Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China.
Université Claude Bernard Lyon 1, Lyon, France; CNRS, Laboratory of Neuroeconomics, Institut des Sciences Cognitives Marc Jeannerod, Lyon, France.
Neurosci Biobehav Rev. 2022 Jan;132:50-60. doi: 10.1016/j.neubiorev.2021.11.023. Epub 2021 Nov 23.
The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making.
自认知神经科学早期以来，人们一直在研究涉及道德决策的神经回路，主要使用道德困境。然而，描述人类大脑如何在各种道德情境中做出道德决策和学习的神经计算机制才刚刚开始建立。在这里，我们回顾了使用基于模型的 fMRI 的新兴领域的最新结果，该方法从机械论水平描述了道德选择。这些发现统一了道德决策领域，扩展了以前为基于价值的决策制定开发的概念框架，并描述了道德过程如何在大脑中进行计算。道德困境可以建模为基于价值的决策，权衡自身利益与对他人的道德成本/伤害，并且可以在不同方面的道德学习中区分不同类型的预测误差。这些关键的计算信号有助于在算法水平上描述道德选择和道德学习，并揭示这些认知操作在大脑中的实现方式。这些研究为解释道德决策的神经计算机制提供了基础。
