Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK.
Cogn Affect Behav Neurosci. 2021 Dec;21(6):1196-1206. doi: 10.3758/s13415-021-00921-w. Epub 2021 Oct 15.
Human decisions can be reflexive or planned, being governed respectively by model-free and model-based learning systems. These two systems might differ in their responsiveness to our needs. Hunger drives us to specifically seek food rewards, but here we ask whether it might have more general effects on these two decision systems. On one hand, the model-based system is often considered flexible and context-sensitive, and might therefore be modulated by metabolic needs. On the other hand, the model-free system's primitive reinforcement mechanisms may have closer ties to biological drives. Here, we tested participants on a well-established two-stage sequential decision-making task that dissociates the contribution of model-based and model-free control. Hunger enhanced overall performance by increasing model-free control, without affecting model-based control. These results demonstrate a generalized effect of hunger on decision-making that enhances reliance on primitive reinforcement learning, which in some situations translates into adaptive benefits.
人类的决策可以是反射性的，也可以是有计划的，分别由无模型和基于模型的学习系统来控制。这两个系统在响应我们的需求方面可能有所不同。饥饿驱使我们专门寻找食物奖励，但在这里我们要问的是，它是否可能对这两个决策系统产生更普遍的影响。一方面，基于模型的系统通常被认为是灵活和敏感的，因此可能会受到代谢需求的调节。另一方面，无模型系统的原始强化机制可能与生物驱动更紧密相关。在这里，我们在一个成熟的两阶段序列决策任务中测试了参与者，该任务可以分离基于模型和无模型控制的贡献。饥饿通过增加无模型控制来提高整体表现，而不影响基于模型的控制。这些结果表明，饥饿对决策有普遍的影响，增强了对原始强化学习的依赖，在某些情况下，这转化为适应性的好处。
