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Article

Regional EEG Responses from Exposures to Virtual Urban Green Spaces

1
Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632, Singapore
2
Department of Architecture, College of Design and Engineering, National University of Singapore, Singapore 117575, Singapore
3
Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, Singapore 138632, Singapore
4
College of Computing and Data Science, Nanyang Technological University, 50 Nanyang Ave, 32 Block N4 02a, Singapore 639798, Singapore
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(12), 5882; https://doi.org/10.3390/app16125882
Submission received: 29 April 2026 / Revised: 22 May 2026 / Accepted: 9 June 2026 / Published: 10 June 2026

Abstract

Exposure to urban green spaces has been associated with mental wellbeing, but the neural responses to specific visual properties of urban green spaces remain unclear. This study investigated regional electroencephalogram (EEG) responses to latent visual dimensions of virtual urban green space exposures. This study used a quantitative scene-based approach that extracted 41 visual metrics to capture the heterogeneous structural properties of 24 panoramic urban green images. EEG recordings were analyzed from 150 participants, each of whom viewed eight randomly selected images repeated three times. Dimension-wise factor analysis with varimax rotation was used to derive latent factor scores for four conceptual dimensions: naturalness, complexity, coherence, and visual scale. These factors were then used as predictors in crossed mixed-effects models of regional EEG relative power changes. The hypothesis-driven primary analysis showed a significant and positive association between parietal alpha–theta activity and a naturalness factor reflecting green–grey scene compositions. Exploratory frontal associations with a terrain-related visual scale factor reached nominal significance but did not survive false discovery rate correction. Overall, the findings support a quantitative, feature-based approach for linking urban green space structure with regional neurophysiological responses. This study provides a methodological step toward more evidence-informed assessment of smart and sustainable urban environments.
Keywords: urban landscape; electroencephalogram (EEG); environmental neuroscience; factor analysis; mixed-effects modelling; representational similarity analysis urban landscape; electroencephalogram (EEG); environmental neuroscience; factor analysis; mixed-effects modelling; representational similarity analysis

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MDPI and ACS Style

Xue, Y.; Chin, Z.Y.; Waykool, R.; Zhang, X.; Qi, J.; Gobeawan, L.; Lin, E.S.; Ang, K.K. Regional EEG Responses from Exposures to Virtual Urban Green Spaces. Appl. Sci. 2026, 16, 5882. https://doi.org/10.3390/app16125882

AMA Style

Xue Y, Chin ZY, Waykool R, Zhang X, Qi J, Gobeawan L, Lin ES, Ang KK. Regional EEG Responses from Exposures to Virtual Urban Green Spaces. Applied Sciences. 2026; 16(12):5882. https://doi.org/10.3390/app16125882

Chicago/Turabian Style

Xue, Yuqing, Zheng Yang Chin, Radha Waykool, Xudong Zhang, Jinda Qi, Like Gobeawan, Ervine Shengwei Lin, and Kai Keng Ang. 2026. "Regional EEG Responses from Exposures to Virtual Urban Green Spaces" Applied Sciences 16, no. 12: 5882. https://doi.org/10.3390/app16125882

APA Style

Xue, Y., Chin, Z. Y., Waykool, R., Zhang, X., Qi, J., Gobeawan, L., Lin, E. S., & Ang, K. K. (2026). Regional EEG Responses from Exposures to Virtual Urban Green Spaces. Applied Sciences, 16(12), 5882. https://doi.org/10.3390/app16125882

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