‘Your Brain on Art’: Emergent cortical dynamics during aesthetic experiences

• Main Authors: Kimberly eKontson, Murad eMegjhani, Justin A Brantley, Jesus Gabriel Cruz-Garza, Sho eNakagome, Dario eRobleto, Michelle eWhite, Eugene eCivillico, Jose Luis Contreras-Vidal
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2015-11-01
• Series: Frontiers in Human Neuroscience
• Subjects: aesthetics; EEG; machine learning; freely moving; functional connectivity (FC)
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00626/full

The brain response to conceptual art was studied with mobile electroencephalography (EEG) to examine the neural basis of aesthetic experiences. In contrast to most studies of perceptual phenomena, participants were moving and thinking freely as they viewed the exhibit The Boundary of Life is Quietly Crossed by Dario Robleto at the Menil Collection-Houston. The brain activity of over 400 subjects was recorded using dry-electrode and one reference gel-based EEG systems over a period of 3 months. Here, we report initial findings based on the reference system. EEG segments corresponding to each art piece were grouped into one of three classes (complex, moderate, and baseline) based on analysis of a digital image of each piece. Time, frequency, and wavelet features extracted from EEG were used to classify patterns associated with viewing art, and ranked based on their relevance for classification. The maximum classification accuracy was 55% (chance = 33%) with delta and gamma features the most relevant for classification. Functional analysis revealed a significant increase in connection strength in localized brain networks while subjects viewed the most aesthetically pleasing art compared to viewing a blank wall. The direction of signal flow showed early recruitment of broad posterior areas followed by focal anterior activation. Significant differences in the strength of connections were also observed across age and gender. This work provides evidence that EEG, deployed on freely behaving subjects, can detect selective signal flow in neural networks, identify significant differences between subject groups, and report with greater-than-chance accuracy the complexity of a subject’s visual percept of aesthetically pleasing art. Our approach, which allows acquisition of neural activity ‘in action and context’, could lead to understanding of how the brain integrates sensory input and its ongoing internal state to produce the phenomenon which we term aesthetic experience.