fNIRS Evidence for Recognizably Different Positive Emotions
fNIRS Evidence for Recognizably Different Positive Emotions
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DOI：
10.3389/fnhum.2019.00120
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发表时间：
2019-04-09
影响因子：
2.9
通讯作者：
Zhang, Dan
中科院分区：
文献类型：
--
作者：
Hu, Xin;Zhuang, Chu;Zhang, Dan
积极情绪的行为分化最近被研究的离散的适应功能或评价配置文件。一些初步的神经生理学证据已被发现与脑电图或自主神经系统的测量，如心率，皮肤电导等，但大脑的血流动力学反应不同的积极情绪仍然在很大程度上是未知的。在本研究中，功能近红外光谱（fNIRS）技术。有了这个工具，我们首次使用fNIRS信号报告了可识别的离散积极情绪。13名受试者观看30个情绪视频片段，以引发10种典型的积极情绪（喜悦，感激，平静，兴趣，希望，自豪，娱乐，灵感，敬畏和爱），并用24通道fNIRS系统同时记录他们的额叶神经活动。参与者对这10种积极情绪的主观评分的多维标度分析显示了三个不同的集群，可以解释为娱乐，喜悦，兴趣的“玩耍”，敬畏，感激，希望，灵感，自豪的“鼓励”，以及爱，宁静的“和谐”。对这三种积极情绪的血流动力学反应显示出不同的模式，基于HbO的个体水平二元分类的平均准确率为73.79 ± 11.49%。（77.56 +/- 7.39%为鼓励与和谐，73.29 +/- 11.87%为玩耍与和谐，70.51 +/- 13.96%为鼓励与和谐）。得益于fNIRS的高便携性，低运行成本和对运动和电气伪影的相对鲁棒性，我们的研究结果提供了支持，实现一个更细粒度的情感识别系统细分的积极情绪类别。
The behavioral differentiation of positive emotions has recently been studied in terms of their discrete adaptive functions or appraising profiles. Some preliminary neurophysiological evidences have been found with electroencephalography or autonomic nervous system measurements such as heart rate, skin conductance, etc. However, the brain's hemodynamic responses to different positive emotions remain largely unknown. In the present study, the functional near-infrared spectroscopy (fNIRS) technique was employed. With this tool, we for the first time reported recognizable discrete positive emotions using fNIRS signals. Thirteen participants watched 30 emotional video clips to elicit 10 typical kinds of positive emotions (joy, gratitude, serenity, interest, hope, pride, amusement, inspiration, awe, and love), and their frontal neural activities were simultaneously recorded with a 24-channel fNIRS system. The multidimensional scaling analysis of participants' subjective ratings on these 10 positive emotions revealed three distinct clusters, which could be interpreted as "playfulness" for amusement, joy, interest, "encouragement" for awe, gratitude, hope, inspiration, pride, and "harmony" for love, serenity. Hemodynamic responses to these three positive emotion clusters showed distinct patterns, and HbO-based individual-level binary classifications between them achieved an averaged accuracy of 73.79 +/- 11.49% (77.56 +/- 7.39% for encouragement vs. harmony, 73.29 +/- 11.87% for playfulness vs. harmony, 70.51 +/- 13.96% for encouragement vs. harmony). Benefited from fNIRS's high portability, low running cost and the relative robustness against motion and electrical artifacts, our findings provided support for implementing a more fine-grained emotion recognition system with subdivided positive emotion categories.