用脑电图预测弹马库评论中表达的道德高尚。

IF 10.5 Q1 ENGINEERING, BIOMEDICAL Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI:10.34133/cbsystems.0028
Chenhao Bao, Xin Hu, Dan Zhang, Zhao Lv, Jingjing Chen
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引用次数: 0

摘要

道德提升是个体观察他人道德行为时产生的情感,在现实生活中对道德行为起着重要的决定作用。虽然最近的研究已经证明了用大脑信号解码基本情绪的潜力,但对道德提升(一种与社会认知相关的情绪)的情感计算的探索有限。为了解决这一差距,我们记录了23名参与者在观看有望引发道德提升的视频时的脑电图(EEG)信号。以1秒的时间分辨率,提取了3万多条“丹玛库”评论,并进行了连续标注。然后,利用功率谱特征、最小绝对收缩和选择算子正则化回归分析,我们获得了良好的道德高尚预测性能(预测r = 0.44±0.11)。我们的研究结果表明,利用脑电图信号解码道德提升是可能的。此外,小样本神经数据可以预测大群体中弹马库评论所传达的持续道德提升体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Predicting Moral Elevation Conveyed in Danmaku Comments Using EEGs.

Moral elevation, the emotion that arises when individuals observe others' moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population.

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CiteScore
7.70
自引率
0.00%
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0
审稿时长
21 weeks
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