An innovative new research study analyzed brain activity data collected from more than 400 people as they viewed an art exhibit.
University of Houston researchers studied how the brain responds as people observed artwork associated with the Menil Collection, one of the largest and most wide-ranging private art collections in the United States.
The study offers evidence that usable brain data can be collected outside of a controlled laboratory setting.
“You can do testing in the lab, but it’s very artificial,” said Jose Luis Contreras-Vidal, Ph.D., a professor of electrical and computer engineering at UH. “We were looking at how to measure brain activity in action and in context.”
The researchers reported their findings in the journal Frontiers in Human Neuroscience.
Investigators found significant increases in functional, or task-related, connectivity in localized brain networks when the subjects viewed art they considered aesthetically pleasing.
Researchers also found differences both between men and women and between the youngest and oldest subjects. Specifically, investigators detected significant differences in the strength of connections of brain signals for both age and gender.
“This work provides evidence that EEG [electroencephalogram], 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.”
Researchers began the study with three questions:
• Can usable brain data be collected in an uncontrolled setting?
• How well do different models of EEG headsets perform?
• Is it possible to collect substantial amounts of data relatively quickly?
Data was collected from 431 people as they viewed a sculptural installation that included both visual and aural representations of the heart.
Researchers categorized each piece as either complex or moderate; they also asked each of the 20 participants to face a blank wall for one minute before entering the exhibit in order to obtain baseline data.
The initial results allowed researchers to predict from the brain activity with 55 percent accuracy whether the participant was looking at a complex piece of art, one categorized as moderately complex or a blank wall. That compares to 33 percent accuracy for random prediction.
Researchers believe their findings could have varying applications. Much of Contreras-Vidal’s recent work centers on using brain activity to help people with disabilities use bionic hands or to regain movement by “walking” in exoskeletons powered by their own thoughts.
He sees this research with artists and museum-goers and a related project that collects brain activity from dancers, visual artists, musicians and writers – as potentially leading to technologies that can restore sensory processing in people with neurological impairments.
Artists and museum curators could also use the findings to learn more about how museum displays affect the way people move through and react to an exhibit, which works are preferred by museum-goers and other information.
Still, the research agenda does not provide a primer on how to create art.
“I don’t think we will understand the mystery (of how art is created),” he said. “The conception of art is a very individual process, built on the artist’s experiences, skills, memories, values and drives.
“But we will know what happens in the brain. We might find that there are people who are very attuned to visual art, or to music, or poetry, and there might be an underlying common neural network. If we know that, we could optimize the delivery of art for therapy, for teaching.”