PNAS: Danielle Bassett and Scott T. Grafton use analysis of brain to predict the ability to learn

April 20, 2011

An international team of scientists has developed a way to predict how much a person can learn, based on studies at UCSB’s Brain Imaging Center. Researchers collected brain imaging data from people performing a motor task, and then analyzed this data using new computational techniques. They found evidence that the flexibility of a person’s brain can be used to predict how well someone will learn. “Parts of the brain communicate with one another very strongly, so they form a sort of module of intercommunicating regions of the brain,” said first author Danielle S. Bassett, postdoctoral fellow in physics at UCSB. Her current studies are carried out within UCSB's Department of Physics and Department of Psychological and Brain Sciences. Scott T. Grafton, director of the UCSB Brain Imaging Center and professor of psychology is senior author.

The study was published in the Proceedings of the National Academy of Sciences (PNAS). Authors of the PNAS study, in addition to Bassett and Grafton, are Nicholas F. Wymbs, UCSB; Mason A. Porter, University of Oxford; Peter J. Mucha, University of North Carolina, and Jean M. Carlson, UCSB. READ MORE (UCSB Featured News)

Nicholas F. Wymbs, Danielle S. Bassett, Scott T. Grafton
credit: George Foulsham, Office of Public Affairs, UCSB