Collaborative Research: Understanding and Optimizing Dynamic Stimulation for Improvement of Short- and Long-term Brain Function

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The brain is an amazing organ which is responsible for a number of important functions including cognition, attention, emotion, perception, memory, and motor control. Many brain functions and disorders are believed to have a dynamical origin; for example, it has been hypothesized that some symptoms of Parkinson's disease are due to pathologically synchronized neural activity in the motor control region of the brain. Recent research suggests that an FDA-approved treatment for Parkinsonian tremors, called deep brain stimulation, is effective because it partially desynchronizes the neural activity via clustering, in which neurons in a subpopulation are synchronized with each other, but desynchronized with neurons in other subpopulations. This research will use engineering techniques, mathematical principles, computer simulations, and in vitro experiments to develop more energy-efficient electrical current stimuli which promote such clustering. Moreover, stimuli will be developed which enhance beneficial neural plasticity in which neurons change their connection strengths based on their activity patterns, work that may be important for treatment of diseases and for situations in which plasticity is desirable such as learning, memory, and recovery from strokes and spinal cord injury.This research will use engineering techniques, mathematical principles, computer simulations, and in vitro experiments to develop efficient electrical stimuli for controlling neural populations in beneficial ways. This will include designing power-minimized stimuli which cause a neural population to split into balanced clusters, in which each cluster contains a nearly identical proportion of the overall population and neighboring clusters are roughly equally spaced in phase, a state of partial desynchronization which recent work suggests is responsible for the success of the standard protocol for deep brain stimulation treatment of Parkinson's disease. Moreover, Hebbian models for synaptic plasticity will be used in combination with optimal control theory to design stimuli which optimally promote plasticity to give beneficial long-term changes in synaptic connections, work which is expected to have important implications for Parkinson's disease and other disorders such as epilepsy and depression, and for situations in which plasticity is desirable such as learning, memory, and recovery from strokes and spinal cord injury. The plasticity studies will also include in vitro brain slice experiments in which neurons will be synchronized to an oscillating electric field and stimulation applied through an electrode to generate balanced clusters, whose effect on synaptic strengths will be measured.