Using Fewer Brain Regions May Speed Learning

Why can some people master a new skill rapidly while others need extra time or practice? To find out, researchers at University of California, Santa Barbara developed a study that measured the connections between different brain regions while participants learned to play a simple game.

The researchers discovered that the neural activity in the quickest learners differed from that of the slowest. Their analysis provides new insight into what happens in the brain during the learning process and sheds light on the role of interactions between different regions.

The findings suggest that recruiting unnecessary parts of the brain for a given task, analogous to overthinking the problem, plays a critical role in this important difference.

Said Scott Grafton, a professor in University of California, Santa Barbara’s department of psychological and brain sciences:

“It’s useful to think of your brain as housing a very large toolkit.



Measuring Neural Activity

At the university’s Brain Imaging Center, study participants played a simple game while their brains were scanned with fMRI. The technique measures neuron activity by tracking the flow of blood in the brain, highlighting which regions are involved in a given task.





Complex Dynamic Network

Lead author Danielle Bassett, an expert in network science, developed new analysis methods to determine what was happening in the participants’ brains that correlated with these differences. But rather than trying to find a single spot in the brain that was more or less active, the team investigated the learning process as the function of a complex, dynamic network involving various regions of the brain.

Said Bassett, assistant professor of innovation at the University of Pennsylvania:




“When network scientists look at these graphs, they see what is known as community structure,” Bassett says. “There are sets of nodes in a network that are really densely interconnected to each other. Everything else is either independent or very loosely connected with only a few lines.”

Dynamic Community Detection




According to Grafton, in some ways this trend was not surprising since the team was essentially seeing the learning process on the neurological level, with the participants’ brains reorganizing the flow of activity as they mastered this new skill. Says Grafton:

“Previous brain imaging research has mostly looked at skill learning over—at most—a few days of practice, which is silly. Who ever learned to play the violin in an afternoon?


Executive Function




“This neurological trait is associated with making and following through with plans, spotting and avoiding errors and other higher-order types of thinking,” Grafton says.



“It’s the people who can turn off the communication to these parts of their brain the quickest who have the steepest drop-off in their completion times,” says Bassett. “It seems like those other parts are getting in the way for the slower learners. It’s almost like they’re trying too hard and overthinking it.”

Follow-on studies will look into why some people are better than others at shutting down the connections in these parts of the brains.


Learning-induced autonomy of sensorimotor systems
Danielle S Bassett, Muzhi Yang, Nicholas F Wymbs & Scott T Grafton
Nature Neuroscience (2015) doi:10.1038/nn.3993