Researchers from the Center of the Neural Basis of Cognition (CNBC) - a joint programme between Carnegie Mellon University and the University of Pittsburgh found 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 the ways in which the brain's activity can be "flexed" during learning could eventually be used to develop better treatments for stroke and other brain injuries, researchers said.
"These findings could be the basis for novel rehabilitation procedures for the many neural disorders that are characterised by improper neural activity," said Byron M Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon.
"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," Yu added.
For the study, the research team trained animals to use a brain-computer interface (BCI) and 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, researchers said.