Rutledge Robb B, Lazzaro Stephanie C, Lau Brian, Myers Catherine E, Gluck Mark A, Glimcher Paul W
Center for Neural Science, New York University, New York, New York 10003, USA.
J Neurosci. 2009 Dec 2;29(48):15104-14. doi: 10.1523/JNEUROSCI.3524-09.2009.
Making appropriate choices often requires the ability to learn the value of available options from experience. Parkinson's disease is characterized by a loss of dopamine neurons in the substantia nigra, neurons hypothesized to play a role in reinforcement learning. Although previous studies have shown that Parkinson's patients are impaired in tasks involving learning from feedback, they have not directly tested the widely held hypothesis that dopamine neuron activity specifically encodes the reward prediction error signal used in reinforcement learning models. To test a key prediction of this hypothesis, we fit choice behavior from a dynamic foraging task with reinforcement learning models and show that treatment with dopaminergic drugs alters choice behavior in a manner consistent with the theory. More specifically, we found that dopaminergic drugs selectively modulate learning from positive outcomes. We observed no effect of dopaminergic drugs on learning from negative outcomes. We also found a novel dopamine-dependent effect on decision making that is not accounted for by reinforcement learning models: perseveration in choice, independent of reward history, increases with Parkinson's disease and decreases with dopamine therapy.
做出恰当的选择通常需要具备从经验中学习可用选项价值的能力。帕金森病的特征是黑质中多巴胺神经元的丧失，这些神经元被认为在强化学习中发挥作用。尽管先前的研究表明帕金森病患者在涉及从反馈中学习的任务中存在缺陷，但他们尚未直接检验一个广泛持有的假设，即多巴胺神经元活动专门编码强化学习模型中使用的奖励预测误差信号。为了检验这一假设的一个关键预测，我们将动态觅食任务中的选择行为与强化学习模型进行拟合，并表明多巴胺能药物治疗以与该理论一致的方式改变选择行为。更具体地说，我们发现多巴胺能药物选择性地调节从积极结果中学习。我们观察到多巴胺能药物对从消极结果中学习没有影响。我们还发现了一种新的多巴胺依赖的决策效应，强化学习模型无法解释这种效应：与奖励历史无关的选择坚持随着帕金森病的发展而增加，随着多巴胺治疗而减少。
