Research

Development of neural mass models to account for observed neurophysiological phenomena (e.g., resonance, spontaneous and evoked activities, auditory habituation) and explain cognitive functions (e.g., stimulus gating/priming, working memory, regularity formation, and change detection).  

Determining the electrical conductivity and permittivity of healthy and tumorous brain tissues through intracranial measurements in patients.  

Exploration of the spatial and pathological origins of abnormal beta-gamma phase-amplitude coupling and the impact of dopamine deficiency on brain activity during both resting state and voluntary motor activity of Parkinson patients compared with healthy subjects.  

Development of highly accurate localization and mapping strategies using transcranial magnetic stimulation, which can be used in the field of preoperative planning of brain tumor surgery.  

Investigation of  parameter uncertainties and sensitivities in computational models in the field of neuroscience.  

Explanation of features of Parkinsonian neural dynamics via mechanistic descriptions of phase transitions in computational models of basal ganglia interactions.  

For high precision in source reconstruction of magnetoencephalography (MEG) data, a high accuracy of the coregistration of sources and sensors is mandatory, because the numerical model of the head is derived from a different modality, namely magnetic resonance imaging (MRI).  

Development of mathematical models relating white matter microstructure to axonal signal transmission delays between different brain areas.