities (including verbal and non-verbal working memory, cognitive speed, and attention) which are central for successful on-line processing of syntactically complex and/or at times ambiguous sentences the question of how changes in memory resources affect language comprehension has been a central issue in the literature on language processing and aging.…”

AI Meets Austen: Towards Human-Robot Discussions of Literary Metaphor

“…They have been underutilized in informal learning settings, which may call for robots to tackle fuzzier objectives for which open-ended conversation is a better avenue of interaction. Reading is a cognitively rewarding way to engage in informal lifelong learning [2,4,15,16,22,23], but the potential for companion robots to play a role in motivating lifelong reading behaviors has remained untapped. We set out to fill that void by developing a proof-of-concept embodied conversational companion capable of engaging readers in discussions about books.…”