For the analysis of causal relationships between time series of different biological (subs)systems already exist different methods, which have been developed in the theoretical framework of linear processes and nonlinear dynamics. Not only in economics, natural sciences and biology, but especially in medicine, the question is increasingly raised whether causal relationships exist between different biosignals (cardiorespiratory-, cardiovascular-, central-autonomic systems) and whether they are detectable and quantifiable. In detail, however, there are still large gaps in our knowledge, especially in elucidating the functional significance of the observed effects (system properties). The approach to determining causality states that the prediction of one time series can be improved by incorporating information from another (past and present determine future and not vice versa). The concept of Granger causality is one of others enabling the description of causal dependencies between different time series. Systems as diverse as clocks, cardiac pacemakers, firing neurons, adjustment of heart rate with respiration and/or locomotory rhythms exhibit a tendency to operate in synchrony. In general, the adjustment of oscillatory rhythms due to an interaction is the essence of synchronization. Investigation of synchronization in large ensembles of neurons becomes an important part and central issue in neuroscience. Synchronization seems to be a central mechanism for neuronal information processing within a brain area as well as for communication between different brain areas.
- Student: Engineering, medical engineering, medical information processing, medicine, psychology or equivalent
- Interest in issues of Network Physiology, electrophysiology, biosignal analysis
- Motivation to work intensively on the issues described above
- Good knowledge of English (with regard to dealing with international literature)
- Knowledge of and interest in scientific work
- Experience in measuring electrophysiological data (EEG, ECG, ...) is an advantage
What we offer:
The aim of this work focuses on the disease-specific description of synchronization effects and/or causal couplings between the autonomic and the central nerve systems in patients suffering from fatigue, burnout and depression. In particular, we will find, select and implement (MatLab) suitable algorithms in the literature that enable and quantitatively describe the synchronization and/or the couplings between heart rate, blood pressure, pulse, respiration and central activity (EEG). In this thesis a method comparison of different approaches applied to simulated datasets and real patient datasets has to be performed. Finally, a new methodological approach will be derived to describe and quantify synchronization and/or causal relationships of and between different biological systems in fatigue, burnout and depression. This includes a comprehensive literature research, the execution of electrophysiological measurements, the collection of questionnaires as well as the systematic evaluation and publication of the data. The content and technical supervision will take place in the working group. There is the possibility to combine the position with a research internship.
How to apply:
Dipl.-Ing. Steffen Schulz
AG IMO, FB Analysis and Processing of Biomedical Signals and Information
Charité - Universitätsmedizin Berlin, CC17, Augustenburger Platz 1, 13353 Berlin