In June 2015, biology professor Colleen Hanlon went to a conference on drug dependence. As she met other researchers and wandered around a glitzy Phoenix resort's conference rooms to learn about the latest work on therapies for drug and alcohol use disorders, she realized that out of the 730 posters, there were only two on brain stimulation as a potential treatment for addiction — both from her own lab at Wake Forest School of Medicine.
Just four years later, she would lead 76 researchers on four continents in writing a consensus article about brain stimulation as an innovative tool for addiction. And in 2020, the Food and Drug Administration approved a transcranial magnetic stimulation (TMS) device to help patients quit smoking, a milestone for substance use disorders.
Brain stimulation is booming. Hanlon can attend entire conferences devoted to the study of what electrical currents do to the intricate networks of highways and backroads that make up the brain's circuitry. This expanding field of research is slowly revealing truths of the brain: how it works, how it malfunctions, and how electrical impulses, precisely targeted and controlled, might be used to treat psychiatric and neurological disorders.
In the last half-dozen years, researchers have launched investigations into how different forms of neuromodulation affect addiction, depression, loss-of-control eating, tremor, chronic pain, obsessive compulsive disorder, Parkinson's disease, epilepsy, and more. Early studies have shown subtle electrical jolts to certain brain regions could disrupt circuit abnormalities — the miscommunications — that are thought to underlie many brain diseases, and help ease symptoms that persist despite conventional treatments.
The National Institutes of Health's massive BRAIN Initiative put circuits front and center, distributing $2.4 billion to researchers since 2013 to devise and use new tools to observe interactions between brain cells and circuits. That, in turn, has kindled interest from the private sector. Among the advances that have enhanced our understanding of how distant parts of the brain talk with one another are new imaging technology and the use of machine learning to interpret complex brain signals and analyze what happens when circuits go haywire.
Still, the field is in its infancy, and even therapies that have been approved for use in patients with, for example, Parkinson's disease or
