Diffusion Magnetic Resonance Imaging; Functional Magnetic Resonance; Models, Statistical; Phantoms, Imaging; Transcranial Magnetic Stimulation; Ultrahigh field MRI
My main research focus is to improve and optimise current methods in various topics related to neuroimaging, especially functional magnetic resonance imaging (fMRI) and diffusion magnetic resonance imaging (dMRI) and transcranial magnetic stimulation (TMS). My research aims to optimise strategies for acquiring, pre-processing and analysing data. This includes taking established methods in retinotopic imaging to the next level, comparing pre-processing strategies, creating new methods for improved targeting in TMS and online motion tracking during concurrent TMS/fMRI sessions. A further focus in my research is on the development of phantoms in both quantitative MRI as well as diffusion MRI.
Techniques, methods & infrastructure
Novel analysis methods and models are implemented and tested in various programming languages (Python, Matlab, C++). Magnetic resonance images are acquired using state of the art imaging sequences (such as multiband echo-planar imaging (EPI)) at high (3 Tesla) and ultra-high (7 Tesla) fields. For motion and eye tracking, optical stereotactic tracking hardware and high frequency eye-tracking devices are used via innovative self-developed software interfaces.
- Woletz, M. et al., 2018. Beware detrending: Optimal preprocessing pipeline for low-frequency fluctuation analysis. Human Brain Mapping, 40(5), pp.1571–1582. Available at: http://dx.doi.org/10.1002/hbm.24468.