The Brain Networks group currently works on projects about modeling of neuronal circuits in the brain, analysis of EEG and MEG data in different contexts, modeling of non-invasive brain stimulation, and new measurement techniques.

Development of mathematical models relating white matter microstructure to axonal signal transmission delays between different brain areas. [more]
Explanation of features of Parkinsonian neural dynamics via mechanistic descriptions of phase transitions in computational models of basal ganglia interactions. [more]
Determining the electrical conductivity and permittivity of healthy and tumorous brain tissues through intracranial measurements in patients. [more]
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). [more]
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). [more]
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. [more]
Investigation of  parameter uncertainties and sensitivities in computational models in the field of neuroscience. [more]
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. [more]
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