A team of leading clinicians, engineers, and neuroscientists has made a groundbreaking discovery in the field of treatment-resistant depression. By analyzing the brain activity of patients undergoing deep brain stimulation (DBS), a promising therapy involving implanted electrodes that stimulate the brain, the researchers identified a unique pattern in brain activity that reflects the recovery process in patients with treatment-resistant depression. This pattern, known as a biomarker, serves as a measurable indicator of disease recovery and represents a significant advance in treatment for the most severe and untreatable forms of depression.
on September 20, offer the first window into the intricate workings and mechanistic effects of DBS on the brain during treatment for severe depression.
The research team, which includes experts from the Georgia Institute of Technology, the Icahn School of Medicine at Mount Sinai, and Emory University School of Medicine, used artificial intelligence to detect shifts in brain activity that coincided with patients' recovery. Helen S. Mayberg, MD, co-senior author of the study, led the first experimental trial of subcallosal cingulate cortex DBS for treatment-resistant depression patients in 2003, demonstrating that it could have clinical benefit. In 2019, she and the Emory team reported the technique had a sustained and robust antidepressant effect with ongoing treatment over many years for previously treatment-resistant patients.
The team's research also confirmed a longstanding subjective observation by psychiatrists: as patients' brains change and their depression eases, their facial expressions also change. The team's AI tools identified patterns in individual facial expressions that corresponded with the transition from a state of illness to stable recovery. These patterns proved more reliable than current clinical rating scales.
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