Age affects reinforcement learning through dopamine-based learning imbalance and high decision noise-not through Parkinsonian mechanisms.
Age affects reinforcement learning through dopamine-based learning imbalance and high decision noise-not through Parkinsonian mechanisms.
复制标题
年龄通过基于多巴胺的学习不平衡和高决策噪声影响强化学习,而不是通过帕金森机制。
DOI:
10.1016/j.neurobiolaging.2018.04.006
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发表时间:
2018
影响因子:
4.2
通讯作者:
Gluck,MarkA
中科院分区:
文献类型:
--
作者:
Sojitra,RaviB;Lerner,Itamar;Petok,JessicaR;Gluck,MarkA
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 Parkinsonian mechanisms.