Prediction in aging language processing

This thesis explores how predictions about upcoming linguistic stimuli are generated during real-time language comprehension in younger and older adults. Previous research has shown humans' ability to use rich contextual information to compute linguistic prediction during real-time language comprehension. Research in the modulating factors of prediction has shown, first, that predictions are informed by our experience with language and second, that these predictions are modulated by cognitive factors such as working memory and processing speed. However, little is known about how these factors interact in aging in which verbal intelligence remains stable or even increases, whereas processing speed, working memory, and inhibitory control decline with age. Experience-driven models of language learning argue that learning occurs across the life span instead of terminating once representations are learned well enough to approximate a stable state. In relation to aging, these models predict that older adults are likely to possess stronger learned associations, such that the predictions they generate during on-line processing may be stronger. At the same time, however, processing speed, working memory, and inhibitory control decline as a function of age, and age-related declines in these processes may reduce the degree to which older adults can predict. Here, I explored the interplay between language and cognitive factors in the generation of predictions and hypothesized that older adults will show stronger predictability effects than younger adults likely because of their language experience. In this thesis, I provide evidence from reading eye-movements, event-related potentials (ERPs), and EEG phase synchronization, for the role of language experience and cognitive decline in prediction in younger and older English speakers. I demonstrated that the eye-movement record is influenced by linguistic factors, which produce greater predictability effects as linguistic experience advances, and cognitive factors, which produce smaller predictability effects as they decline. Similarly, the N400, an ERP response that is modulated by a word's predictability, was also moderated by cognitive factors. Most importantly, older adults were able to use context efficiently to facilitate upcoming words in the ERP study, contrary to younger adults. Further, I provide initial evidence that coherence analysis may be used as a measure of cognitive effort to illustrate the facilitation that prediction confers to language comprehenders. The results indicate that for a comprehensive account of predictive processing research needs to take into account the role of experience acquired through lifetime and the declines that aging brings.