Dr Mohammed Sendi of Assistant Neuroscientist at McLean Hospital and an Instructor in Psychiatry at Harvard Medical School.

Brain stimulation shows significant potential in treating neurological disorders, but the challenge lies in personalizing these therapies effectively. Traditionally, identifying the optimal stimulation parameters, such as amplitude, frequency, and pulse width, requires extensive trial-and-error testing, which is both time-consuming and costly. To streamline this process, we developed an active learning framework that efficiently identifies the most effective relationships between stimulation parameters and brain responses, reducing the need for numerous experiments. We conducted three types of validation for our framework: in silico experiments using synthetic data from a Parkinson’s disease model, in silico tests with real data from a non-human primate model, and in vivo tests through real-time optogenetic stimulation in rats. In each scenario, our active learning models demonstrated superior performance over traditional random sampling methods, achieving significantly lower errors in predicting brain responses. This innovative approach enhances the efficiency and efficacy of research and clinical applications in brain stimulation, offering a more cost-effective pathway to developing personalized therapies for neurological disorders.

Biography:

Mohammad Sendi, PhD, is an Assistant Neuroscientist at McLean Hospital and an Instructor in Psychiatry at Harvard Medical School. Renowned for his groundbreaking research on neuroimaging biomarkers for PTSD and depression, Dr. Sendi holds dual Ph.D. degrees in Biomedical Engineering and Electrical and Computer Engineering from Georgia Tech and Emory University. His innovative work integrates functional MRI (fMRI), structural MRI (sMRI), and genetic data to refine neuropsychiatric treatments. Dr. Sendi has pioneered machine learning models to identify biomarkers from brain network dynamics, significantly advancing the field. His pivotal research on deep brain stimulation (DBS) in depression, which has been featured in Science Magazine, holds promise for revolutionizing DBS therapies. At McLean and Harvard, his focus on dynamic functional network connectivity and polygenic risk scores aims to predict PTSD severity and enhance personalized treatment paradigms in neuropsychiatry. Dr. Sendi is also a Senior Member of IEEE and an active member of several prestigious organizations, including the Anxiety & Depression Association of America, the Society of Biological Psychiatry, the Society for Neuroscience, and the International Society for Magnetic Resonance in Medicine.

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