Newly identified neuromarker reveals clues to drug and food cravings
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 gives rise to craving – is not well understood.
In a new study, researchers from Yale, Dartmouth and the National Center for Scientific Research (CNRS) have identified a stable brain pattern, or neuromarker, for craving for drugs and food. Their findings were published Dec. 19 in Nature Neuroscience.
The finding 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 say. Importantly, this neuromarker can also be used to differentiate addicts from non-addicts, making it not only a neuromarker of craving, but also a potential neuromarker that could one day be used in diagnosis. 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 for a blood marker called A1C.
“One of the benefits of having a stable biological indicator for a disease is that you can then test anybody and say they have or don’t have that disease,” said Hedy Kober, associate professor of psychiatry at the Yale School of Medicine. and author of the study. “And we don’t have that for psychopathology and certainly not for addiction. »
To determine if such a marker could be established for craving, Kober and his colleagues – Leonie Koban of CRNS and Tor Wager of Dartmouth College – used a machine learning algorithm. Their idea was that if many people experiencing similar levels of thirst share a pattern of brain activity, then a machine learning algorithm might be able to detect that pattern and use it to predict thirst levels based on brain images.
For the study, they used functional magnetic resonance imaging (fMRI) data – which offers insight into brain activity – and self-reported ratings of cravings from 99 people to train and test the machine learning algorithm. The fMRI data was collected while the individuals – who self-identified as drug users or non-users – viewed images of highly palatable drugs and foods. Participants then rated how much they crave the items they saw.
The algorithm identified a pattern of brain activity that could be used to predict craving intensity for drugs and food from fMRI images alone, the researchers said. The pattern they observed – which they dubbed “Neurobiological Craving 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 in subregions of these brain areas can predict craving.
“It gives us a really granular understanding of how these regions interact with and predict the subjective experience of craving,” Kober said.
The NCS also revealed that brain responses to drug and food cues were similar, suggesting that drug craving stems from the same neural systems that generate food cravings. Importantly, the marker was able to differentiate drug users from nonusers based on their brain responses to drug cues, but not food cues.
“And these results are not substance-specific because we included participants who used cocaine, alcohol, and cigarettes, and the NCS predicts craving for each of them,” said Kober. “So it’s really a biomarker for craving and addiction. There’s something common to all of these substance use disorders that’s captured in a moment of craving. »
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 signature for ‘reward,'” he said, “but something more selective for the need for food and drugs. »
In addition, the NCS also offers a new brain target to better understand how craving for food and drugs can be influenced by context or emotional states. “For example,” Koban 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 shows promise, it still needs to be validated and is not yet ready for clinical use. It’s probably in a few years. Now she – along with her team and collaborators – is 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.
This, she 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, may allow us not only to identify who has substance use disorder and to understand the variance in people’s outcomes, but also who will respond to particular treatments. »
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