Not enough, or maybe too much: Associative deficit vs. hyper-binding models of aging in implicit learning
Year: 2019
Type: article
Abstract: Background. This project investigated the effects of cognitive aging on implicit learning [IL] by testing the competing predictions of two models. One model, the Associative Deficit Hypothesis [ADH], suggests that older adults [OAs] have a specific deficit in their ability to form new relationships in memory, whereas the Hyper-Binding Hypothesis [HBH] suggests that age differences in IL stem from attentional changes in later life. Aims. We contrasted the predictions of these models by addressing the following aims: 1. Determine whether OAs show more context dependence in IL tasks than younger adults. 2. Determine whether OAs show greater interference from unattended stimuli during IL tasks than younger adults. Method. We tested context dependence using a novel protocol that manipulated the informativity of objects and their contexts during a word-learning task, and we adapted an established protocol to examine interference from unattended linguistic stimuli. Results. Neither protocol revealed reliable main effects of age on the learning measure, counter to the predictions of both the ADH and the HBH, although this may be a result of relatively small sample sizes and a wide age range in the older age group. Both experiments provided tentative support of the HBH in their higher-order interactions, but some interactions in the interference protocol contradicted elements of the HBH’s predictions. Post-experimental interviews suggested that participants completed the contextual dependence protocol implicitly but may have been explicitly aware of the patterns present in the interference protocol. Future studies should focus on narrowing the age range of older participants and increasing sample sizes, and in the case of the interference protocol, separating effects of different sources of interference (i.e. interference from attended stimuli versus interference from unattended stimuli.)
Author: Rebecca A. Hayes
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2947032123