Brain scans predict if smokers can quit

"The neural response to quitting even after one day can give us valuable information that could inform new and existing personalized intervention strategies for smokers, which is greatly needed," says lead author James Loughead. (Credit: Matteo Parrini/ Flickr)

Changes in the brain’s working memory may accurately predict who is more likely to quit smoking.

Researchers say the findings—which go above and beyond current clinical or behavioral tools for assessing relapse risk—could help separate successful quitters from those who will start smoking again, and could lead to new treatments.


Smokers who relapsed within seven days from their target quit day had disruptions in the brain’s working memory system—mainly a decrease in the part of the brain that supports self-control and a boost in the area that promotes an “introspective” state—during abstinence.

“This is the first time abstinence-induced changes in the working memory have been shown to accurately predict relapse in smokers,” says senior author Caryn Lerman, professor of psychiatry at the University of Pennsylvania.

“The neural response to quitting even after one day can give us valuable information that could inform new and existing personalized intervention strategies for smokers, which is greatly needed,” says lead author James Loughead, associate professor of psychiatry.

Smoking in the United States is at an all-time low in adults; however, there are still 42 million Americans who do smoke, including teenagers and young adults.

Working memory and smoking

Researchers used functional magnetic resonance imaging (fMRI) to explore the effects of brief abstinence from smoking on working memory and its associated neural activation in 80 smokers seeking treatment. Participants were between 18 and 65 years old and reported smoking more than 10 cigarettes a day for more than six months.

Two fMRI sessions occurred: one immediately after a person smoked and one 24 hours after abstinence began. Following smoking cessation counseling, participants set a future target quit date.  Seven days after the target quit date, participants completed a monitoring visit, during which smoking behavior was accessed, including a urine test.

Past research strongly suggests that if a person is tobacco free after seven days, they will likely remain that way for six months, if not longer, and is therefore highly predictive of long-term quitting success.

Sixty one smokers relapsed and 19 quit successfully for this period, the researchers report.

Those who relapsed had decreased activity in the left dorsolateral prefrontal cortex, which controls executive functions, like working memory, compared to those who quit. Working memory is an essential cognitive function necessary for staying focused, blocking distractions, and completing tasks.

They also had reduced suppression of activation in the posterior cingulate cortex, a central part of the default mode network of the brain, which is more active when people are in a so-called “introspective” or “self-referential” state.

Early smoking relapse

Past studies have shown relationships between these brain networks. A study in JAMA Psychiatry from Lerman and colleagues published earlier this year showed how smokers suffering from nicotine withdrawal have more trouble shifting from the default mode network into the executive control network, where people can exert more conscious, self-control over cravings and to focus on quitting for good.  However, this new study is the first to use that brain activity to help predict relapse in smokers.

There are several tools currently used to predict changes of relapse, including the Fagerstrom Test for Nicotine Dependence and other smoking urges and withdrawal tests, but there is much room for improvement.

Researchers determined predictive values of these two relapse models, as well as a new model that includes the working memory data. Using resampling methods, they found that incorporating the working memory-related brain activity resulted in an 81 percent correct prediction rate, a significant improvement over current models.

Without that data, the prediction values were 73 percent for the model of withdrawal symptoms and demographic/smoking history predictors, and 67 percent for demographic/smoking history predictors only.

The National Cancer Institute and National Institutes of Drug Abuse and the Pennsylvania Department of Health supported the research, which was published in the journal Neuropsychopharmacology.

Source: University of Pennsylvania