We offer an account of mental health and well-being using the predictive processing framework (PPF). According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence is modelled as error dynamics—the change in prediction errors over time. Our aim in this paper is to show how error dynamics can account for both momentary happiness and longer term well-being. What will emerge is a new neurocomputational framework for making sense of human flourishing.

我们使用预测处理框架 (PPF) 提供心理健康和幸福感。根据这个框架，心理健康和精神病理学之间的区别可以在于预测模型作为行动调节器的优劣。避免与精神病理学相关的僵化的思维、感觉和行为模式的关键是基于情感状态的效价对行为的调节。在 PPF 中，效价被建模为误差动态——预测误差随时间的变化。我们在本文中的目的是展示错误动态如何解释暂时的幸福和长期的幸福。将会出现的是一个新的神经计算框架，用于理解人类的繁荣。