For more than a decade, UC San Francisco (UCSF) physician-scientists have worked to advance deep brain stimulation (DBS), a technique that delivers targeted electrical currents to the brain through implanted electrodes. Supported by funding from the National Institutes of Health (NIH) Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative, UCSF researchers have made progress in developing personalized DBS that responds in real time to patients’ unique neurological activity.
Traditionally, continuous DBS has been used to treat movement disorders such as Parkinson’s disease. However, this approach has not always kept up with patients’ changing symptoms and has shown limited effectiveness for other conditions.
Professors Philip Starr, MD, PhD, and Edward Chang, MD, at UCSF have led efforts to develop a new generation of DBS technology. Their work enables devices to deliver electrical stimulation only when abnormal brain activity associated with symptoms is detected—activity that varies between individuals.
Shawn Connolly, diagnosed with Parkinson’s disease at age 39, participated in a clinical trial of this self-adjusting DBS system. The device uses an algorithm developed by Starr and Simon Little, MBBS, PhD, which recognizes brain signals indicating symptom onset and administers targeted stimulation accordingly. In February, the Food and Drug Administration approved two adaptive DBS algorithms based on this research.
“It’s definitely changed my life,” Connolly said in 2024. “I can just go through the whole day feeling good.”
Starr and Chang’s advancements in brain mapping have also contributed to research into less invasive methods for achieving personalized DBS outcomes without surgery. Their early adoption of electrocorticography allowed for multi-site recording of brain signals in Parkinson’s patients as early as 2013.
Beyond movement disorders, UCSF scientists are investigating personalized DBS applications for chronic pain. Early attempts at continuous DBS for chronic pain often failed over time as the brain adapted to constant stimulation. In 2023, Prasad Shirvalkar, MD, PhD identified individual pain biomarkers by correlating patient pain logs with recorded brain activity using artificial intelligence. This development enabled clinical trials of responsive DBS systems that activate only when pain markers are detected.
Personalized DBS is also being studied as a treatment for severe depression resistant to conventional therapies. Sarah, a participant in one such trial led by Chang’s team at UCSF in 2020, received a custom-fitted device that responded to her specific patterns of depressive brain activity.
“I was at the end of the line. I was severely depressed. I could not see myself continuing … if I could never move beyond this,” she said in 2021. “It was not a life worth living.” After receiving personalized stimulation: “In the early few months, the lessening of the depression was so abrupt, and I wasn’t sure if it would last,” she remembered. “But it has lasted. And I’ve come to realize that the device really augments the therapy and self-care I’ve learned while being a patient here at UCSF.” She added: “Those thoughts still come up, but it’s just … poof … the cycle stops.”
Andrew D. Krystal, MD, PhD is currently leading federally-funded trials on using DBS for depression with potential broader application if successful.
At present, NIH funding allows UCSF to be among roughly twelve U.S. hospitals offering continuous DBS as psychiatric care for obsessive-compulsive disorder (OCD), reserved for severe cases due to Food and Drug Administration restrictions. Andrew Moses Lee, MD, PhD directs UCSF’s OCD Program and leads ongoing trials aiming to identify OCD-related biomarkers suitable for future personalized DBS treatments.
Chang expressed optimism about extending tailored neural signature-based treatments across various conditions: “Tailoring these treatments to the person’s neural signature is really the key that allows DBS to be effective across many conditions,” he said.
Research continues into expanding these techniques for addiction disorders and neurodegenerative diseases such as Alzheimer’s.
