The Autonomic Nervous System (ANS) regulates the function of internal organs such as the heart. Experimental and clinical evidences suggest an important participation of the ANS in cardiac arrhythmias. However, the bases for such participation are mainly speculative, which hampers the design of more efficient anti-arrhythmic therapies. In this project we specifically aim at unraveling the ANS participation in arrhythmias related to cardiac diseases such as genetic Long QT syndrome, ischemia and atrial fibrillation and to conditions associated with increased cardiac risk due to competitive sport, microgravity exposure or cardiovascular aging. A methodological framework is set up that will combine processing of biological signals and development of computational models of ANS-heart electrophysiology. Analyzed biological signals will include patch-clamp recordings of ionic currents, action potentials of cell and tissue preparations, intracavitary pressures, electrograms and electrocardiograms. Stochastic computational models will be built to represent variability in human cardiac electrophysiology and ANS regulation. Model development and calibration, in healthy and diseased hearts, will be based on the results of the processed signals.