Decoding Spontaneous Emotional States in the Human Brain
Decoding Spontaneous Emotional States in the Human Brain
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DOI：
10.1371/journal.pbio.2000106
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发表时间：
2016-09-01
期刊：
影响因子：
9.8
通讯作者：
LaBar, Kevin S.
中科院分区：
文献类型：
--
作者：
Kragel, Philip A.;Knodt, Annchen R.;LaBar, Kevin S.
人类大脑活动的模式分类提供了对不同精神状态的神经基础的独特洞察。这些多变量工具最近被用于情感神经科学领域，以对情绪诱导过程中诱发的大脑激活的分布模式进行分类。在这里，我们评估了在缺乏外感情绪刺激的情况下，为区分不同情绪类别而开发的神经模型是否显示出预测有效性。在两个实验中，我们证明了人类休息状态大脑活动的自发波动可以被解码为描述独特情绪状态的体验类别，这些情绪状态表现出时空一致性，与情绪和个性特征的个体差异相关，并预测在线的自我报告的感觉。这些发现验证了客观的、基于大脑的情绪模型，并展示了情绪状态是如何从可分离的神经系统的活动中动态出现的。
Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.