Newly identified neuromarker reveals clues to drug and food cravings

Newly identified neuromarker reveals clues to drug and food cravings

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Summary: Researchers have identified neural biomarkers associated with food and drug cravings. The findings could help pave the way for new addiction treatments.

source: Yale

Craving is known to be a key factor in substance use disorders and can increase the likelihood of future drug use or relapse. Yet its neural basis—or how the brain generates craving—is not well understood.

In a new study, researchers from Yale, Dartmouth, and the French National Center for Scientific Research (CNRS) have identified a robust brain model, or neuromarker, for drug and food craving. Their findings were published in Nature Neurology.

The discovery could be an important step toward understanding the brain basis of craving, addiction as a brain disorder, and how to better treat addiction in the future, the researchers said. Importantly, this neuromarker can also be used to differentiate drug users from non-users, making it not only a neuromarker for craving, but also a potential neuromarker that may one day be used in the diagnosis of substance use disorders .

For many diseases, there are biological markers that doctors can use to diagnose and treat patients. To diagnose diabetes, for example, doctors test a blood marker called A1C.

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

To determine whether such a marker could be established for longing, Kober and her colleagues — Leonie Coban of CRNS and Thor Wager of Dartmouth College — used a machine learning algorithm. Their idea was that if many individuals experiencing similar levels of craving shared a pattern of brain activity, then a machine learning algorithm might be able to detect that pattern and use it to predict craving levels based on brain patterns. images.

For the study, they used functional magnetic resonance imaging (fMRI) data, which offers insight into brain activity, and self-reported willingness ratings from 99 people to train and test the machine learning algorithm.

fMRI data were collected while individuals who self-identified as either drug users or nonusers viewed images of drugs and highly palatable food. Participants then rated how much they longed for the objects they saw.

The algorithm identified a pattern of brain activity that could be used to predict the intensity of drug and food cravings from fMRI images alone, the researchers said.

The pattern they observed — which they called the “Neurobiological Signature of Craving (NCS)” — involved activity in several areas of the brain, some of which previous studies have linked to substance use and craving.

However, NCS also provides a new level of detail, showing how neural activity in subregions of these brain regions can predict craving.

“This gives us a really detailed understanding of how these regions interact and predict the subjective experience of thirst,” Kober said.

NCS also revealed that the brain’s responses to drug and food cues were similar, suggesting that drug cravings arise from the same neural systems that generate food cravings. Importantly, the marker was able to distinguish drug users from non-users based on their brain responses to drug cues, but not to food cues.

“And these findings are not substance-specific because we included participants who used cocaine, alcohol, and cigarettes, and NCS predicts craving for all of them,” Kober said. “So it’s really a biomarker for craving and addiction. There’s something in common in all of these substance use disorders that is caught in a moment of craving.”

In a new study, researchers from Yale, Dartmouth, and the French National Center for Scientific Research (CNRS) have identified a robust brain model, or neuromarker, for drug and food craving. Image is in the public domain

Wager also points out that emotional and motivational processes that may seem similar actually involve different brain pathways and can be measured in different ways.

“What we’re seeing here is probably not a general ‘reward’ signature,” he said, “but something more selective for food and drug cravings.”

In addition, NCS also offers a new brain target to better understand how food and drug craving can be influenced by context or emotional states. “For example,” Coban said, “we can use the NCS in future studies to measure how stress or negative emotions increase the urge to use drugs or indulge in our favorite chocolate.”

Kober notes that while the NCS is promising, it needs further validation and is not yet ready for clinical use. That’s probably a few years away. Now she — along with her team and collaborators — are working to better understand this network of brain regions and see if the NCS can predict how people with substance use disorders will respond to treatment.

This, she said, would make this neuromarker a powerful tool to inform treatment strategies.

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

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About this addiction research news

Author: Press office
source: Yale
Contact: Press Office – Yale
Image: Image is in the public domain

Original research: Closed access.
A neuromarker for drug and food craving distinguishes users from nonusersby Hedy Kober et al. Nature Neurology


A neuromarker for drug and food craving distinguishes users from nonusers

Craving is a central feature of substance use disorders. It is a strong predictor of substance use and relapse and is associated with binge eating, gambling, and other maladaptive behaviors.

Desire is measured by self-report, which is limited by introspective access and sociocultural contexts. Neurobiological markers of craving are needed and lacking, and it remains unclear whether drug and food craving involve similar mechanisms.

In three functional magnetic resonance studies (n= 99), we used machine learning to identify a cross-validated neuromarker that predicted self-reported intensity of cue-induced drug and food craving (P< 0.0002).

This pattern, which we call the Neurobiological Craving Signature (NCS), includes ventromedial prefrontal and cingulate cortex, ventral striatum, temporal/parietal association areas, mediodorsal thalamus, and cerebellum.

Importantly, NCS responses to drug versus food cues discriminated drug users from nonusers with 82% accuracy. NCS is also modulated by a self-regulatory strategy. Transfer between separate neuromarkers of drug and food craving suggests shared neurobiological mechanisms.

Future studies could assess the discriminant and convergent validity of the NCS and test whether it responds to clinical interventions and predicts long-term clinical outcomes.

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