Mathar David, Wilkinson Leonora, Holl Anna K, Neumann Jane, Deserno Lorenz, Villringer Arno, Jahanshahi Marjan, Horstmann Annette
Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Leipzig University Medical Center, IFB Adiposity Diseases, Leipzig, Germany.
Behavioral Neurology Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
Cortex. 2017 May;90:149-162. doi: 10.1016/j.cortex.2016.09.004. Epub 2016 Sep 19.
Incidental learning of appropriate stimulus-response associations is crucial for optimal functioning within our complex environment. Positive and negative prediction errors (PEs) serve as neural teaching signals within distinct ('direct'/'indirect') dopaminergic pathways to update associations and optimize subsequent behavior. Using a computational reinforcement learning model, we assessed learning from positive and negative PEs on a probabilistic task (Weather Prediction Task - WPT) in three populations that allow different inferences on the role of dopamine (DA) signals: (1) Healthy volunteers that repeatedly underwent [C]raclopride Positron Emission Tomography (PET), allowing for assessment of striatal DA release during learning, (2) Parkinson's disease (PD) patients tested both on and off L-DOPA medication, (3) early Huntington's disease (HD) patients, a disease that is associated with hyper-activation of the 'direct' pathway. Our results show that learning from positive and negative feedback on the WPT is intimately linked to different aspects of dopaminergic transmission. In healthy individuals, the difference in [C]raclopride binding potential (BP) as a measure for striatal DA release was linearly associated with the positive learning rate. Further, asymmetry between baseline DA tone in the left and right ventral striatum was negatively associated with learning from positive PEs. Female patients with early HD exhibited exaggerated learning rates from positive feedback. In contrast, dopaminergic tone predicted learning from negative feedback, as indicated by an inverted u-shaped association observed with baseline [C]raclopride BP in healthy controls and the difference between PD patients' learning rate on and off dopaminergic medication. Thus, the ability to learn from positive and negative feedback is a sensitive marker for the integrity of dopaminergic signal transmission in the 'direct' and 'indirect' dopaminergic pathways. The present data are interesting beyond clinical context in that imbalances of dopaminergic signaling have not only been observed for neurological and psychiatric conditions but also been proposed for obesity and adolescence.
在我们复杂的环境中,偶然学习适当的刺激-反应关联对于最佳功能发挥至关重要。正性和负性预测误差(PEs)作为不同(“直接”/“间接”)多巴胺能通路中的神经教学信号,用于更新关联并优化后续行为。我们使用计算强化学习模型,在三个群体中评估了在概率任务(天气预报任务 - WPT)中从正性和负性PEs进行的学习,这三个群体能够对多巴胺(DA)信号的作用进行不同的推断:(1)反复接受[C]雷氯必利正电子发射断层扫描(PET)的健康志愿者,从而能够在学习过程中评估纹状体DA释放;(2)在左旋多巴药物治疗期间和停药后进行测试的帕金森病(PD)患者;(3)早期亨廷顿病(HD)患者,这是一种与“直接”通路过度激活相关的疾病。我们的结果表明,在WPT上从正性和负性反馈进行的学习与多巴胺能传递的不同方面密切相关。在健康个体中,作为纹状体DA释放指标的[C]雷氯必利结合潜能(BP)差异与正性学习率呈线性相关。此外,左右腹侧纹状体基线DA水平的不对称与从正性PEs进行的学习呈负相关。早期HD的女性患者从正性反馈中表现出夸张的学习率。相比之下,多巴胺能张力预测了从负性反馈进行的学习,这在健康对照中通过与基线[C]雷氯必利BP观察到的倒U形关联以及PD患者在多巴胺能药物治疗期间和停药后的学习率差异得以体现。因此,从正性和负性反馈进行学习的能力是多巴胺能信号在“直接”和“间接”多巴胺能通路中传递完整性的敏感标志物。目前的数据在临床背景之外也很有趣,因为多巴胺能信号失衡不仅在神经和精神疾病中被观察到,在肥胖和青春期也有相关报道。