척수신경자극을 통한 혈역학 관련 신경 집단 내 상호작용 모델링

Abstract

Neuromodulation offers a non-pharmacological approach to neural regulation, particularly significant for conditions requiring sustained treatment. With FDA-approved methods like Vagus nerve stimulation (VNS) and Deep brain stimulation (DBS), specific neural clusters can be targeted to treat various diseases. The advent of closed-loop stimulation allows personalized protocols based on patient biomarkers, enhancing treatment efficacy and safety. This study aimed to develop an effective neuromodulation method for blood pressure regulation using digital biomarkers. Specifically, the research focuses on developing neuromodulation methods for blood pressure regulation by investigating spinal Intermediolateral nucleus (IML) stimulation. Through animal experiments and digital modeling, the study analyzed the interaction between IML neural activity and hemodynamics, accurately predicting blood pressure changes. The study revealed heterogeneous neuron responses to stimulation, emphasizing collective dynamics over individual neuron reactions. Through Principal Component Analysis (PCA), dimensionality reduction techniques, a ring-shaped manifold with high correlation to blood pressure was identified, achieving over 70% accuracy in blood pressure estimation. This research paves the way for a digital biomarker for continuous control of complex neural networks, enhancing the precision of neuromodulation therapies