Newswise—New Haven, Connecticut— Craving is known to be a key factor in substance use disorders and can increase the likelihood of future drug use or relapse. However, its neural basis, or how the brain gives rise to desire, is not well understood.
In a new study, researchers from Yale, Dartmouth and the French National Center for Scientific Research (CNRS) have identified a stable brain pattern, or neuromarker, for the desire to consume drugs and food. Their findings were published December 19 in Nature Neuroscience.
The discovery may 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 say. 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 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 benefits of having a stable biological indicator for a disease is that you can then test anyone and tell whether or not they have that disease,” said Hedy Kober, an associate professor of psychiatry at Yale School of Medicine. and a study author. “And we don’t have that for psychopathology and certainly not for addiction.”
To determine whether such a marker could be set for desire, Kober and his colleagues, CRNS’s Leonie Koban and Dartmouth College’s Tor Wager, used a machine learning algorithm. His idea was that if many people experiencing similar levels of desire shared a pattern of brain activity, then a machine learning algorithm could detect that pattern and use it to predict desire levels based on brain imaging.
For the study, they used functional magnetic resonance imaging (fMRI) data, which provides insights into brain activity, and self-reported craving assessments from 99 people to train and test the machine learning algorithm. The fMRI data was collected while people, who identified themselves as drug users or non-users, viewed images of drugs and very tasty food. The participants then rated how strongly they wanted the items they saw.
The algorithm identified a pattern of brain activity that could be used to predict the intensity of drug and food cravings from functional magnetic resonance imaging alone, the researchers said. The pattern they observed, which they dubbed the “Neurobiological Desire Signature (NCS),” includes activity in several areas of the brain, some of which previous studies have linked to substance use and craving. However, the NCS also provides a new level of detail, showing how neural activity within subregions of these brain areas can predict desire.
“It gives us a really granular understanding of how these regions interact and predict the subjective experience of desire,” Kober said.
The NCS also revealed that brain 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 differentiate drug users from non-users based on their brain responses to drug cues, but not food cues.
“And these findings are not substance-specific because we included participants who used cocaine, alcohol, and cigarettes, and the NCS predicts craving in all of them,” Kober said. “So it’s really a biomarker for craving and addiction. There’s something common to all of these substance use disorders that is captured in a moment of desire.”
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 looking at here is probably not a blanket signing for ‘bounty,'” he said, “but something more selective for food and drug cravings.”
In addition, the NCS also offers a novel brain target to better understand how context or emotional states can influence the desire for food and drugs. “For example,” Koban said, “we can use the NCS in future studies to measure how stress or negative emotions increase the need 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 is likely in a few years. Now she, along with her team and her collaborators, are working to understand this network of brain regions more deeply and see if the NCS can predict how people with substance use disorders will respond to treatment.
That, he said, would make this neuromarker a powerful tool to inform treatment strategies.
“Our hope,” Kober said, “is that the brain, and specifically the NCS as a stable biological indicator, will allow us to not only identify who has a substance use disorder and understand the variation in outcomes across individuals, but also who will respond to particular treatments.”
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