Individuals can be aesthetically engaged by objects from widely different visual aesthetic domains, such as paintings, mountain vistas, or buildings. The goal of this project is to understand whether aesthetic appreciation of different visual domains relies on the same underlying processes. Behaviorally, we find that the degree of "shared taste" across people differs systematically by domain: preferences for faces and landscapes contain a high proportion of shared taste, while preferences for architecture and artworks, both artifacts of human culture, reflect strong individual differences.
Using functional magnetic resonance imaging (fMRI) combined with machine-learning techniques, we are mapping out the topography of "domain-specific" versus "domain-general" neural processes. Patterns of activity from the default-mode network (DMN), a brain network thought to support aspects of internally-directed thought, contain a strong signature of domain-general aesthetic processing. We also find evidence for domain-specific information in several regions of the prefrontal cortex that are more prevalent for artwork and architecture, suggesting that not only do cultural artifacts rely more heavily on individual aesthetic sensibilities than do evaluations of landscape, they also engage additional processes beyond a "core" domain-general system.
"Behaviorally, we find that the degree of "shared taste" across people differs systematically by domain: preferences for faces and landscapes contain a high proportion of shared taste, while preferences for architecture and artworks, both artifacts of human culture, reflect strong individual differences (Vessel et al., 2018).”
Vessel,E.A., Isik, A.I., Belfi, A.M., Stahl, J. L., and Starr, G. G. (2019) The default-mode network represents aesthetic appeal that generalizes across visual domains. PNAS https://doi.org/10.1073/pnas.1902650116
Vessel, E. A., Maurer, N., Denker, A. H., & Starr, G. G. (2018). Stronger shared taste for natural aesthetic domains than for artifacts of human culture. Cognition, 179, 121–131. http://doi.org/10.1016/j.cognition.2018.06.009