Our group focuses on understanding the principles of complex dynamics of biological systems at the cell, tissue and organ level and their application in medicine.
Life-threatening cardiac rhythm disorders such as ventricular fibrillation are associated with complex, self-organizing spatio-temporal electromechanical excitation of the heart. We are developing novel cardiac imaging techniques, numerical simulations and machine learning methods to understand and efficiently control the dynamics of electromechanical waves in the heart muscle (Nature 2018, 2011).
Our translational research group is affiliated with the Max Planck Institute for Dynamics and Self-Organization, the University Medical Center Göttingen and the German Center for Cardiovascular Research (DZHK).
Additional Information CaosDB is an open source research data management system developed at the research group biomedical physics. It …
Machine learning tasks in cardiac research include: data classification (e.g., time series, images, evolution of patterns and shapes) …
Project Information Project Title: Global Carbon Cycling and Complex Molecular Patterns in Aquatic Systems: Integrated Analyses …
Self-organized complex spatial-temporal dynamics underlies dynamic physiological and pathological states in excitable biological …
The electrocardiogram (ECG) provides a noninvasive transthoracic interpretation of the electrical activity of the heart. Cardiovascular …
The mechanism underlying the recruitment of wave emission from heterogeneities in electrical conductance is shown in Fig. 1A. In the …
This project aims at characterizing a multiple spiral wave system from a large-scale perspective. Our goal was to develop improved …
Spatiotemporally chaotic wave dynamics underlie a variety of debilitating crises in extended excitable systems including the heart. …
The development of detailed physiological models of the heart, the availability of large quantities of high-quality structural and …
During cardiac fibrillation, the coherent mechanical contraction of the heart is disrupted by vortex-like rotating waves or scroll …
Physiological cardiac modeling requires detailed structural, functional, and dynamical characterization of the heart. The MPRG …
The measurement of electro-mechanical waves in cardiac tissue remains a major experimental challenge. Conventional fluorescence imaging …
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide affecting an estimated 5.5 million people worldwide. …
We are using mathematical models of cardiac tissue with various levels of complexity, ranging from generic to detailed physiological …
In the heart, electrical excitation propagates through diffusively coupled cardiac cells and subsequently results in contraction and …
Two important questions in the investigation of cardiac arrhythmias are how these activation patterns develop and how their complexity …
While physical models often can be derived from first principles, they may contain parameters whose values are not or only partially …
An important approach for analyzing spatially extended systems is “network analysis” (also called graphical methods) where time series …
Characterization and classification of cardiac dynamics on the basis of measured time series (e.g. electrocardiogram, ECG) is crucial …
While FF-AFP provides remarkable energy reduction compared to conventional therapeutic approaches, the underlying mechanisms remain …