Bottemanne Hugo, Barberousse Anouk, Fossati Philippe
Paris Brain Institute - Institut du Cerveau (ICM), Sorbonne University/CNRS/Inserm, Paris, France; Department of philosophy, Sciences Normes Démocratie research unit, Sorbonne university/CNRS, Paris, France; Department of psychiatry, DMU Neuroscience, Pitié-Salpêtrière hospital, Sorbonne university/Assistance publique-Hôpitaux de Paris (AP-HP), Paris, France.
Department of philosophy, Sciences Normes Démocratie research unit, Sorbonne university/CNRS, Paris, France.
Encephale. 2022 Dec;48(6):682-699. doi: 10.1016/j.encep.2022.02.002. Epub 2022 Aug 18.
What is mood? Despite its crucial place in psychiatric nosography and cognitive science, it is still difficult to delimit its conceptual ground. The distinction between emotion and mood is ambiguous: mood is often presented as an affective state that is more prolonged and less intense than emotion, or as an affective polarity distinguishing high and low mood swinging around a baseline. However, these definitions do not match the clinical reality of mood disorders such as unipolar depression and bipolar disorder, and do not allow us to understand the effect of mood on behaviour, perception and cognition. In this paper, we propose a multidimensional and computational theory of mood inspired by contemporary hypotheses in theoretical neuroscience and philosophy of emotion. After suggesting an operational distinction between emotion and mood, we show how a succession of emotions can cumulatively generate congruent mood over time, making mood an emerging state from emotion. We then present how mood determines mental and behavioral states when interacting with the environment, constituting a dispositional state of emotion, perception, belief, and action. Using this theoretical framework, we propose a computational representation of the emerging and dispositional dimensions of mood by formalizing mood as a layer of third-order Bayesian beliefs encoding the precision of emotion, and regulated by prediction errors associated with interoceptive predictions. Finally, we show how this theoretical framework sheds light on the processes involved in mood disorders, the emergence of mood congruent beliefs, or the mechanisms of antidepressant treatments in clinical psychiatry.
什么是情绪？尽管情绪在精神疾病分类学和认知科学中占据关键地位，但界定其概念基础仍颇具难度。情绪与情感之间的区别并不明晰：情感常被视为一种比情绪更为持久且强度更低的情感状态，或者是一种区分高涨与低落情绪的情感极性，围绕基线波动。然而，这些定义与诸如单相抑郁症和双相情感障碍等情绪障碍的临床现实并不相符，也无法让我们理解情绪对行为、感知和认知的影响。在本文中，我们提出了一种多维且基于计算的情绪理论，该理论受到理论神经科学和情感哲学中当代假说的启发。在提出情绪与情感的操作性区分之后，我们展示了一系列情绪如何随着时间的推移累积产生一致的情感，使情感成为一种从情绪中浮现的状态。然后，我们阐述了情感在与环境相互作用时如何决定心理和行为状态，构成一种情感、感知、信念和行动的倾向状态。利用这一理论框架，我们通过将情感形式化为编码情绪精度的三阶贝叶斯信念层，并由与内感受预测相关的预测误差进行调节，提出了情感浮现维度和倾向维度的计算表示。最后，我们展示了这一理论框架如何阐明情绪障碍所涉及的过程、情绪一致信念的出现，或临床精神病学中抗抑郁治疗的机制。
