MIT News (December 9, 2013): Balancing Old and New Skills

Publication Date: 
Mon, 12/09/2013

To learn new motor skills, the brain must be plastic: able to rapidly change the strengths of connections between neurons, forming new patterns that accomplish a particular task. However, if the brain were too plastic, previously learned skills would be lost too easily.
This works well for learning one skill, but complications arise when the brain is trying to learn many different skills at once.  Because the same distributed network controls related motor tasks, new modifications to existing patterns can interfere with previously learned skills.
A new computational model developed by MIT neuroscientists explains how the brain maintains the balance between plasticity and stability, and how it can learn very similar tasks without interference between them.
The key, the researchers say, is that neurons are constantly changing their connections with other neurons. However, not all of the changes are functionally relevant — they simply allow the brain to explore many possible ways to execute a certain skill, such as a new tennis stroke.
“Your brain is always trying to find the configurations that balance everything so you can do two tasks, or three tasks, or however many you’re learning,” says Robert Ajemian, a research scientist in MIT’s McGovern Institute for Brain Research and lead author of a paper describing the findings in the Proceeding of the National Academy of Sciences the week of Dec. 9. “There are many ways to solve a task, and you’re exploring all the different ways.”
As the brain explores different solutions, neurons can become specialized for specific tasks, according to this theory.
As the brain learns a new motor skill, neurons form circuits that can produce the desired output — a command that will activate the body’s muscles to perform a task such as swinging a tennis racket. Perfection is usually not achieved on the first try, so feedback from each effort helps the brain to find better solutions.
This works well for learning one skill, but complications arise when the brain is trying to learn many different skills at once.  Because the same distributed network controls related motor tasks, new modifications to existing patterns can interfere with previously learned skills.
http://web.mit.edu/newsoffice/2013/balancing-old-and-new-skills-1209.html