Nil Gurel - Coping with Trauma: Noninvasive Vagal Nerve Stimulation for Acute Stress and Its Real Time Biomarkers in PTSD

Description

Abstract: Exposure to traumatic events, from military combat to sexual assault, may generate strongly encoded intrusive memories. Trauma-related neuropathways have the opportunity to repeatedly activate in vulnerable individuals, and may eventually lead to posttraumatic stress disorder (PTSD) and autonomic imbalance associated with it. Electrical stimulation of the vagus nerve – the longest cranial nerve, which regulates the autonomic state – using an implantable device is a proven treatment method to address such imbalance. Noninvasive vagal nerve stimulation (nVNS) devices offer inexpensive and low-risk alternatives to surgical implants, but their effects on the physiology are not well understood. Real time, noninvasively obtained biomarkers are required to tailor therapy and to close the loop for automated delivery. In this talk, I will present my research on noninvasive sensing and neuromodulation with applications in stress, PTSD, and cardiovascular health monitoring. First, I will discuss how noninvasive sensing modalities could be instrumented and used in conjunction with signal processing and machine learning methods to quantify a person’s autonomic state. Second, I will present our mechanistic double-blind randomized clinical trial on the use of nVNS for dampening physiological arousal to acute stress in individuals with or without PTSD, with investigations in multiple dimensions: downstream physiological effects, brain imaging, and biochemical biomarkers. I will particularly focus on real time physiological biomarkers of nVNS and their potential for closing the loop for personalized neuromodulation and titration of therapy. Finally, I will advocate how these biomarkers could be instrumental in a machine learning guided neuromodulation scheme, applicable outside of clinical settings. Bio: Nil Gurel is a Ph.D. candidate in the School of Electrical and Computer Engineering at Georgia Institute of Technology. She works on noninvasive sensing and neuromodulation for stress and PTSD. She is particularly interested in the applications of physiological modulation, signal processing, and machine learning for mental health. She received her M.S. in Electrical and Computer Engineering from University of Maryland, College Park, MD where she was a Clark Fellow, and her B.S. in Electrical and Electronics Engineering from Bogazici University, Istanbul, Turkey. She is the recipient of Runner-up Best Paper Award from the 2018 IEEE Body Sensor Networks Conference, Best Paper Finalist Award from the 2018 IEEE Engineering in Medicine and Biology Conference, and Runner-up Best Poster Award from the 2019 IEEE Biomedical Health Informatics Conference. She was also named a Rising Star in EECS by MIT in 2018.