Basic mechanisms of DBS for Parkinson’s disease: computational and experimental studies on neural dynamics

Deep Brain Stimulation (DBS) has become an accepted therapy of last resort for Parkinson’s disease (PD). The acceptance of DBS for the management of PD motor symptoms is based on its success rate and contrasts sharply with ones understanding of the pathophysiology underlying the disease state and mechanism of DBS. Theoretical and experimental studies at a neuronal and population level continue to shed light on the mechanism of DBS. In this thesis, we employ computational models in order to test certain hypothesis put forward in the field regarding the mechanism of DBS and efficacy of high frequency stimulation. Moreover, we make use of cellular recordings in order to test the validity of observations made using computational models. We incorporate population level recordings, obtained from PD patients, into a theoretical population level model in order to infer possible neuronal mechanisms underlying the differences observed in the recordings, arising from different experimental conditions. Last but not least, we analyze experimental recordings obtained from PD patients and assess which signal properties are selective to certain brain regions of interest.