Division for Clinical Psychiatry Research, Psychiatric Hospital, University of Zurich; at the Neuroscience Centre Zurich, University of Zurich, 8032 Zurich, Switzerland; and at the Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK.
Gatsby Computational Neuroscience Unit, University College London, London W1T 4JG, UK.
Nat Rev Neurosci. 2017 May;18(5):311-319. doi: 10.1038/nrn.2017.35. Epub 2017 Mar 31.
The nature and neural implementation of emotions is the subject of vigorous debate. Here, we use Bayesian decision theory to address key complexities in this field and conceptualize emotions in terms of their relationship to survival-relevant behavioural choices. Decision theory indicates which behaviours are optimal in a given situation; however, the calculations required are radically intractable. We therefore conjecture that the brain uses a range of pre-programmed algorithms that provide approximate solutions. These solutions seem to produce specific behavioural manifestations of emotions and can also be associated with core affective dimensions. We identify principles according to which these algorithms are implemented in the brain and illustrate our approach by considering decision making in the face of proximal threat.
情绪的本质和神经实现是激烈争论的主题。在这里，我们使用贝叶斯决策理论来解决该领域的关键复杂性，并根据与生存相关的行为选择来概念化情绪。决策理论指出在给定情况下哪种行为是最优的；然而，所需的计算是非常棘手的。因此，我们推测大脑使用一系列预先编程的算法来提供近似解。这些解决方案似乎产生了情绪的特定行为表现，也可以与核心情感维度相关联。我们确定了这些算法在大脑中实现的原则，并通过考虑面对近在咫尺的威胁时的决策来举例说明我们的方法。
