News Release 11-020
Brain Scans Predict Likely Success When It Comes to Quitting Smoking
University of Michigan study says fMRI scans know more about us than we do
January 31, 2011
View a video with Emily Falk, director of University of Michigan's Communication Neuroscience Laboratory.
This material is available primarily for archival purposes. Telephone numbers or other contact information may be out of date; please see current contact information at media contacts.
New research from University of Michigan says brain scans showing neural reactions can predict behavior change even better than the person whose brain is being scanned.
Emily Falk, director of University of Michigan's Communication Neuroscience Laboratory, recently led a study that scanned the brain activity of 28 heavy smokers to investigate whether pro-health messages would have an impact on their ability to quit smoking. The smokers were recruited from an anti-smoking program.
The researchers found a positive relationship exists between observed brain activity and successfully quitting smoking, even when test subjects erroneously predict their likelihood of success. Moreover, their report concludes that "neural activity is a useful complement to existing self-report measures."
A forthcoming issue of Health Psychology, a peer-reviewed journal, will report the findings.
For the study, functional magnetic resonance imaging (fMRI), a type of specialized scanning technology, was used to monitor how participants responded to a series of television ads designed to help people quit smoking.
After seeing each ad, the test subjects rated how it affected their intention to quit, whether it increased their confidence about quitting, and how much they related to the message. A month after the scan, researchers contacted participants to see how they were doing and to obtain biological verification of how much they were smoking, by assessing their CO levels.
Participants reported smoking an average of 5 cigarettes a day, compared with an average of 21 a day at the start of the study, and CO levels were consistent with these self-reports.
"These results bring us one step closer to the ability to use functional magnetic resonance imaging to select the messages that are most likely to affect behavior change both at the individual and population levels," said Falk. "It seems that our brain activity may provide information that introspection does not."
The study was partially funded by Falk's National Science Foundation's research fellowship. The National Institutes of Health also contributed to the study. Falk's colleagues Matthew Lieberman, Elliot Berkman and Danielle Whalen also took part in the study and evaluation of participants.
To learn more about the study, see University of Michigan's news article.
Emily Falk discusses the results of a new study that uses fMRI scans to predict smoking.
Credit and Larger Version
Bobbie Mixon, NSF, (703) 292-8070, email: firstname.lastname@example.org
The U.S. National Science Foundation propels the nation forward by advancing fundamental research in all fields of science and engineering. NSF supports research and people by providing facilities, instruments and funding to support their ingenuity and sustain the U.S. as a global leader in research and innovation. With a fiscal year 2023 budget of $9.5 billion, NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and institutions. Each year, NSF receives more than 40,000 competitive proposals and makes about 11,000 new awards. Those awards include support for cooperative research with industry, Arctic and Antarctic research and operations, and U.S. participation in international scientific efforts.
Connect with us online
NSF website: nsf.gov
NSF News: nsf.gov/news
For News Media: nsf.gov/news/newsroom
Awards database: nsf.gov/awardsearch/
Follow us on social
Facebook: facebook.com/US.NSF Instagram: instagram.com/nsfgov