Behavioral and neural foundations of aesthetic experience

This research area takes a neurobiological view of "the aesthetic granularity problem.” What are the "atoms of aesthetic experience," as viewed from human neuroscience? Experiencing a single musical note or one word is arguably too small a unit of analysis; experiencing an entire symphony or whole novel is arguably too big. What constitutes an "aesthetic primitive," from a brain’s-eye-view? A second focus concerns the variability of experience - despite compelling neurobiological universals or shared properties. Here we seek to identify the principles (universal? innate?) and parameters (culture-specific and contingent? acquired?) of aesthetic experience. 


Does it sound right?

Listeners can easily say if a singer sounds in tune or out of tune (Larrouy-Maestri et al., 2013, 2015) and if a band plays on the beat or not. In fact, we are used to “categorize” what we hear and identify performances sounding wrong. However, as is true for several types of judgments (e.g., beauty or obscenity), the definition of ‘correctness’ in music lacks precision, and the foundation of such categorization remains unclear (Larrouy-Maestri, under review). This project examines what ‘correctness’ means in different musical contexts and the cognitive processes behind such categorization. 


Aesthetics Across Visual Domains

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.


Are you speaking to me?

Although we intuitively know if someone is speaking or singing, the neuronal mechanisms that drive this experience are not well understood. Whether we perceive auditory sequences as speech or song is associated with certain acoustic features (Merrill, & Larrouy-Maestri, 2017).


Exploring Network Interactions during Aesthetic Experiences

How does the brain support aesthetic experiences with visual stimuli such as artwork, landscapes, architecture or dance? Recent work in our group suggests that finding a painting to be aesthetically moving involves a change away from the typical behavior of large-scale brain networks. In particular, the default-mode network (DMN), a brain network that is thought to support aspects of internally-directed thought, is typically suppressed when visual networks are active, and vice versa. However, during moving aesthetic experiences, these two networks appear to be simultaneously active (Vessel, Starr, Rubin, 2012; 2013). The goal of this project is to better understand these network interactions: what neural processes support such moving visual aesthetic experiences, and what role do changes in the activation and connectivity of large scale networks plays in moving aesthetic experiences.


Singing Voice Preferences

As suggested by the many singing contests and music programs in the media, the singing voice attracts ample attention. Recent studies showed that lay and expert listeners share similar definitions of what is “correct” when listening to untrained (Larrouy-Maestri et al., 2015) and trained singers (Larrouy-Maestri et al., 2017). The definition of pitch accuracy (i.e., correctness) relies on specific acoustic features that can be measured. However, we usually don’t attend opera or pop concerts to evaluate the correctness of a performance but to enjoy it. This project aims to investigate what “preference” means when listening to sung performances, and to explore the roots of such aesthetic experience.


Development of Preferences

Adult liking judgments for visual scenes are strongly influenced by the semantic content of images, more so than by lower-level visual features (e.g. the presence of specific colors or line types). This results in a strong degree of shared taste across different real-world scenes but highly idiosyncratic liking judgments for abstract images such as fractals and kaleidoscopic images that lack semantic content (Vessel & Rubin, 2010). This project seeks to understand how this adult-like pattern of shared taste emerges over the course of development.