情绪作为系统活动的离散模式。
Emotions as discrete patterns of systemic activity.
作者信息
Nummenmaa Lauri, Saarimäki Heini
机构信息
Turku PET Centre and Department of Psychology, University of Turku, Finland.
Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Finland.
出版信息
Neurosci Lett. 2019 Feb 6;693:3-8. doi: 10.1016/j.neulet.2017.07.012. Epub 2017 Jul 10.
Emotions organize human and animal behaviour by automatically adjusting their actions at multiple physiological and behavioural scales. Recently, pattern recognition techniques have emerged as an important tool for quantifying the neural, physiological, and phenomenological organization of emotions in humans. Here we review recent advances in our understanding of the human emotion system from the viewpoint of pattern recognition studies, focussing on neuroimaging experiments. These studies suggest, in general, clear and consistent categorical structure of emotions across multiple levels of analysis spanning expressive behaviour, subjective experiences, physiological activity, and neural activation patterns. In particular, the neurophysiological data support the view of multiple discrete emotion systems that are organized in a distributed fashion across the brain, with no clear one-to-one mapping between emotions and brain regions. However, these techniques are inherently limited by the choice of a priori emotion categories used in the studies, and cannot provide direct causal evidence for brain activity-emotion relationships.
情绪通过在多个生理和行为尺度上自动调整行为来组织人类和动物的行为。最近,模式识别技术已成为量化人类情绪的神经、生理和现象学组织的重要工具。在这里,我们从模式识别研究的角度回顾了我们对人类情绪系统理解的最新进展,重点是神经影像学实验。这些研究总体上表明,在跨越表达行为、主观体验、生理活动和神经激活模式的多个分析层面上,情绪具有清晰且一致的分类结构。特别是,神经生理学数据支持了多个离散情绪系统的观点,这些系统以分布式方式在大脑中组织,情绪与脑区之间没有明确的一一对应映射。然而,这些技术本质上受到研究中使用的先验情绪类别的选择限制,并且无法为大脑活动与情绪的关系提供直接的因果证据。