cortex

Project number:

803

Project title:

EEG spectral and source analysis in neurogenic pain and Parkinson's disease

Project supervisor:

Daniel Jeanmonod, Functional Neurosurgery, Universitätsspital Zürich, CH-8091 Zürich

Project description:

The Functional Neurosurgery group offers neurosurgical therapy to patients with severe forms of central neurogenic pain and Parkinson's disease. Our research has over the last years characterized a common physiopathological mechanism for these diseases. Recently, we were able to discriminate patients and healthy controls on the basis of their scalp EEG spectral parameters.
The present project plans to record the clinical state and scalp EEG from a larger group of patients with neurogenic pain and Parkinson's disease before surgery and 3 and 12 months after surgery as clinical improvement stabilizes. With advanced techniques of spectral analysis and EEG source localization we aim (1) to describe the differences between patient and control EEG parameters preoperatively, and (2) to follow the evolution of EEG parameters after the surgical intervention. In this way we expect to refine our understanding of the physiopathology of neurogenic pain and Parkinson's disease and to develop non-invasive scalp EEG as diagnostic tool for clinical practice.
The project is demanding on both the computational side as well as its extensive neurological aspects. The doctoral student will support the lab technician with EEG recording and will be responsible for spectral analysis and LORETA source localization. Together with the assistant MD, the student will keep track of clinical data and will perform neuropsychological testing. Candidates should have a psychology or medical background, computational skills, and interest in patient contact.

Possible cortex partners for rotation:

Thomas Müller at IGSN Bochum uses of various functional, morphologic brain imaging techniques (MRI, fMRI, SPECT, PET) in the diagnosis and evaluation of progression of neurodegenerative disorders, i.e. Parkinson's disease. Our diagnostic tool based on EEG may be developed as a complementary method which could also be tested with patients at IGSN.