The Pathophysiology of Network Synchrony in Parkinson's Disease

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Project Summary/Abstract The physiological underpinning of motor symptoms in Parkinson disease (PD) remains incompletely understood. We propose that the dynamic nature of basal ganglia thalamocortical (BGTC) network activity accounts for and is critical for understanding the dynamic symptomatology of PD and the pathophysiology of disease. We believe that the failure to focus on and investigate the non-stationarity of BGTC physiology and movement kinematics significantly contributes to inconsistency in published results and has impeded progress. We propose and investigate a novel model that accounts for the underexplored temporally dynamic cascade of physiological events occurring between nodes in the BGTC motor circuit. We hypothesize that transient exaggerations in network-level coupling that result in impaired information flow trigger pathophysiological and motor sequelae of PD, including rigidity and bradykinesia, allowing for and differentiating pathological and non-pathological synchrony. We hypothesize that the likelihood of pathological synchrony resulting in impaired information flow depends on the “movement” state, accounting for disproportionate difficulty with movement initiation in PD. We also hypothesize that treatment (dopaminergic and deep brain stimulation [DBS]) decreases the probability of a synchrony-triggered pathological cascade, with some common final changes in the network (e.g., cortical phase amplitude coupling) but with specific differences in physiological effects due to distinct sites of therapeutic action. We will build on prior success of investigating PD network physiology in patients undergoing DBS implantation surgery by simultaneously assessing population level activity from multiple BGTC nodes, including motor cortex, dorsal premotor cortex (to where pallidal-receiving thalamic regions project), subthalamic nucleus (STN), and globus pallidus (GPi, in separate patients), in relation to clinical symptoms and behavior. We now also integrate single unit physiology and synchronized dynamic tasks to test our model. In Aim 1, we will establish the dynamic relationship between network synchronization, local oscillations, and pathophysiologic sequelae under different therapeutic conditions, including STN and GPi DBS and dopaminergic therapy. We hypothesize an increased probability of synchrony leading to pathologic sequelae in the “off” state and test specific hypotheses about both common and distinct physiological effects of the different therapies, depending on site of action. In Aim 2, we hypothesize and aim to demonstrate that movement-related brain states affect sequelae of network synchrony both physiologically and behaviorally, differentially impacting movement initiation and ongoing activity. Finally, in Aim 3, we will distinguish normal and pathologic synchrony (across therapeutic and movement conditions) using a novel information theoretic frameowrk, with a focus on the impact of criticality, complexity matching, and impairments in information flow. This work will enhance the BGTC functional wiring diagram by defining the pathophysiologic significance of network synchrony in PD. Addressing this gap will facilitate therapeutic innovations, including identification of signals for adaptive DBS and to guide pharmacologic innovation.