Deep brain stimulation (DBS) is a neurosurgical therapy for Parkinson's disease that involves the implantation of a four contact lead into subcortical brain structures for delivering continuous, high frequency electrical stimulation. This doctoral dissertation has aimed to advance DBS technology for the treatment of Parkinson's disease by: 1) elucidating biomarkers of the disease and DBS therapy, 2) evaluating novel, 32 contact high-density electrode arrays to improve sensing and stimulation within the basal ganglia, and 3) developing computational algorithms that can capture complex neurophysiological interactions in high-dimensional feature spaces of these biomarkers. The primary studies employed the MPTP non-human primate model of Parkinsonism to invasively probe how neural oscillations in the form of local field potentials (LFPs) are modulated in conjunction with disease severity, therapies, and behavior. These results demonstrate that high-density electrode arrays are superior to the current state- of-the-art, because they improve the spatial selectivity of sensing LFPs and enable the delivery of directional stimulation. Subsequently, I have shown how non-invasive imag- ing techniques and commercially available implantable devices could be used to study Parkinson's disease in patients. Ultimately, these results motivate the use of higher-density DBS leads for sensing and stimulation, and facilitate the implementation of more complex therapeutic algorithms, such as closed-loop stimulation.