Computational modelling of brain networks, neural mass modelling.
Biophysical modelling of EEG/MEG, in particular source reconstruction.
Modeling and analysis of non-invasive brain stimulation.
Neurocognition of language and music.
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.