Familiarization May Minimize Age-Related Declines in Rule-Based Category Learning

Rabi, Rahel; Minda, John Paul

doi:10.31219/osf.io/7vkwz

Cited by 2 publications

(3 citation statements)

References 24 publications

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“…Similar patterns of performance have been observed when comparing younger adults with older adults (Rabi & Minda, 2016, 2017. As with children, older adults sometimes struggle relative to younger adults with tasks that are dependent on working memory, executive functioning, and cognitive flexibility.…”

Section: The Role Of Cognitive Flexibility In Category Learningsupporting

confidence: 63%

The relationship between depressive symptoms, hypomanic symptoms, mood, and category learning.

Nielsen¹,

Minda²

2018

Preprint

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Participants completed several self-assessments that measured depressive symptoms, hypomania, and mood. They were then asked to learn either a set of rule-based categories or a set of non-rule-based categories. Correlational analyses suggested that participants with high levels of self-reported depression were impaired on complex rule learning. In contrast, performance on a rule-based learning task was found to be improved by high levels of current positive mood. Multiple linear regression analyses further revealed that, when the variance due to other constructs was removed, the relationship between depressive symptoms and rulebased performance disappeared while the relationship between positive mood and rule-based performance remained significant. These findings suggest that positive mood is related to enhanced rule learning abilities. Neither level of depression nor positive mood were found to be related to performance on categories that could be learned via associative processes. This dissociation provides evidence for a dual systems approach to categorization. These findings also suggest that executive functioning impairments observed among individuals with depression may be specifically related to a lack of positive mood rather than overall depressive symptoms, per se. Stimuli, data, and analysis code is available at https://osf.io/35pt6/.

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Section: The Role Of Cognitive Flexibility In Category Learningsupporting

confidence: 63%

The relationship between depressive symptoms, hypomanic symptoms, mood, and category learning.

Nielsen¹,

Minda²

2018

Preprint

Self Cite

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“…Finally, the present study examines the fit of several computational models to the behavioral data at successive points in the category learning trajectory in order to understand how strategies may change with time (Filoteo, Lauritzen, & Maddox, 2010;Nadler, Rabi, & Minda, 2010;Rabi & Minda, 2017) . This is particularly informative for the conjunctive rule category set, as we predict that participants will first acquire the single-dimensional, suboptimal rules and will then shift to the more complicated and optimal conjunctive rule.…”

Section: Rationale For the Present Researchmentioning

confidence: 99%

“…For insight into the response strategies used by our participants, we fit several classes of decision boundary models to each block of each participant's data (for additional details see (Ashby, 1992;Filoteo et al, 2010;Maddox & Ashby, 1993;Rabi & Minda, 2017;Zeithamova & Maddox, 2006) . Two unidimensional models were fit to each observer's responses.…”

Section: F Igure 3 Average Proportion Of Correct Categorization Respmentioning

confidence: 99%

Cognitive changes in conjunctive rule-based category learning: An ERP approach

Rabi

Joanisse

Zhu

et al. 2018

Cogn Affect Behav Neurosci

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When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared to easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.

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Familiarization May Minimize Age-Related Declines in Rule-Based Category Learning

Cited by 2 publications

References 24 publications

The relationship between depressive symptoms, hypomanic symptoms, mood, and category learning.

The relationship between depressive symptoms, hypomanic symptoms, mood, and category learning.

Cognitive changes in conjunctive rule-based category learning: An ERP approach

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