Faculty member

Research Interests

• Computational modelling of brain networks, neural mass modelling
• Biophysical modelling of EEG/MEG, in particular source reconstruction
• Modelling 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.
• TMS target localization and targeting: Recently, our group has developed a set of powerful methods to localize the neural populations underlying TMS induced effects (Weise et al., NeuroImage 2020; Numssen et al., NeuroImage 2021). The task is to develop these methods into usable tools that help to lift non-invasive cortical mapping in research and clinics to a new level.