Two women stopped binge eating after their brains were stimulated with electricity

What if we told you that electric zaps to the brain stopped two women from binge eating?

Dr. Casey Halpern, a neurosurgeon at the University of Pennsylvania, told The New York Times that he and his colleagues decided to try deep brain stimulation on patients that had the common but underreported disorder.

As described in a paper in Nature Medicine, published in August, the trial followed the two patients, Robyn Baldwin, 58, and Lena Tolly, 48, for six months, during which the implanted device monitored activity in a brain region called nucleus accumbens which has been implicated in addiction.

Now, their binge eating isn't what is typically considered binging. The NYT reported that the patients' condition is in the Diagnostic and Statistical Manual of Mental Disorders, which involves binging multiple times a week, followed by feelings of losing control and feeling disgusted.

The researchers had previously used deep brain stimulation to calm the neurons in the nucleus accumbens of mice and were able to prevent the animals from binging.

But, would it work in humans?

The device stimulated the brain region, disrupting craving-related signals

Each woman was provided with a 5,000-calorie feast of their favorite foods when they weren't hungry. The women, who had described their 'specific emotional triggers' that could set off a binge, permitted the researchers to prompt them to binge with those triggers for the study's purpose, reported NYT.

The device which was used to record signals from and stimulate the brains of the mice is commercially available and approved for treating drug-resistant epilepsy. It is surgically placed beneath the scalp, with wires running through the skull to the nucleus accumbens in each hemisphere of the brain, as per the release.

As the women ate, the researchers recorded the electrical impulses in their nucleus accumbens. According to the release, whenever the device sensed nucleus accumbens signals that were found to predict food cravings in prior studies, it stimulated that brain region, disrupting the craving-related signals.

The women reported that whenever the devices were activated, they no longer felt like binging or the uncontrollable eating urge.

Over six months of treatment, both women reported far fewer binge episodes and lost weight. They're also eating differently.

"This was an early feasibility study in which we were primarily assessing safety, but certainly the robust clinical benefits these patients reported to us are really impressive and exciting," Halpern, study senior author, said in a statement.

The same treatment could be applied to other eating disorders

The women whose devices were implanted a year ago had the option to get their devices removed after 12 months. But both wanted to keep them as they no longer felt insatiable eating urges. They will be followed up for three years.

The researchers have begun enrolling new patients for a larger study. They noted that the same treatment could be applied to other loss-of-control-related disorders, including bulimia. The NYT stressed that before the treatment is approved by the Food and Drug Administration, researchers will need to test the method on at least 100 people in multiple medical centers.

Study Abstract:

Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.