Advancing a Situated Neuroscience of Emotion

我们怎么能知道别人的真实感受呢？如果情绪强烈，这可能很容易分辨，但有些人善于隐藏他们的情绪，或者他们可能不知道或无法报告他们的感受。幸运的是，测量大脑活动和情绪理论的技术进步可以帮助我们更客观地了解人们的情绪状态。一些情绪理论认为，不同的情绪状态，如恐惧、愤怒或快乐，都是由特定的、专用的神经回路产生的，这种神经回路在任何时候都以同样的方式产生情绪。例如，快乐的神经回路是一样的，无论是因为你得到了赞美还是你得知了升职。相比之下，拟议的研究是建立在一种创新的情绪“情境神经科学”模型上的。这个模型假设情绪对应于可变的神经模式。这些变化的模式被假设是由所经历的情绪类别决定的，比如恐惧，部分是由经历情绪的环境决定的。语境包括来自文化和情境本身的成分。北卡罗来纳大学教堂山分校的克里斯汀·林德奎斯特博士和他的同事们提出了三个实验来检验这个模型。她的研究将使用测量大脑活动的位置（功能性磁共振成像；fMRI）和大脑活动的时间（脑电图；EEG）。以这种方式将情感理论和技术结合起来，可以帮助我们改善对情感的沟通和理解，帮助我们预测情感何时会影响我们的决策和表现，并可能对我们与他人互动的方式有好处。这项拟议中的研究将情绪理论与测量大脑活动的技术进步结合起来，从大脑状态中“解读”情绪感受。其目的是发展一种情境情感神经科学，这将告知我们对情感基础及其意识体验的理解。提出了三个实验来检验情境和文化背景在情绪和大脑活动中的作用。第一个实验使用功能性磁共振（fMRI）检查恐惧和愤怒，以及它们与情境和文化背景对大脑活动的影响。这种情况被操纵为社会或非社会，文化源于招收美国和中国的当地人，他们知道各自文化中基于情感的规范和价值观。第二个实验将这项研究扩展到使用脑电图（EEG）的情绪大脑活动的时间动态。第三项研究利用从先前实验中获得的数据进行机器学习，以确定在不同背景下，哪些变量最能预测情绪期间的大脑活动。理解情绪的情境本质对于理解神经回路如何映射到主观心理状态至关重要。这些发现可能会提高我们对自己和他人情感体验的理解，并增强我们的沟通、幸福感和外交关系。它还可能为情绪相关疾病和脑机接口领域的应用进展提供信息。

How can we know how other people are really feeling? If emotions are intensely experienced it may be easy to tell, but some people are good at hiding their emotions, or they may be unaware of or unable to report what they are feeling. Fortunately, technological advances in measuring brain activity and emotion theory can help us to have a more objective understanding of people's emotional states. Some theories of emotion suggest that different emotional states, such as fear, anger, or happiness, arise because of specific, dedicated neural circuitry that responds in the same way any time that emotion is experienced. For example, the circuitry for happiness is the same whether it arises because you get a compliment or you learned of a promotion. In contrast, the proposed research is built on an innovative 'situated neuroscience' model of emotions. This model hypothesizes that emotions correspond to variable neural patterns. These variable patterns are hypothesized to be determined by the emotion category experienced, such as fear, and partly by the context in which the emotion is experienced. The context includes components from culture and the situation itself. Dr. Kristen Lindquist, at the University of North Carolina at Chapel Hill, and colleagues proposed three experiments to examine this model. Her research will use measures of the location of brain events (functional magnetic resonance imaging; fMRI) and the timing of brain events (electroencephalography; EEG). The integration of emotion theory and technology in this way could help to improve communication about and understanding of emotions, help us to predict when emotions influence our decisions and performance, and may have benefits for the way we interact with others. The proposed research integrates emotion theory with technological advances in measuring brain activity to "read" emotional feelings from brain states. The aim is to develop a situated neuroscience of emotion that will inform our understanding of the basis of emotions and their conscious experience. Three experiments are proposed that examine the role of situational and cultural contexts in emotion and brain activity. The first experiment examines fear and anger and their interaction with situational and cultural contexts on brain activity, using functional magnetic resonance (fMRI). The situation is manipulated to be either social or non-social, and culture stems from enrolling natives of the US and China who know the emotion-based norms and values of their respective culture. The second experiment extends this investigation to the temporal dynamics of emotional brain activity using electroencephalography (EEG). The third study uses machine learning on data obtained from the prior experiments to determine which variables best predict brain activity during emotion, in the different contexts. Understanding the situated nature of emotion is crucial to an understanding of how neural circuits map on to subjective mental states. These findings may improve our understanding of emotional experience in ourselves and others, and enhance our communication, well-being, and diplomatic relations. It may also inform applied advancements in the areas of mood-related illnesses and brain-computer interface.