Functional connectivity derived from EEG, MEG, fMRI, concurrent EEG/fMRI and peri-operative multi spectral optical imaging will be integrated with Diffusion Tensor Imaging (DTI). In order to achieve this integration, pattern analysis and graph theoretical techniques will be applied to extract diagnostic and prognostic biomarkers (e.g. functional network parameters). Crucial selection criteria will be of relevance to both diagnosis and monitoring of treatment in patients with Alzheimer’s disease, Parkinson’s disease and specific types of cancer. The major challenge of this program is to develop validated tools that are routinely applicable.
Deliverables
Functional connectivity algorithms and software that can be applied routinely in clinical practice.
Milestones
identification of relevant diagnostic and prognostic biomarkers in Alzheimer’s disease, Parkinson’s disease and cancer.
Leadership competences
Dr. Jan de Munck
- Associate professor at VUmc. His research concentrates on mathematical and signal processing aspects of medical imaging.
- He has worked on image fusion for radiotherapy applications and on MEG/EEG inverse modeling for epilepsy.
- He has authored about 100 papers in peer reviewed journals of which about one third as first author. He has an H-index of 24. He has received several research grants (NWO and national fund for epilepsy research) and has supervised several PhD students and post-docs.
