Huys Quentin J M, Tobler Philippe N, Hasler Gregor, Flagel Shelly B
Translational Neuromodeling Unit, Department of Biomedical Engineering, ETH Zürich and University of Zürich, Zürich, Switzerland; Department of Psychiatry, Psychosomatics and Psychotherapy, Hospital of Psychiatry, University of Zürich, Zürich, Switzerland.
Department of Economics, Laboratory for Social and Neural Systems Research, University of Zürich, Zürich, Switzerland.
Prog Brain Res. 2014;211:31-77. doi: 10.1016/B978-0-444-63425-2.00003-9.
Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction.
多巴胺能信号在与奖励相关的学习中发挥着精确的数学作用,多巴胺能信号的变化与成瘾易感性有关。在此,我们详细概述了相位多巴胺信号的理论、数学和实验描述之间的关系,及其对与学习相关的多巴胺信号在成瘾及相关疾病中的作用的影响。我们描述了基于奖励预测误差的无模型学习的理论和行为特征,包括对基础方程的逐步解释。然后,我们利用动物模型的最新见解,该模型突出了经典条件反射范式中学习的个体差异,来描述动机显著性归因和无模型学习的重叠方面。我们认为,这为成瘾的某些特征提供了一个计算连贯的解释。