Their study, published in Nature Biotechnology, is a significant step towards creating new closed-loop therapies that use brain stimulation to treat debilitating mood and anxiety disorders in millions of patients who are not responsive to current treatments.
Assistant Professor and Viterbi Early Career Chair Maryam Shanechi of the Ming Hsieh Department of Electrical Engineering and the Neuroscience Graduate Program at USC led the development of the decoding technology, and Professor of Neurological Surgery Edward Chang at UCSF led the human implantation and data collection effort. The researchers were supporting the Defense Advanced Research Projects Agency's SUBNETS program to develop new biomedical technologies for treating intractable neurological diseases.
Team - Volunteers - Group - Epilepsy - Patients
The team recruited seven human volunteers among a group of epilepsy patients who already had intracranial electrodes inserted in their brain for standard clinical monitoring to locate their seizures. Large-scale brain signals were recorded from these electrodes in the volunteers across multiple days at UCSF, while they also intermittently reported their moods using a questionnaire. Shanechi and her students, Omid Sani and Yuxiao Yang, used that data to develop a novel decoding technology that could predict mood variations over time from the brain signals in each human subject, a goal unachievable to date.
"Mood is represented across multiple sites in the brain rather than localized regions, thus decoding mood presents a unique computational challenge," Shanechi said. "This challenge is made more difficult by the fact that we don't have a full understanding of how these regions coordinate their activity to encode mood and that mood is inherently difficult to assess. To solve this challenge, we needed to develop new decoding methodologies that incorporate neural signals from distributed brain sites while dealing with infrequent opportunities to measure moods."
Decoder - Shanechi - Team - Researchers - Brain
To build the decoder, Shanechi and the team of researchers analyzed brain signals that were recorded from intracranial electrodes in...
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