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Ecological decoding of visual aesthetic preference with oscillatory electroencephalogram features-A mini-review. 利用振荡脑电图特征对视觉审美偏好进行生态解码--微型综述。

Frontiers in neuroergonomics Pub Date : 2024-02-21 eCollection Date: 2024-01-01 DOI: 10.3389/fnrgo.2024.1341790

Marc Welter, Fabien Lotte

{"title":"Ecological decoding of visual aesthetic preference with oscillatory electroencephalogram features-A mini-review.","authors":"Marc Welter, Fabien Lotte","doi":"10.3389/fnrgo.2024.1341790","DOIUrl":"10.3389/fnrgo.2024.1341790","url":null,"abstract":"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.","PeriodicalId":517413,"journal":{"name":"Frontiers in neuroergonomics","volume":"5 ","pages":"1341790"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914990/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140051400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Subject-specific information enhances spatial accuracy of high-density diffuse optical tomography. 受试者特定信息可提高高密度弥散光学断层扫描的空间精确度。

Frontiers in neuroergonomics Pub Date : 2024-02-19 eCollection Date: 2024-01-01 DOI: 10.3389/fnrgo.2024.1283290

Sruthi Srinivasan, Deepshikha Acharya, Emilia Butters, Liam Collins-Jones, Flavia Mancini, Gemma Bale

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引用次数: 0

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