Two Different Brain Systems Cooperate in Learning Process

Saturday, February 24, 2018 - 14:53

Researchers have found out that two different brain systems work cooperatively in learning process and focused on the interplay of two very different modes of learning a new task: reinforcement learning and working memory.

Reinforcement learning is an “under-the-hood” process in which people gradually learn which actions to take by processing rewards and punishments at the neural level, and then choosing the one that works best on average—even if the person is not aware of it. In contrast, working memory involves keeping previous actions and their outcomes in mind to more rapidly and flexibly improve performance, Futurity reports.

“People have largely interpreted these systems as working independently or as competing with each other in the learning process,” says Michael Frank, a professor in Brown University’s cognitive, linguistic, and psychosocial sciences department and coauthor of the paper in Proceedings of the National Academy of Sciences. “But we show that the two work together, with neural signals underlying working memory helping to guide those that support reinforcement learning.”

In this study, researchers developed an experimental method designed to isolate the brain signals associated with each of the two systems. They showed 40 study participants a series of symbols on a screen and asked participants, for each symbol, to press a particular button on a keyboard.

The researchers didn’t tell participants which key was the right one for each symbol. They had to learn it. When they got it right, participants were rewarded with points. Over repeated trials, the participants came to learn which keys corresponded with which symbols.

The study shows that when memory demands were high, the signals in the brain correlated to reinforcement learning actually got stronger. In other words, when the working memory system was overtaxed, the reinforcement learning system became more important in the learning process.

In contrast, when participants could hold information in mind, signals associated with reinforcement learning were weaker, suggesting an increased role for working memory.

The researchers also found that they could decode from the brain signals in a particular trial whether information was likely to be in memory or not. That too traded off with the neural marker of reinforcement learning. Those findings, the researchers say, suggest that the two systems aren’t working independently.

Anne Collins, an assistant professor at the University of California, Berkeley, led the work when she was a postdoctoral researcher working with Frank, who directs the Initiative for Computation in Brain and Mind in the Brown Institute for Brain Science.

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