Development of advanced multivariate analysis tools for characterizing network physiology

Advanced multivariate analysis tools for characterizing interactions among brain-brain and brain-body rhythms will be developed based on available multichannel and multimodal physiological datasets, including, e.g., electroencephalogram (EEG), electrocardiogram (ECG), respiratory, and electrogastrogram (EGG) signals. The focus will be on the development of novel algorithmic tools that acknowledge both the systemic and dynamic (i.e., time-changing) nature of the interactions between physiological subsystems to achieve a more complete characterization of the physiological network. The project will tackle the assessment and quantification of temporal directionality changes of coupling effects (e.g., respiration driving changes in heart rate or vice versa), multi-scale behavior, and possible nonlinear interactions between the physiological subsystems to achieve a more complete characterization of systemic network physiology (i.e., dynamic interactions among brain- brain and brain-body rhythms).