Age affects reinforcement learning through dopamine-based learning imbalance and high decision noise-not through Parkinsonian mechanisms

Neurobiology of Aging
Ravi B SojitraMark A Gluck

Abstract

Probabilistic reinforcement learning declines in healthy cognitive aging. While some findings suggest impairments are especially conspicuous in learning from rewards, resembling deficits in Parkinson's disease, others also show impairments in learning from punishments. To reconcile these findings, we tested 252 adults from 3 age groups on a probabilistic reinforcement learning task, analyzed trial-by-trial performance with a Q-reinforcement learning model, and correlated both fitted model parameters and behavior to polymorphisms in dopamine-related genes. Analyses revealed that learning from both positive and negative feedback declines with age but through different mechanisms: when learning from negative feedback, older adults were slower due to noisy decision-making; when learning from positive feedback, they tended to settle for a nonoptimal solution due to an imbalance in learning from positive and negative prediction errors. The imbalance was associated with polymorphisms in the DARPP-32 gene and appeared to arise from mechanisms different from those previously attributed to Parkinson's disease. Moreover, this imbalance predicted previous findings on aging using the Probabilistic Selection Task, which were misattributed to...Continue Reading

Citations

Nov 13, 2018·Aging·Itamar LernerMark Gluck
Dec 7, 2018·Frontiers in Cellular Neuroscience·Khadija TayaraRocío M de Pablos
Dec 12, 2018·Cognitive, Affective & Behavioral Neuroscience·Anne S BerryMing Hsu
Oct 17, 2020·Nature and Science of Sleep·Xue-Rui PengJing Yu
Nov 30, 2021·Journal of the International Neuropsychological Society : JINS·Christina E WierengaGregory G Brown

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