Brain Research Helps Unlock Secrets of Learning

UT Dallas researchers report that brain stimulation accelerated learning in laboratory experiments that may eventually lead to improved treatments for strokes, tinnitus, chronic pain and more.

In addition, rats in the study were able to perform tasks they had learned under stimulation even after their brain responses returned to their pre-stimulation state. These findings, published in the April 14 issue of Neuron, have allowed researchers to better understand how the brain learns and encodes new skills.

Previous studies showed that people and animals that practice a task experience major changes in their brains. Learning to read Braille with a single finger, for example, leads to increased brain responses to the trained digit. Similarly, learning to discriminate among a set of tones leads to increased brain responses to the trained tones.

But it has not been clear whether these brain changes are just a coincidence or whether they truly help with learning. The current research shows that they do, said Dr. Amanda Reed, who wrote the article with colleagues from The University of Texas at Dallas’ School of Behavioral and Brain Sciences.

Reed and her fellow researchers used brain stimulation to release neurotransmitters that caused the brain to increase its response to a small set of tones. The team found that this increased response allowed rats to learn a task using these tones more quickly than animals that had not received stimulation. This finding provides the first direct evidence that a larger brain response can aid learning.

Future treatments that enhance large changes in the brain may assist with recovery from stroke or learning disabilities. In addition, this new understanding may lead to better treatments for such brain disorders as tinnitus and chronic pain that occur when large-scale brain changes are unable to reverse.

Researchers examined the laboratory animals’ brains again after the rats had practiced their learned task for a few weeks. The brains appeared to have returned to normal, even though the animals had not forgotten how to perform the task they had learned. Although large changes in the brain were helpful for initial learning, those changes did not have to be permanent to be beneficial, Reed wrote.

“We think that this process of expanding the brain responses during learning, and then contracting them back down after learning is complete, may help animals and people to be able to perform many different tasks with a high level of skill,” Reed said. “So for example, this may explain why people can learn a new skill like painting or playing the piano without sacrificing their ability to tie their shoes or type on a computer.”  

The study by Reed and colleagues supports a theory that large-scale brain changes are not directly responsible for learning.  Rather, they accelerate learning by creating an expanded pool of neurons from which the brain can select the most efficient, small “network” to accomplish the new skill.

This new view of the brain can be compared to an economy or an ecosystem, rather than a computer, Reed said. Computer networks are designed by engineers to use a finite set of rules and solutions to solve problems. But the brain, like other natural systems, works by trial and error.

The first step of learning is to create a large set of diverse neurons that are activated by doing the new skill. The second step is to identify a small subset of neurons that can accomplish the necessary computation and return the rest of the neurons to their previous state, at which point they can be used to learn the next new skill.

By the end of a long training period, skilled performance is accomplished by small numbers of specialized neurons, not by large-scale reorganization of the brain. This research helps explain how brains can learn new skills without interfering with earlier learning.

The researchers used anesthesia when inserting electrodes into the laboratory rats’ brains. The brain stimulation was painless for the rats, Reed said. Co-authors of the study were Drs. Jonathan Riley, Ryan Carraway, Andres Carrasco, Claudia Perez, Vikram Jakkamsetti and Michael Kilgard of UT Dallas.

The work was supported by the James S. McDonnell Foundation. Reed is a former McDermott Scholar at UT Dallas. After earning her bachelor’s and master’s degrees, she went on to also earn a PhD in neuroscience at UT Dallas.