MRC Brain Networks Dynamics Unit, University of Oxford, Oxford, United Kingdom.
Elife. 2020 Jul 7;9:e53262. doi: 10.7554/eLife.53262.
This paper describes a framework for modelling dopamine function in the mammalian brain. It proposes that both learning and action planning involve processes minimizing prediction errors encoded by dopaminergic neurons. In this framework, dopaminergic neurons projecting to different parts of the striatum encode errors in predictions made by the corresponding systems within the basal ganglia. The dopaminergic neurons encode differences between rewards and expectations in the goal-directed system, and differences between the chosen and habitual actions in the habit system. These prediction errors trigger learning about rewards and habit formation, respectively. Additionally, dopaminergic neurons in the goal-directed system play a key role in action planning: They compute the difference between a desired reward and the reward expected from the current motor plan, and they facilitate action planning until this difference diminishes. Presented models account for dopaminergic responses during movements, effects of dopamine depletion on behaviour, and make several experimental predictions.
本文提出了一个用于模拟哺乳动物大脑中多巴胺功能的框架。该框架认为学习和动作规划都涉及到最小化由多巴胺能神经元编码的预测误差的过程。在这个框架中，投射到纹状体不同部位的多巴胺能神经元编码了基底神经节内相应系统做出的预测误差。多巴胺能神经元在目标导向系统中编码了奖励与期望之间的差异，在习惯系统中编码了选择动作与习惯动作之间的差异。这些预测误差分别触发了关于奖励和习惯形成的学习。此外，目标导向系统中的多巴胺能神经元在动作规划中起着关键作用：它们计算期望奖励与当前运动计划预期奖励之间的差异，并在这个差异减小时促进动作规划。提出的模型解释了运动过程中的多巴胺能反应、多巴胺耗竭对行为的影响，并做出了一些实验预测。
