Welter Marc, Lotte Fabien
Inria Center at the University of Bordeaux/LaBRI, Talence, France.
Front Neuroergon. 2024 Feb 21;5:1341790. doi: 10.3389/fnrgo.2024.1341790. eCollection 2024.
In today's digital information age, human exposure to visual artifacts has reached an unprecedented quasi-omnipresence. Some of these cultural artifacts are elevated to the status of artworks which indicates a special appreciation of these objects. For many persons, the perception of such artworks coincides with aesthetic experiences (AE) that can positively affect health and wellbeing. AEs are composed of complex cognitive and affective mental and physiological states. More profound scientific understanding of the neural dynamics behind AEs would allow the development of passive Brain-Computer-Interfaces (BCI) that offer personalized art presentation to improve AE without the necessity of explicit user feedback. However, previous empirical research in visual neuroaesthetics predominantly investigated functional Magnetic Resonance Imaging and Event-Related-Potentials correlates of AE in unnaturalistic laboratory conditions which might not be the best features for practical neuroaesthetic BCIs. Furthermore, AE has, until recently, largely been framed as the experience of beauty or pleasantness. Yet, these concepts do not encompass all types of AE. Thus, the scope of these concepts is too narrow to allow personalized and optimal art experience across individuals and cultures. This narrative mini-review summarizes the state-of-the-art in oscillatory Electroencephalography (EEG) based visual neuroaesthetics and paints a road map toward the development of ecologically valid neuroaesthetic passive BCI systems that could optimize AEs, as well as their beneficial consequences. We detail reported oscillatory EEG correlates of AEs, as well as machine learning approaches to classify AE. We also highlight current limitations in neuroaesthetics and suggest future directions to improve EEG decoding of AE.
在当今数字信息时代，人类接触视觉人工制品的情况已达到前所未有的近乎无处不在的程度。其中一些文化人工制品被提升到艺术品的地位，这表明对这些物品有特殊的欣赏。对许多人来说，对这类艺术品的感知与审美体验（AE）相契合，而审美体验能对健康和幸福产生积极影响。审美体验由复杂的认知、情感心理和生理状态组成。对审美体验背后神经动力学更深入的科学理解，将有助于开发被动式脑机接口（BCI），该接口能提供个性化的艺术展示，从而在无需明确用户反馈的情况下改善审美体验。然而，以往视觉神经美学的实证研究主要在非自然主义的实验室条件下，研究审美体验与功能磁共振成像及事件相关电位的相关性，而这些可能并非实用神经美学脑机接口的最佳特征。此外，直到最近，审美体验在很大程度上仍主要被界定为对美的体验或愉悦感。然而，这些概念并未涵盖所有类型的审美体验。因此，这些概念的范围过于狭窄，无法实现跨个体和跨文化的个性化和最佳艺术体验。这篇叙述性小型综述总结了基于振荡脑电图（EEG）的视觉神经美学的最新进展，并描绘了一条朝着开发生态有效、能优化审美体验及其有益影响的神经美学被动脑机接口系统发展的路线图。我们详细介绍了已报道的审美体验与振荡脑电图的相关性，以及用于分类审美体验的机器学习方法。我们还强调了神经美学当前的局限性，并提出了改进脑电图对审美体验解码的未来方向。
