Recent success of neurostimulation therapies such as deep brain stimulation (DBS) for Parkinson's disease (PD) support the importance of understanding how activity of specific local neuronal population influence the overall brain network to drive behaviors such as reversing tremors in Parkinson's disease. Given the resulting complex behavioral output, it is likely that the effects of brain stimulations are not limited to simply changing local neuronal activity. The local change is driving neural activity in many regions of the brain to give rise to the therapeutic effects. However, this important neurobiological question of how large-scale network activity relates to behavior still remains largely elusive. Understanding of how specific neuronal population functionally relates to the overall brain enables us to systematically design therapeutics for neurological diseases based on our concrete knowledge of the circuit function underlying behavior. The main therapeutic goal for neurological diseases lies in reversing the behavioral phenotype such as essential tremors, which are a direct consequence of loss of proper circuit function. If the circuit function underlying behavior can be directly visualized, the potential for therapeutic intervention is limitless. Therefore, in this proposal, we aim to start reverse- engineering global brain dynamics associated with the basal ganglia circuit and to understand how they relate to motor behavior. The novel optogenetic functional magnetic resonance imaging (ofMRI) technology, enables us to selectively trigger specific neuronal populations within the brain while monitoring how activity in regions across the brain are altered as a result of such stimulations. Optogenetics enables cell-type specific, millisecond-scale, activity modulation using light while high-field fMRI tracks resulting responses in live subjects across the whole brain. In the initial study, it was shown tha specific cell-type triggered fMRI responses could be measured throughout the brain with temporal precision. Since we first developed the ofMRI technology, we developed advanced imaging technologies to enable high-throughput, high-resolution images in live subjects. With these advances in place, we acquired preliminary ofMRI datasets, through which we have evidence that dopamine D1 and D2 receptor expressing medium spiny neuron (MSN)-driven dynamic interactions across the whole brain can be reliably measured across multiple synapses. Electrophysiological recordings also show strong evidence that the time course of the ofMRI signal closely matches underlying electrical activity patterns. With this unprecedented ability to obtain global brain dynamics associated with cell- type specific modulations, we aim to determine the global direct and indirect pathway functions. These measurements will then be computationally modeled to provide a mechanistic understanding. In addition, resting-state fMRI measurements will be made during systematically increased and decreased excitability of D1 or D2 MSN. This will enable us to evaluate how the direct and indirect pathway imbalance is reflected in resting-state fMRI measurements, and allow direct translation of the findings into clinical neuroimaging.

Public Health Relevance

Due to the extreme complexity of the brain, we still have a very limited understanding of how cells in our brains work together with other cells across the whole brain to give rise to our behaviors. Utilizing a novel technology that enables precise, selective excitation and/or inhibition of brain cells while measuring high-resolution videos of the associated whole brain interactions, we aim to reverse-engineer the global brain function dynamics associated with motor behavior. Upon success, these measurements can be utilized to understand normal and diseased brain circuit functions and associated motor behaviors, which in turn will enable us to systematically design therapies that can restore normal brain circuit function in neurological diseases such as Parkinson's disease.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Neuroscience and Ophthalmic Imaging Technologies Study Section (NOIT)
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Chen, Daofen
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Stanford University
Schools of Medicine
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