Scientists have discovered a fundamental constraint in the brain that may explain why it’s easier to learn a skill that’s related to an ability you already have.
For example, a trained pianist can learn a new melody easier than learning how to hit a tennis serve.
As reported in Nature, the researchers found for the first time that there are limitations on how adaptable the brain is during learning and that these restrictions are a key determinant for whether a new skill will be easy or difficult to learn.
Understanding how the brain’s activity can be “flexed” during learning could eventually be used to develop better treatments for stroke and other brain injuries.
Lead author Patrick T. Sadtler, a Ph.D. candidate in the University of Pittsburgh department of bioengineering, compared the study’s findings to cooking.
“Suppose you have flour, sugar, baking soda, eggs, salt, and milk. You can combine them to make different items—bread, pancakes, and cookies—but it would be difficult to make hamburger patties with the existing ingredients,” Sadtler says.
“We found that the brain works in a similar way during learning. We found that subjects were able to more readily recombine familiar activity patterns in new ways relative to creating entirely novel patterns.”
Moving the Cursor
For the study, the research team trained animals (Rhesus macaques) to use a brain-computer interface (BCI), similar to ones that have shown recent promise in clinical trials for assisting quadriplegics and amputees.
“This evolving technology is a powerful tool for brain research,” says Daofen Chen, program director at the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health. “It helps scientists study the dynamics of brain circuits that may explain the neural basis of learning.”
The researchers recorded neural activity in the subject’s motor cortex and directed the recordings into a computer, which translated the activity into movement of a cursor on the computer screen.
This technique allowed the team to specify the activity patterns that would move the cursor. The test subjects’ goal was to move the cursor to targets on the screen, which required them to generate the patterns of neural activity that the experimenters had requested. If the subjects could move the cursor well, that meant that they had learned to generate the neural activity pattern that the researchers had specified.
The results showed that the subjects learned to generate some neural activity patterns more easily than others, since they only sometimes achieved accurate cursor movements.
The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning.
Only so Flexible
“We wanted to study how the brain changes its activity when you learn, and also how its activity cannot change. Cognitive flexibility has a limit—and we wanted to find out what that limit looks like in terms of neurons,” says Aaron P. Batista, assistant professor of bioengineering at University of Pittsburgh.
Byron M. Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon, believes this work demonstrates the utility of BCI for basic scientific studies that will eventually impact people’s lives.
“These findings could be the basis for novel rehabilitation procedures for the many neural disorders that are characterized by improper neural activity,” Yu says.
“Restoring function might require a person to generate a new pattern of neural activity. We could use techniques similar to what were used in this study to coach patients to generate proper neural activity.”
The researchers are part of the Center for the Neural Basis of Cognition (CNBC), a joint program between Carnegie Mellon University and the University of Pittsburgh. Additional researchers from University of Pittsburgh, Carnegie Mellon, and Stanford University and Palo Alto Medical Foundation contributed to the work.
The NIH, National Science Foundation, and the Burroughs Wellcome Fund funded the research.
Source: Carnegie Mellon. Republished from Futurity.org under Creative Commons License 3.0.
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