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A new method of interpreting brain activity could potentially be used in clinics to help determine the best treatment options for depression, according to a study led by researchers at the Stanford School of Medicine.
Stanford researchers and their collaborators used electroencephalography, a tool for monitoring electrical activity in the brain, and an algorithm to identify a brain-wave signature in individuals with depression who will most likely respond to sertraline, an antidepressant marketed as Zoloft.
The paper co-authors include Molly Lucas, a 2016 Stanford Graduate Fellow, and Camarin Rolle, a 2015 SGF and 2017-18 SPICE funding recipient.
