Summary: Researchers have identified neural biomarkers associated with food and drug cravings. The findings could help pave the way for new treatments for addiction.
Craving is known to be an important factor in substance use disorders and may increase the likelihood of future drug use or relapse. Yet its neural basis – or how the brain causes cravings – is not fully understood.
In a new study, researchers from Yale, Dartmouth and the French National Center for Scientific Research (CNRS) have identified a stable brain model, or neuromarker, for drug and food cravings. Their findings have been published Nature Neuroscience.
The researchers say the discovery could be an important step toward understanding the brain basis of craving, addiction as a brain disorder, and how addiction can be better treated in the future. More importantly, this neuromarker can also be used to distinguish drug users from non-users, making it not only a neuromarker for craving but also a potential neuromarker that could one day be used in the diagnosis of substance use disorders.
For many diseases, there are biomarkers that doctors can use to diagnose and treat patients. For example, to diagnose diabetes, doctors test for a blood marker called A1C.
“One benefit of having a fixed biomarker for a disease is that you can then administer the test to any person and tell them if they have that disease,” said Hedy Kober, MD, professor of psychiatry at Yale School of Medicine. and the author of the study. “And we don’t have that for psychopathology, and we certainly don’t have that for addiction.”
Kober and his colleagues – Leonie Koban of CRNS and Tor Wager of Dartmouth College – used a machine learning algorithm to determine whether such a marker for craving could be generated. Their idea was that if many people with similar levels of craving shared the same pattern of brain activity, a machine learning algorithm could detect this pattern and use it to predict their craving levels based on brain images.
For the study, they used functional magnetic resonance imaging (fMRI) data, which provides insight into brain activity, and self-reported assessments of craving from 99 people to train and test the machine learning algorithm.
fMRI data were collected when individuals who identified themselves as drug users or non-users viewed images of drugs and highly palatable foods. Participants then rated how strongly they craved the items they saw.
The algorithm identifies a pattern of brain activity that can be used to estimate the intensity of drug and food cravings from fMRI images alone, the researchers said.
The pattern they observed, which they called the “Neurobiological Craving Signature (NCS),” includes activity in various brain regions that some previous studies have linked to substance use and craving.
However, the NCS also provides a new level of detail in how neural activity in subregions of these brain areas can predict craving.
“It gives us a really detailed understanding of how these regions interact with and predict the subjective craving experience,” Kober said.
The NCS also revealed that brain responses to both drug and food cues were similar; This suggested that drug cravings originate in the same nervous systems that generate food cravings. More importantly, the marker was able to distinguish drug users from nonusers based on brain responses to drug cues, but not food cues.
“And these findings are not specific to a single substance 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. All of these substance use disorders have something in common that is caught in a 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 generic signature for ‘reward,'” he said, “something more selective for craving food and drugs.”
Additionally, the NCS offers a new brain target to better understand how food and drug cravings can be influenced by context or emotional states. “For example,” said Koban, “we can use the NCS in future studies to measure how stress or negative emotions increase the urge to use drugs or eat our favorite chocolate.”
Kober notes that while NCS is promising, it needs further validation and is not yet ready for clinical use. That’s probably a few years down the road. He is now working with his team and collaborators to understand this network of brain regions more deeply and to see if the NCS can predict how those with substance use disorders will respond to treatment.
He said this would make this neuromarker a powerful tool for informing treatment strategies.
“Our hope,” Kober said, “is that the brain, and especially the NCS as a stable biological marker, will allow us to not only identify who has a substance use disorder and understand the difference in people’s outcomes, but also understand who has a substance use disorder.” will respond to certain treatments.”
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“A neuromarker for drug and food cravings distinguishes drug users from nonusers” by Hedy Kober et al. Nature Neuroscience
A neuromarker for drug and food cravings distinguishes drug users from nonusers
Craving is a core feature of substance use disorders. It is a strong indicator of substance use and relapse and is linked to overeating, gambling, and other maladaptive behaviors.
Craving is measured through introspective access and self-report that is limited to sociocultural contexts. Neurobiological markers of craving are both necessary and deficient, and it remains unclear whether craving for drugs and food involves similar mechanisms.
In three functional magnetic resonance imaging studies (n= 99), we used machine learning to identify a cross-validated neuromarker that predicts the self-reported intensity of cue-induced drug and food craving (P< 0.0002).
This pattern, which we call the Neurobiological Craving Signature (NCS), includes the ventromedial prefrontal and cingulate cortices, the ventral striatum, the temporal/parietal junction areas, the mediodorsal thalamus, and the cerebellum.
More importantly, NCS responses to drug versus food cues distinguish drug users and non-users with 82% accuracy. NCS is also modulated by a self-regulation strategy. The transfer between separate neuromarkers for drug and food cravings suggests shared neurobiological mechanisms.
Future studies can evaluate the discriminant and convergent validity of the NCS and test whether it responds to clinical interventions and predicts long-term clinical outcomes.