These images show how your brain lights up when you crave food or drugs

The newly-discovered neuromarker could prove to be a potent tool for treating substance abuse.
Chris Young
Brain activity hologram
Brain activity hologram

da-kuk/iStock  

The neural basis for cravings is poorly understood, but a new study identifies a stable brain pattern, or neuromarker, for drug and food cravings.

The discovery could prove to be a vital step toward improving the living conditions of people suffering from addiction by developing new treatments that tackle the problem at its origin, a press statement from Yale University reveals.

Machine learning algorithm determines craving neuromarker

Scientists from Yale, Dartmouth, and the French National Centre for Scientific Research (CNRS) identified the neuromarker, and they outlined their findings in a paper in the journal Nature Neuroscience.

These images show how your brain lights up when you crave food or drugs
Medial, lateral and insula displays of the most consistent pattern weights.

The discovery could help to better understand craving disorders, develop new treatments, and also improve methods for diagnosing substance use disorders. Physicians diagnose a lot of diseases today by identifying biological markers in a patient — diabetes, for example, is diagnosed by testing for a blood marker called A1C.

"One benefit of having a stable biological indicator for a disease is that you can then give the test to any person and say that they do or do not have that disease," explained Hedy Kober, an associate professor of psychiatry at Yale School of Medicine and an author on the study. "And we don’t have that for psychopathology and certainly not for addiction."

Kober and her colleagues set out to determine whether they could find an equivalent marker for craving. They decided to use a machine learning algorithm to analyze brain activity. To be precise, they set out to test the hypothesis that people experiencing cravings might share a pattern of brain activity. If that were to be the case, a machine learning algorithm could, therefore, detect that pattern and use it to predict craving levels in individuals based on brain images.

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Neuromarker could boost substance use disorder treatment

Ultimately, the researchers said they identified a pattern of brain activity that could be used to predict the intensity of drug and food cravings using only fMRI images.

The newly-observed pattern — dubbed "Neurobiological Craving Signature (NCS)" — includes activity in brain areas that have previously been linked to addiction.

They did this by using functional magnetic resonance imaging (fMRI) data and self-reported assessments of cravings from 99 volunteers — some of whom were drug users and others not. The scientists collected the brain data while the volunteers viewed images of drugs and food, and the individuals also rated how highly they craved the items they saw.

These images show how your brain lights up when you crave food or drugs
Pop-out rectangles show the multivariate pattern for selected clusters of interest.

The new pattern works for many different substances, according to the scientists. "It’s really a biomarker for craving and addiction," Kober explained. "There’s something common across all of these substance use disorders that is captured in a moment of craving.”

What's more, Kober pointed out that it "gives us a really granular understanding of how these regions interact with and predict the subjective experience of craving."

However, though NCS shows a great deal of promise for creating new medical treatments and diagnosis methods, Kober did concede that it's not yet ready for clinical use and it requires further validation. The next step, she said, is to understand the network of brain regions associated with NCS more clearly in a bid to determine whether the pattern can predict how individuals will respond to treatments for substance use disorders.

“Our hope,” Kober said, “is that the brain, and specifically the NCS as a stable biological indicator, might allow us to not only to identify who has a substance use disorder and to understand the variance in people’s outcomes, but also who will respond to particular treatments.”