Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.
Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.
Curr Biol. 2021 Nov 8;31(21):4748-4761.e8. doi: 10.1016/j.cub.2021.08.052. Epub 2021 Sep 15.
A large body of work has aimed to define the precise information encoded by dopaminergic projections innervating the nucleus accumbens (NAc). Prevailing models are based on reward prediction error (RPE) theory, in which dopamine updates associations between rewards and predictive cues by encoding perceived errors between predictions and outcomes. However, RPE cannot describe multiple phenomena to which dopamine is inextricably linked, such as behavior driven by aversive and neutral stimuli. We combined a series of behavioral tasks with direct, subsecond dopamine monitoring in the NAc of mice, machine learning, computational modeling, and optogenetic manipulations to describe behavior and related dopamine release patterns across multiple contingencies reinforced by differentially valenced outcomes. We show that dopamine release only conforms to RPE predictions in a subset of learning scenarios but fits valence-independent perceived saliency encoding across conditions. Here, we provide an extended, comprehensive framework for accumbal dopamine release in behavioral control.
大量研究旨在定义多巴胺能投射支配伏隔核(NAc)所编码的精确信息。流行的模型基于奖励预测误差(RPE)理论,其中多巴胺通过编码预测与结果之间的感知误差,更新奖励与预测线索之间的关联。然而,RPE 无法描述与多巴胺密切相关的多种现象,例如由厌恶和中性刺激驱动的行为。我们结合了一系列行为任务,以及在小鼠 NAc 中进行的直接、亚秒级的多巴胺监测、机器学习、计算建模和光遗传学操作,以描述受不同效价结果强化的多种条件下的行为和相关多巴胺释放模式。我们表明,多巴胺释放仅在学习场景的一个子集符合 RPE 预测,但在条件下符合与效价无关的感知显着性编码。在这里,我们提供了一个扩展的、全面的框架,用于行为控制中的伏隔核多巴胺释放。