I studied physics at the University of Regensburg, Germany, for my BSc and masters degree. I then went on to qualify as a medical physicist during two years working in the radiation therapy department of the university hospital in the above town. My experience with brain imaging analysis during that time lead me on to do a PhD in the field of neuroscience in a collaboration between the Technical University of Berlin, Germany, and UCL in London. This project then resulted in a post-doc position here in Manchester and finally a Lectureship in 2003.

Investigation of the structure, hemodynamic response and metabolism in functional brain imaging.

 
Multi-wavelength optical imaging with electrode and tissue oxygen recordings.

We try to establish how neural activity and the connected changes in metabolic function relate to the intrinsic signals measured in many functional brain imaging methods like fMRI, PET or optical imaging. By acquiring two dimensional spectroscopic data we can calculate the local concentration of oxy- and deoxy-hemoglobin as well as signals from changes in tissue scattering. This information can then be combined with recordings of the electric activity of neurons or neuroanatomical staining of the tissue with antrograde and retrograde tracers.
The aim of this research is to improve the spatial and temporal resolution of intrinsic brain imaging techniques. This improvements in cortical imaging are crucial in the early detection of change of the brain response and tissue oxygenation due to injury or disease like stroke or neuroinflamation.

Independent component analysis of functional brain imaging data

New techniques and advances are emerging in the field of statistical signal processing that deserve the attention of the biomedical and neuroscience community. Several algorithms have been proposed to separate multiple signal sources on the basis of their statistical properties, instead of the more common spectral features. These algorithms have the promise to lead to more effective artefact rejection algorithms, one of the most challenging conditions faced in biomedical signal processing.