Faculty member

Research Interests

  1. Computational modelling of neural networks, in particular neural mass modelling; use of these models to reveal principles of cognition and disease mechanisms
  2. Biophysical modelling of EEG and MEG, in particular source reconstruction, head modelling and connectivity analysis, as well as application to neuroscientific and clinical questions
  3. Reconstruction of fiber connections with diffusion MRI, in particular in connection with the identification of microstructural properties (e.g., axonal diameters).

Available PhD projects

  1. Modeling the neural mechanisms of cognition and disease: We are using neural mass models to investigate the neural circuits underlying various aspects of cognition and disease. The goal is a mechanistic understanding of these processes, rather a mere localization, and the generation of experimental predictions that can be tested. Accordingly, projects in this area involve mathematical modeling, theoretical understanding of neurobiology and brain imaging experiments (e.g., MRI, EEG and MEG). Currently, PhD projects are available in the areas of language processing and Parkinson’s disease, as well as on the fundamental relationship between cortical wiring patterns, neural dynamics, and the building blocks of cognition.
  2. Reconstruction of functional connectivity from EEG and MEG data: Reconstruction of functional connectivity from extracranial measurements is a special challenge. We are seeking PhD students for conducting research on sophisticated approaches that integrate source reconstruction and connectivity estimation.
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