Parkinson’s Disease (PD) is a neurodegenerative disorder, within this categoryof diseases it is among the most prevalent worldwide. The etiology of PD isbased in progressive deterioration of neural tissue in the basal ganglia (neuronalnuclei located at the base of the cerebrum) and their related structures. Current research is focusing on treatment approaches to either enhance or replaceexisting pharmaceutical treatment approaches, such as dopamine replacementtherapy. In this project, the focus was on finding correlates between movementdata and neurological signals to provide insight into potential biomarkers forcomplex motor symptoms of PD. This will in turn provide a starting point forspecifically targeted closed-loop neural stimulation that alleviates these symptoms. Although the data available at the time of this thesis did not providesufficient insight to derive a conclusion on the neural correlates, a pipeline wasdeveloped, which analyzes and synchronizes kinematic and neural data and willenable further exploration as additional data is obtained.