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Autonomic responses to choice outcomes: Links to task performance and reinforcement-learning parameters

机译:选择结果的自主反应:与任务性能和强化学习参数的联系

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Previous work has shown that autonomic responses to choice feedback can predict subsequent decision-making. In this study, we tested whether skin conductance responses (SCRs) and heart rate (HR) decelerations following the presentation of choice outcomes predict Iowa Gambling Task performance in nonclinical participants (n = 64). We also examined how these signals related to parameters of a reinforcement-learning (RL) model. Feedback SCRs and HR decelerations were greater following outcomes that included losses and choices from the bad decks defined by their negative expected value. In addition, SCRs predicted task performance. A hierarchical Bayesian RL model indicated that greater feedback SCR for the bad decks compared to good decks was associated with stronger loss aversion and a lower learning rate, both of which predicted higher performance. These results suggest that feedback-related SCRs are linked to individual differences in outcome evaluation and learning processes that guide reinforcement-learning.
机译:以前的工作表明,自主反应选择反馈可以预测后续决策。在这项研究中,我们在选择结果的演示后测试了皮肤电导响应(SCR)和心率(HR)减速,预测了非临床参与者(n = 64)中的IOWA赌博任务表现。我们还检查了与增强学习(RL)模型的参数相关的这些信号。反馈SCR和HR减速是更大的结果,其中包括损失和由其负期望值定义的坏甲板的损失和选择。此外,SCR预计任务性能。分层贝叶斯RL模型表明,与良好甲板相比,错误甲板的更大反馈SCR与较强的损耗厌恶和较低的学习率相关,这两者都预测了更高的性能。这些结果表明,反馈相关的SCR与指导加强学习的结果评估和学习过程中的个体差异有关。

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