Exploring Aesthetic Perception in Impaired Aging: A Multimodal Brain—Computer Interface Study

Bibliographic Details
Title: Exploring Aesthetic Perception in Impaired Aging: A Multimodal Brain—Computer Interface Study
Authors: Livio Clemente, Marianna La Rocca, Giulia Paparella, Marianna Delussi, Giusy Tancredi, Katia Ricci, Giuseppe Procida, Alessandro Introna, Antonio Brunetti, Paolo Taurisano, Vitoantonio Bevilacqua, Marina de Tommaso
Source: Sensors, Vol 24, Iss 7, p 2329 (2024)
Publisher Information: MDPI AG, 2024.
Publication Year: 2024
Collection: LCC:Chemical technology
Subject Terms: BCI, aesthetic, fNIRS, EEG, impaired aging, Chemical technology, TP1-1185
More Details: In the field of neuroscience, brain–computer interfaces (BCIs) are used to connect the human brain with external devices, providing insights into the neural mechanisms underlying cognitive processes, including aesthetic perception. Non-invasive BCIs, such as EEG and fNIRS, are critical for studying central nervous system activity and understanding how individuals with cognitive deficits process and respond to aesthetic stimuli. This study assessed twenty participants who were divided into control and impaired aging (AI) groups based on MMSE scores. EEG and fNIRS were used to measure their neurophysiological responses to aesthetic stimuli that varied in pleasantness and dynamism. Significant differences were identified between the groups in P300 amplitude and late positive potential (LPP), with controls showing greater reactivity. AI subjects showed an increase in oxyhemoglobin in response to pleasurable stimuli, suggesting hemodynamic compensation. This study highlights the effectiveness of multimodal BCIs in identifying the neural basis of aesthetic appreciation and impaired aging. Despite its limitations, such as sample size and the subjective nature of aesthetic appreciation, this research lays the groundwork for cognitive rehabilitation tailored to aesthetic perception, improving the comprehension of cognitive disorders through integrated BCI methodologies.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1424-8220
Relation: https://www.mdpi.com/1424-8220/24/7/2329; https://doaj.org/toc/1424-8220
DOI: 10.3390/s24072329
Access URL: https://doaj.org/article/f542c4b853a041d39e6122c751b60617
Accession Number: edsdoj.f542c4b853a041d39e6122c751b60617
Database: Directory of Open Access Journals
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More Details
ISSN:14248220
DOI:10.3390/s24072329
Published in:Sensors
Language:English