PROJECT SUMMARY A promising strategy to improve neuromodulation therapies (e.g. deep brain stimulation) in Parkinson’s Disease (PD) is to develop stimulation paradigms that target specific neural signals. Most previous work has aimed to identify and reduce pathologic signals. An unexplored alternative approach is to identify and enhance neural signals that promote movement. Several scenarios known to improve movement in PD patients are the presence of visual movement targets, rhythmic auditory stimuli, and motivational incentives. The goal of this proposal is to capitalize on these scenarios to identify biomarkers of movement facilitation that may serve as targets for future neuromodulation therapies. This approach has potential to provide novel therapies for symptoms refractory to current treatments, such as freezing of gait. Previous work examining neural mechanisms of movement facilitation in PD have yielded inconsistent results. This may be due to a failure to account for well-known heterogeneity in behavioral benefits across PD patients and the assumption that different cueing phenomena exert motor benefits through a single neural mechanism. The studies proposed here test the overarching hypothesis that 3 different types of cues (visual targets, rhythmic auditory stimuli and reward incentives) facilitate movement through distinct neuroanatomic circuits and electrophysiological mechanisms, by leveraging known variability in behavioral cueing benefits across patients. Aim 1 is to demonstrate behavioral dissociations between the 3 forms of movement facilitation within patients and relate variability in cueing benefits to integrity of dissociable neuroanatomic circuits as measured by resting state and diffusion tensor magnetic resonance imaging (MRI). Aim 2 is to characterize the electrophysiological correlates of behavioral benefits for the different cue types using electroencephalography (EEG) and intraoperative electrophysiological recordings obtained during implantation of deep brain stimulator in the globus pallidus internus. This work will augment my prior skills in task fMRI, transcranial magnetic stimulation (TMS) and electrophysiology by extending training in multiple modalities (high density EEG, resting state fMRI, DTI); build my analytic skills in advanced multivariate statistics; and advance my expertise in PD motor physiology. My mentorship team comprises experts in PD neurophysiology and neuromodulation therapies, and non-invasive studies of inter-individual differences in motor neurophysiology. Coursework in multivariate statistics and seminars in advanced EEG and neuroimaging applications will further my development. The environment at UCLA has a rich interdisciplinary neuroimaging community, state-of-the-art image acquisition facilities including Ahmanson-Lovelace Brian Mapping Center and Staglin Center for Cognitive Neuroscience and a renowned clinical Movement Disorders Division. The career development plan forges a path to ...