Effects of aging and IQ on item and associative memory.

Abstract

The effects of aging and IQ on performance were examined in four memory tasks: item recognition, associative recognition, cued recall, and free recall. For item and associative recognition, accuracy and the response time distributions for correct and error responses were explained by Ratcliff’s (1978) diffusion model, at the level of individual participants. The values of the components of processing identified by the model for the recognition tasks, as well as accuracy for cued and free recall, were compared across levels of IQ ranging from 85 to 140 and age (college-age, 60-74 year olds, and 75-90 year olds). IQ had large effects on the quality of the evidence from memory on which decisions were based in the recognition tasks and accuracy in the recall tasks, except for the oldest participants for whom some of the measures were near floor values. Drift rates in the recognition tasks, accuracy in the recall tasks, and IQ all correlated strongly with each other. However, there was a small decline in drift rates for item recognition and a large decline for associative recognition and accuracy in cued recall (about 70 percent). In contrast, there were large age effects on boundary separation and nondecision time (which correlated across tasks), but little effect of IQ. The implications of these results for single- and dual- process models of item recognition are discussed and it is concluded that models that deal with both RTs and accuracy are subject to many more constraints than models that deal with only one of these measures. Overall, the results of the study show a complicated but interpretable pattern of interactions that present important targets for response time and memory models.

Parallel interactive retrieval of item and associative information from event memory

“…Older adults have been found to show deficits for associative memory, relative to their memory for individual items (Naveh-Benjamin, 2000; Ratcliff et al, 2011;McKoon & Ratcliff, 2012). These deficits are reduced when the components of the association are already related, rather than representing a novel association (Naveh-Benjamin et al, 2003), consistent with our suggestion that associative information arises from a unitization process that transforms pairs into single items with repeated exposure.…”

How many trials are required for parameter estimation in diffusion modeling? A comparison of different optimization criteria

“…In any diffusion model study, the probably most important issue that a researcher has to examine is validity of parameters. In recent years, several experimental validation studies (e.g., Arnold, Bröder, & Bayen, 2015;Voss et al, 2004;Wagenmakers, Ratcliff, et al, 2008) and correlational analyses (e.g., Ratcliff, Thapar, & McKoon, 2011;Schubert, Hagemann, Voss, Schankin, & Bergmann, 2015) have supplied promising results regarding parameter validity. However, for any new paradigm, the validity has to be first examined.…”

Age-related differences in diffusion model boundary optimality with both trial-limited and time-limited tasks

“…For example, participants use different criteria when verbal instructions focus on speed versus accuracy, showing that criteria can be affected by goals that are defined very broadly. Moreover, participantlevel factors seem to play a large role, given that participants maintain fairly consistent criteria across a range of different decision tasks (Ratcliff, Thapar, & McKoon, 2006;Ratcliff, et al, 2010Ratcliff, et al, , 2011. Thus, a complete account of speedaccuracy settings must consider a broad range of influences and is likely to remain a challenge for quite some time.…”

“…Diffusion model studies have found that aging has little or no effect on drift rates in many tasks (e.g., Ratcliff, Thapar, Gomez, et al, 2004;Ratcliff, Thapar, & McKoon, 2001, 2010Ratcliff et al 2003), although drift rate differences have been observed in some contexts (Ratcliff, Thapar, & McKoon, 2011;. Two other components of processing show much more consistent age differences: Older adults take longer at nondecision components of the task-such as reading a stimulus word or pressing a key once the decision has been made-and older adults set wider boundaries than younger adults.…”