MRI Analysis Predicts Skill at Video Game
By simply scanning your brain’s activity with magnetic resonance imaging (MRI), researchers say they can tell “with unprecedented accuracy” how well you would perform on a strategic video game.
For the study, researchers used conventional brain imaging methods in a novel way. Rather than analyze the “before and after” brain activity while participants learn and perform a complex task, the researchers instead studied the background activity in the basal ganglia, a set of brain structures associated with procedural learning, feelings of reward and coordinated movements.
Through the use of MRI and a method called multivoxel pattern analysis, the researchers noted a significant difference in a certain type of MRI signal, called T2*, in the basal ganglia of study participants. By analyzing these differences, the researchers were able to predict the variance (differences in performance) 55 to 68 percent of the time for the 34 people who would learn how to play the game.
“There are many, many studies, hundreds perhaps, in which psychometricians, people who do the quantitative analysis of learning, try to predict from SATs, GREs, MCATS or other tests how well you’re going to succeed at something,” said University of Illinois psychology professor and Beckman Institute director Dr. Art Kramer.
These types of techniques, along with studies that look at the relative size of specific-brain structures, have had some success predicting learning, Kramer said, “but never to this degree in a task that is so complex.”
“We take a fresh look at MRI images that are recorded routinely to investigate brain function,” said Ohio State University psychology professor Dr. Dirk Bernhardt-Walther, who designed and performed the computational analysis together with Illinois electrical and computer engineering graduate student Loan Vo.
“By analyzing these images in a new way, we find variations among participants in the patterns of brain activity in their basal ganglia,” Bernhardt-Walther said.
“Powerful statistical algorithms allow us to connect these patterns to individual learning success. Our method may be useful for predicting differences in abilities of individuals in other contexts as well,” he said. “Testing this would be inexpensive because the method recycles MRI images that are recorded in many studies anyway.”
For the study, volunteers were chosen who didn’t have much prior experience with video games. After their brains were imaged, they had 20 hours to learn how to play Space Fortress, a game developed at the University of Illinois and designed to test the participants’ cognitive skills. Players must try to destroy a fortress while protecting their own ship from many potential hazards.
The game is quite challenging, Kramer said. It frequently challenges players to shift their attention to chase various goals or avoid threats. When they are first beginning to play, study subjects “tend to start out with negative 2,000 points,” he said. However, after 20 hours of training and practice, all the players’ scores go up quite a bit. Some do far better than others, however, a difference that can largely be predicted by analyzing activity in parts of the basal ganglia.
“We predict up to three times as much of the variance (in learning) as you would using performance measures,” Kramer said.
The researchers analyzed three brain regions: the caudate nucleus and the putamen, two structures that are active when a person is learning new motor skills (such as moving a joystick); these regions are also important during tasks requiring strategy and quickly shifting one’s attention. A third region, the nucleus accumbens, processes emotions associated with reward or punishment.
During the study, activity in the putamen and caudate nucleus were found to be better predictors of future video game performance than in the nucleus accumbens. The researchers also found that white matter (the axons and dendrites that carry signals between neurons), but not gray matter (the cell bodies), offered more clues in predicting game success.
“Our data suggest that some persistent physiological and/or neuroanatomical difference is actually the predictor of learning,” Kramer said.
Kramer emphasized that the findings should not be interpreted to mean that some people are destined to succeed or fail at a given task or learning challenge.
“We know that many of these components of brain structure and function are changeable,” he added.
The study is published in the online journal PLoS ONE.
Source: University of Illinois
Pedersen, T. (2015). MRI Analysis Predicts Skill at Video Game. Psych Central. Retrieved on March 25, 2018, from https://psychcentral.com/news/2011/01/17/mri-analysis-predicts-skill-at-video-game/22702.html