PROJECT SUMMARY/ABSTRACT The pathophysiological basis underlying the development of parkinsonian motor signs (PMS) and how deep brain stimulation (DBS) works to improve them is unclear. Synchronized oscillations in the beta band have been proposed to play a significant role, but how this activity leads to the development of the motor abnormalities in Parkinson's disease (PD), the potential role of oscillatory activity in other frequency bands and how this affects neuronal activity in the basal ganglia thalamo-cortical circuit (BGTC) are not well understood. In this proposal we will further explore the cortical-subcortical interactions that underlie the development of PMS, how DBS modifies this activity, and compare DBS to L-dopa alone or with DBS by examining the changes in synchronized oscillatory activity, coupling and connectivity changes that occur between cortical and subcortical structures under these different conditions. To better understand the relative effect of stimulation focused into motor versus nonmotor regions of the subthalamic nucleus and internal segment of the globus pallidus on BGTC circuitry and motor signs we will compare the effect of DBS directed into motor versus nonmotor regions using segmented lead technology, explore whether these interactions change with continued DBS and develop novel algorithms for closed loop DBS that include both beta and gamma frequency spectrums and incorporate a novel “phasic stimulation” approach where stimulation is timed to a specific phase of the oscillation. The nonhuman primate MPTP model of PD will be used and animals will be assessed both at rest, as well as during passive movement and task related activity. This study will provide a greater understanding of the pathophysiological changes that occur in BGTC circuitry in PD, further delineate the mechanisms underlying the therapeutic effects of DBS and L-dopa, and characterize the effect of directional DBS on BGTC circuitry and motor signs, while identifying physiological biomarkers to be used for closed loop algorithms that improve motor signs both at rest and during task related activity where biomarker activity is dynamic and constantly changing.