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Researchers have identified a specific pattern of brain activity that can distinguish people with cocaine use disorder from those without the condition. This brain activity pattern can also predict whether a person will respond well to a magnetic brain stimulation therapy designed to reduce cravings. The study detailing these results was published in Nature Mental Health.
Cocaine use disorder involves compulsive drug use and high rates of relapse. Current psychosocial treatments help some patients, but many people still struggle to recover. Medical professionals need objective biological markers to better diagnose the condition and develop targeted treatments.
To find these markers, researchers often look at the brain using functional magnetic resonance imaging. This technology measures blood flow in the brain to detect which areas are active at the same time. When different brain regions activate together while a person is resting, scientists consider them to be functionally connected.
Functional connectivity shows how different parts of the brain communicate to form complex networks. Previous imaging research has shown that cocaine addiction alters brain structure and task-related brain activity. However, observing the resting communication between brain networks can provide a more sensitive measure of brain dysfunction.
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Another emerging area of addiction research involves repetitive transcranial magnetic stimulation, often abbreviated as rTMS. This non-invasive therapy uses magnetic fields to stimulate specific areas of the brain. Clinical trials suggest it can help reduce cocaine cravings, but researchers do not entirely understand why it works for some people and not others.
Bioengineers Kanhao Zhao and Yu Zhang of Lehigh University led a team of researchers to explore these questions. They wanted to find a reliable brain connectivity pattern associated with cocaine use disorder. They also wanted to know if this biological marker could predict a patient’s response to magnetic stimulation therapy.
The researchers began by gathering brain imaging data from a discovery group of 129 people in Mexico. This group included 71 individuals with cocaine use disorder and 58 healthy controls. Participants underwent resting-state brain scans, lying still in the scanner without performing any specific tasks.
Using this data, the team mapped the functional connectivity across different brain regions for each participant. They fed this information into a machine learning algorithm. The computer program was tasked with finding connectivity patterns that could accurately separate the people who used cocaine from the healthy controls.
The algorithm successfully identified a distinct functional connectivity signature for cocaine use disorder. The model distinguished the two groups with an accuracy rate of 83 percent. The researchers noticed specific abnormalities in how different brain networks communicated with one another.
People with cocaine use disorder showed increased connectivity between networks involved in visual processing and attention. They also had elevated communication between networks that control goal-directed behavior and sensory attention. At the same time, the patients exhibited reduced connectivity between the brain’s default mode network, which handles internal thoughts, and the limbic network, which processes emotions.
To ensure these patterns were reliable, the researchers tested their algorithm on an independent replication group. This second dataset included 82 patients with cocaine use disorder and 81 healthy controls from different locations in the United States and Mexico. The mathematical model applied the previously learned brain signature to this new group of participants.
In the independent group, the algorithm accurately classified the participants with a 70 percent success rate. The specific brain connectivity differences observed in the first group were also present in the second group. This confirmed that the brain signature was a generalizable feature of cocaine addiction, rather than a fluke in the initial data.
Next, the research team investigated whether this diagnostic brain signature could predict treatment outcomes. They analyzed data from a small study involving 45 patients with cocaine use disorder who participated in a randomized clinical trial. In this trial, 25 patients received active magnetic brain stimulation, and 20 received a fake, or sham, version of the treatment.
The researchers looked at the baseline brain scans of these 45 patients before the therapy began. They isolated the specific functional connections that made up the cocaine use disorder signature. Then, they used another computer model to see if the strength of these connections could predict changes in the patients’ self-reported cocaine cravings after two weeks.
The model successfully predicted the reduction in cravings for patients who received the active magnetic stimulation. Patients with certain connectivity patterns in their frontal lobes were more likely to experience relief from their cravings. However, the model failed to predict outcomes for the patients in the sham group, showing that the brain signature was specifically linked to the actual treatment.
Finally, the researchers examined how the magnetic stimulation altered the patients’ brain connectivity over time. They compared the brain scans of patients before and after the two-week treatment period. They found that the active treatment helped normalize the communication between networks involved in cognitive control and physical movement.
The study relied on observational brain imaging, which means the results cannot prove that these brain connectivity patterns directly cause cocaine addiction. It is possible that prolonged cocaine use alters brain communication, or that pre-existing brain patterns make certain individuals more susceptible to addiction. Experimental therapies that directly manipulate these brain circuits are required to understand the exact direction of this relationship.
The participant groups in this research also included substantially more males than females. Illicit cocaine use is more common among males, but this demographic imbalance means the identified brain signature might not fully capture how the disorder presents in females. Brain dysfunction patterns could differ by sex, which future research should investigate.
Data for the independent replication group came from multiple different research sites. Differences in how functional magnetic resonance imaging scanners are calibrated or how data is collected across sites can introduce inconsistencies. Future studies will need standardized data collection methods and more diverse geographic participant pools to confirm the reliability of this brain signature.
Scientists hope to use these findings to improve targeted therapies for addiction. The connectivity patterns identified in this research could eventually serve as a screening tool in clinical settings. Doctors might one day scan a patient’s brain to determine if they are a good candidate for magnetic stimulation, or if alternative therapies would be more appropriate.
The study, “Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response,” was authored by Kanhao Zhao, Gregory A. Fonzo, Hua Xie, Desmond J. Oathes, Corey J. Keller, Nancy B. Carlisle, Amit Etkin, Eduardo A. Garza-Villarreal, and Yu Zhang.
