Neurotech Teams Seek to Tackle Common Addiction Disorders

by James Cavuoto, editor

October 2025 issue

Neurotech researchers and commercial firms have devised therapeutic approaches to treating a number of psychiatric disorders, such as major depression, OCD, and anxiety. More recently, some research teams have set their site on treating addiction, and one firm, Spark Biomedical, has obtained FDA clearance for its noninvasive Sparrow device to treat opioid use disorder.

But a more challenging and ubiquitous form of addiction involves substances that are legal and commercially available, namely tobacco and alcohol. A neuromodulation therapy to treat these two forms of addiction would benefit from a significantly larger market opportunity than opioid addiction.

In recent months, two research teams, one at Spark and the other at the Medical University of South Carolina, have reported progress in these two applications.

The MUSC team is using repetitive transcranial magnetic stimulation in an effort to promote smoking cessation. “We want to improve the effectiveness and specificity of rTMS and reduce side effects,” said study leader Xingbao Li, an associate professor in the department of psychiatry and behavioral sciences who has done extensive research on TMS. His team published its findings in the journal Brain Connectivity.

TMS is probably best known for its role in treating depression and obsessive-compulsive disorder. But the therapy has also been approved by the FDA for smoking. MUSC Health was the first place in South Carolina to offer TMS to smokers. Research has shown that multiple sessions of rTMS, specifically over the left dorsolateral prefrontal cortex of the brain, can cut cravings and cigarette consumption.

The new MUSC study gets even more targeted than that, using machine learning to analyze images from the brain’s neural networks to see if it’s possible to predict which smokers are likely to benefit from multiple sessions of rTMS.

To do that, the researchers used fMRI to detect changes in blood flow to measure brain activity. They looked at neural networks when participants were in a resting state, relaxed with their eyes closed, and when they were exposed to smoking photos. That analysis found that one neural network stood out: the salience network. It filters information to determine what’s salient, or important, to focus on. In the study, connectivity in the salience network was the best predictor of rTMS effectiveness.

“The study gives us a roadmap to extend personalized rTMS and build an fMRI and multimodal biomarker pipeline. The methods can be used for other substance use disorders as well,” Li said.

“Historic studies focus on the reward network in cigarette smokers,” he continued, referring to the parts of the brain involved in motivation and pleasure. “We were surprised to find that the salience network plays such a crucial role in smoking behavior. This makes it a mechanistic bridge between rTMS neuromodulation and successful smoking cessation.”

The researchers used machine learning to analyze data collected during an earlier MUSC study on TMS in smokers. In that study, the team recruited 42 people who wanted to quit smoking. They were split into two groups. One group got real TMS. The other got sham TMS. They all spent a minute-and-a-half before each TMS session interacting with things like cigarettes and ashtrays, then during the TMS, real or sham, watched videos of people smoking. There were 10 sessions per person over a two-week period.

In the end, the researchers found participants who got the real TMS “smoked significantly fewer cigarettes per day during the two-week treatment,” were more likely to quit by their target date and had lower cravings for tobacco.

Li said thanks to the fMRI scans that were also part of that work, the newer study was able to build on its findings. “Using machine learning to identify an individual’s dysfunctional brain network and then applying rTMS to the dysfunctional network, we can select who prefers to use rTMS or who prefers medicine to help them stop smoking.”

Li said their relatively small study lays the groundwork for larger studies to further explore targeted TMS for smokers. “This demonstrates that MUSC researchers can use novel and high-impact technology to move beyond fixed-target stimulation into precision neuromodulation.”

Meanwhile, Spark announced that it was awarded a $305,000 Phase I STTR grant from the National Institute on Alcohol Abuse and Alcoholism. The grant will support a study evaluating Spark’s proprietary transcutaneous auricular neurostimulation technology as a potential treatment to alleviate alcohol withdrawal symptoms in patients with alcohol use disorder. Conducted in partnership with leading research institutions, the study will assess both the safety and efficacy of the Sparrow Link device (Spark’s research platform) while exploring its impact on functional brain connectivity—marking an important step toward advancing noninvasive neuromodulation treatment for alcohol addiction care.

In this Phase I clinical study, Spark will collaborate with Menninger Clinic in Houston and Baylor College of Medicine, delivering tAN therapy to patients enrolled in a fiveday inpatient alcohol withdrawal protocol. To deepen the understanding of the neural mechanisms involved, the trial will track key clinical outcomes. These include alcohol withdrawal symptoms using the Clinical Institute Withdrawal Assessment for Alcohol; cumulative benzodiazepine medicine administered,; and the Penn Alcohol Craving Scale before and after the therapy. These measures will allow investigators to evaluate how tAN may support recovery and improve the overall AUD treatment.

Daniel Powell, Spark co-founder and CEO, stated: “As a company, our mission has always been to harness the power of neurostimulation to address some of the most urgent and underserved challenges in healthcare. Alcohol withdrawal is one of the most dangerous stages of addiction recovery, and patients deserve safer, more effective options. This grant validates the critical need for innovation in this space and underscores the trust NIH/NIAAA places in our technology and team. We’re honored to advance this study alongside such esteemed partners as Menninger Clinic and Baylor College of Medicine.”

Navid Khodaparast, Spark co-founder and CSO and study principal investigator added: “This study represents an important step in exploring how tAN therapy can be applied towards AUD treatment, and reshape the brain’s response during alcohol withdrawal. By measuring not only clinical outcomes but also changes in functional connectivity, we have the opportunity to better understand the mechanisms of recovery at a neural level.”

This alcohol withdrawal study adds another important dimension to Spark’s expanding application in overall neurological health and builds on prior NIH-funded research. Upon the successful completion of this study, Spark intends to broaden the use of tAN therapy beyond opioid withdrawal to also include alcohol withdrawal.