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

 

  • Cortical microcircuits, language, and global connectivity: The overarching goal is to understand cognition the mechanistic way and to establish a model of the brain that is detailed and realistic enough to truly constrain cognitive theory. The specific cognitive focus is on the specific human language abilities, while biologically, we are especially interested in whole-brain modeling and the role of long-range connectivity.

 

  • Detection of subcortical neural activity with EEG or MEG: The goal is to develop methods to identify causal relationships between (i) cortical stimulation, (ii) cortical activity reconstructed from EEG by classical methods, and (iii) subcortical activity as reconstructed from EEG by to-be-developed methods based on biophysical models fitted to simultaneous cortical and subcortical recordings.

 

  • Identification of cortical networks using transcranial magnetic stimulation (TMS): The goal is to develop methods to identify the causal interactions and information flow in networks of cortical neural populations during cognitive tasks by fusing multi-focal stimulation by TMS, neural mass modeling, and electroencephalography.

 

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