Amanda Studnicki, captain of the high school tennis team and four-year veteran of college varsity tennis, has been coaching in the moment for years.
All she had to do now was think small. Like a little table tennis.
For weeks, Studnicki, a graduate student at the University of Florida, worked and rallied against dozens of players on a table tennis court. Her opponents donned a sci-fi look, a cap of electrodes cascading from their heads into a backpack as they played against a studniki or ball-serving machine. This cyborg appearance was vital to Studnicki’s goal: to understand how our brains react to the intense demands of a high-speed sport like table tennis — and what a difference a machine opponent makes.
Studnicki and her advisor, Daniel Ferris, discovered that the brains of table tennis players react very differently to human or machine opponents. Faced with the ambiguity of the ball machine, players’ brains scrambled for themselves in anticipation of the next serve. While there were the clear signals that a human opponent was about to serve, their neurons were firing in unison, seeming confident of their next move.
The results have implications for athletic training, suggesting that human opponents provide realism that cannot be replaced by machine aids. And as robots grow more common and complex, understanding our brains’ response can help make our artificial companions more natural.
“Robots are getting more and more ubiquitous. You have companies like Boston Dynamics that are building robots that can interact with humans and other companies that are building social assistant robots that help elderly people,” said Ferris, a professor of biomedical engineering at UF. It occurs when they interact with other humans. Our long-term goal is to try to understand how the brain reacts to these differences.”
Ferris’ lab has long studied the brain’s response to visual cues and motor tasks, such as walking and running. He was looking forward to an upgrade to the study of complex, fast-paced motion when Studnicki, with her background in tennis, joined the research group. So the lab decided that tennis was the perfect sport to deal with these questions. But the bulky movements—particularly the soaring strikes—proved to be an obstacle to the burgeoning technique.
“So we brought things down to the level of table tennis and asked all the same questions we had for tennis before,” Ferris said. Researchers have yet to compensate for the smaller movements of table tennis. So Ferris and Studnicki doubled the 120 electrodes in a typical brain scan cap, each additional electrode providing control over rapid head movements during a game of table tennis.
With all of these electrodes scanning the players’ brain activity, Studnicki and Ferris were able to fine-tune the area of the brain that converts sensory information into movement. This area is known as the parietal-occipital cortex.
“It takes in all of your senses—visual, vestibular, auditory—and provides information about creating your motor plan. It’s been studied a lot for simple tasks, like reaching and grasping, but it’s all static,” Studnicki said. “We wanted to understand how it works with complex movements like tracking and intercepting a ball in space, and table tennis was perfect for that.”
The researchers analyzed dozens of hours of playing against studniki and the ball machine. When playing against another human being, the players’ neurons work in unison, as if they were all speaking the same language. By contrast, when the players faced a ball-serving machine, the neurons in their brains weren’t lined up with one another. In the world of neuroscience, this lack of alignment is known as desynchronization.
“If we have 100,000 people on a football field and they’re all cheering together, it’s like synchronization in the brain, a sign that the brain is relaxed,” Ferris said. “If we have these same 100,000 people but they’re all talking to their friends, they’re busy but they’re out of sync. In a lot of cases, that desynchronization is an indication that the brain is doing a lot of math instead of sitting still and idling.”
The team suspects that the players’ brains were so active while waiting for the bots to be dispatched because the machine didn’t provide any cues as to what they were going to do next. What is clear is that our brains process these two experiences very differently, suggesting that training with a machine may not offer the same experience as playing against a real opponent.
“I still see a lot of value in practicing on the instrument,” Studnicki said. “But I think as machines will evolve in the next 10 or 20 years, we can see more natural behaviors that players can practice with.”