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"Brain Data Could Read Moods, Potentially Treat Depression" - Daniela Hernandez

  • The Wall Street Journal
  • New York, NY
  • (September 10, 2018)

Can mood be decoded from brain data? The work is part of a larger movement aimed at developing better, more personalized therapies for psychiatric conditions like depression, anxiety, post-traumatic stress disorder and obsessive compulsive disorder used for deep brain simulation, a procedure that requires surgery and is highly invasive. The approach is similar to treatments already in use for movement disorders like Parkinson’s disease and epilepsy. While DBS is meant for patients with severe mental health issues for whom other lines of treatment haven’t worked, what clinicians learn from its use could also improve our overall understanding of disease and, in the future, health care for people with less severe disease, scientists said. The new algorithm is a step toward reading and decoding mood-related brain activity reliably—a prerequisite for delivering more personalized care in the future. “It sets the stage to think about how you move that mood around,” said Helen Mayberg, MD, director for the Center for Advanced Circuit Therapeutics at the Icahn School of Medicine at Mount Sinai, who wasn’t involved in the study.

- Helen Mayberg, MD, Senior Faculty, Neurosurgery, Neurology, Psychiatry, Neuroscience, Icahn School of Medicine at Mount Sinai, Director, The Center for Advanced Circuit Therapeutics, Mount Sinai Health System

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