Compensatory processing during rule-based category learning in older adults

Abstract

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.

Keywords: Category learning; aging; event-related potentials; rule-based learning.

Figure 1

An example of a rule-based category distribution where categories were determined by spatial frequency regardless of spatial orientation.

Figure 2

Participants saw a stimulus to be categorized after a fixation cross and were asked to press buttons labeled “A” or “B” indicating their categorization decision while the stimulus was on the screen. Feedback on the categorization decision was given in the form of a tone after 500 ms of stimulus offset. EEG was recorded continuously; stimulus- and feedback-locked ERPs were calculated for each trial.

Figure 3

(a) A plot of overall task accuracy and age showing the accuracy-age distribution of YA-Learners, OA-Learners, and OA-Nonlearners. Older adults that achieved 60% or higher categorization accuracy were considered OA-Learners. Accuracy (b) and correct response time (c) from YALearners, OA-Learners, and OA-Nonlearners in each of four 80-trial blocks. (d) Proportion of 80-trial blocks best fit by an RB-F DBT model for each participant. Error bars represent ±1SEM.

Figure 4

(a) Grand average stimulus-locked ERPs and corresponding topographic maps for YA-Learners, Older Adults, OA-Learners, and OA-Nonlearners. The LPC was measured from 400–700 ms (gray shading) from a parietal electrode cluster marked in the topographic maps with black dots. Scatterplots showing the relationship of accuracy to correct minus incorrect mean amplitude ERP subtractions from 400–700 ms for YA-Learners (b) and Older Adults (c) with OA-Learners depicted in solid gray diamonds and OA-Nonlearners depicted in open gray diamonds.

Figure 5

(a) Grand average feedback-locked ERPs and corresponding topographic maps for YA-Learners, Older adults, OA-Learners, and OA-Nonlearners. The P300 was measured from 250–450 ms (gray shading) from an electrode cluster marked in the topographic maps with black dots. Scatterplots showing the relationship of accuracy to correct minus incorrect mean amplitude ERP subtractions from 250–450 ms for YA-Learners (b) and Older Adults (c) with OA-Learners depicted in solid gray diamonds and OA-Nonlearners depicted in open gray diamonds.

Figure 6

Scatterplots showing the relationship of accuracy to correct feedback-locked 250–450 ms mean amplitude ERP and corresponding mean amplitude topographic maps for YA-Learners (a) and OA-Learners (b). Scatterplots showing the relationship of accuracy to incorrect feedback-locked 250–450 ms mean amplitude ERP and corresponding mean amplitude topographic maps for YA-Learners (c) and OA-Learners (d)