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

Abstract

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.

Keywords: BCI; EEG; aesthetic; fNIRS; impaired aging.

Figure 1

Flow chart of the study design illustrating the stages of recruitment, recording, data processing, and group comparison.

Figure 2

Combined EEG/fNIRS system with 10/20 64 electrodes and 20 NIR channels resulting from 16 optodes (8 sensors in red and 8 detectors in green).

Figure 3

Experimental paradigm, showing (a) common stimuli; (b) target dynamic stimuli on the left side and target static stimuli on the right; (c) Likert scale for evaluation of aesthetic appreciation.

Figure 4

The analysis of oxyhemoglobin (HbO) is presented in two parts: the left side displays the raw beta value, while the right side shows the same values filtered to display only areas where brain activity is statistically significant (p < 0.05).

Figure 5

Statistical analysis and electrophysiological responses were used to evaluate aesthetic stimuli. (a) P300 ANOVA p-value in group and condition, showing the topographical map of raw activity and the wavelet; (b) LPP ANOVA p-value in condition*aesthetic (left), group*condition*aesthetic (central), and aesthetic (right).

Figure 6

Non-parametric cluster-based permutation analysis showing topographical raw difference (top row) and raw difference filtered by cluster (down row) between groups in pleasant dynamic, pleasant static, and unpleasant dynamic stimuli.