Researchers, including University of California, Santa Barbara professor Scott Grafton and colleagues at the University of Pennsylvania and Johns Hopkins University, found that recruiting unnecessary parts of the brain for a task, or overthinking, plays a critical role in the way we learn.
The lab had participants play a game with their brains involving patterns. Participants responded to color-coded notes by pressing buttons on a hand-held controller and were asked to play the sequences back as quickly and accurately as possible. After this, their brains were scanned to measure neural activity by the flow of blood in the brain, highlighting which regions are involved in a given task.
The participants returned to the lab at two, four, and six week intervals for further scans to determine how well practice had helped them master the skill. Initially, participants took much longer to figure out the patterns, but over time, the brain scans showed that their completion times had dropped. Some picked up sequences immediately, while others gradually improved.
“When you learn how to do something, such as play a musical instrument, your brain uses many different tools to learn,” said Grafton. “With more time and practice, we rely less on these tools, such as the visual part, and use core motor areas. Our lab shows that beyond practice, these tools might help us further learning.”
Researchers used analysis methods to see what was happening in the participants’ brains that correlated in difference of learning rates. They looked at the learning process as a function of a dynamic network involving various communities in the brain and examined the brain as a whole rather than finding single spots.
“We looked at three communities in the brain,” said Grafton. “There’s the visual, motor, and non-visual/non-motor. The community structure contains networks that are densely connected to each other. To analyze the brain, we use algorithms to determine which areas are incorporated into clusters and how their interactions change over time. With this algorithm, we are able to predict how likely two areas will interact and figure out trends on how regions responsible for different functions work together.”
Scientists delved into the differences among participants by looking at the neurological correlates of the learning process that comes from focus to explain why some learn faster than others. Participants who showed less neural activity tended to learn the fastest.
The critical distinction related to the frontal cortex and the anterior cingulate cortex, which are needed for complex tasks but tend to hinder mastering simple ones. The frontal and anterior cingulate cortex are the last to develop in humans. Because the frontal cortex and anterior cortex are primarily used for complex tasks, adults often over think and learn simple tasks slower than children, who have not yet developed these cortices.
“People who can turn off communication in the frontal and anterior cingulate cortex tended to learn the patterns faster,” said Grafton. “Those that are not as good seemed to overthink and try too hard, thus getting in the way of their learning.”
Additional studies will look at why some people are better than others at shutting down the connections in the frontal and anterior cortex of the brain.
Other authors include Muzhi Yang of the University of Pennsylvania and Nicholas Wymbs of Johns Hopkins University.
The research was supported by the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the US Army Research Laboratory, the Institute for Translational Medicine and Therapeutics, the National Science Foundation, the National Institutes of Health, and the U.S. Army Research Office.