Deep brain stimulation (DBS) is a remarkable treatment for later stages of Parkinson's disease and an emerging revolutionary therapy for other neurological and psychiatric disorders. Currently DBS is employed in a static fashion, in the sense that stimulation intensity and frequency are manually adjusted. However, the neural circuits of the brain are highly dynamic, so major advances to DBS therapy must be "dynamic" systems as well, with recording and processing neural signals in real-time and modulating the applied stimulation based on the dynamic state of the brain. The overall goal of this project is to lay the scientific and technical foundations for dynamic DBS systems that will radically increase the efficacy of DBS in treating neurological and psychiatric disorders. The proposed studies are therefore significant in terms of advancing both basic science, by enabling new and faster experiments, and clinically, by accelerating the development and implementation of DBS therapies. As part of education and outreach activities, high school, college and graduate students will be engaged in neuroengineering education and research by (i) using an engaging module to teach high school students basics of neurobiology theory and experiment; (ii) challenging college juniors to build their own rat DBS with power and size constraints; and (iii) teaching graduate students neural signal processing using recorded neural activity.
The overall goal of this project is to advance the scientific and technical foundations for dynamic DBS systems that will radically increase the efficacy of DBS in existing indications and enable rapid development for other neurological and psychiatric disorders. As an initial target for innovation, this proposal focuses on DBS of the subthalamic nucleus (STN) for Parkinson's disease. The following specific aims are proposed. 1 Use new materials to develop joint stimulation and recording electrodes. Record the activity of cortico-striatal-thalamic neurons in healthy, diseased, and DBS-stimulated states during intentional movements. 2 Develop a latent variable model of the dynamics of neural activity during intentional movement. Build a rodent-scale dynamic DBS device that implements model-based, closed-loop dynamic stimulation. 3 Evaluate the effects of long-term dynamic DBS across large cohorts of animals using an automated, high-throughput behavioral monitoring system. The proposed studies are expected to lay the foundation for novel dynamic DBS therapies; generate new conceptualizations of the neural basis of motor symptoms and STN DBS therapy in Parkinson's disease; transition computational models of DBS from the current static approaches to ones that incorporate the time-varying nature of movement-related neural activity; and help discover the neuroprotective and non-motor effects of static and dynamic DBS.
