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DESCRIPTION (provided by applicant): PROJECT SUMMARY / ABSTRACT Across the world, nearly 50 million people suffer from epilepsy. For an estimated 30% of these individuals, seizures remain poorly controlled despite maximal medical management. Moreover, treatment of epilepsy through medication often results in significant - sometimes debilitating - side effects. To advance the therapeutic management of epilepsy, we must understand the physiological mechanisms which support this disease. Unraveling these mechanisms is especially difficult. Like many neural processes, the seizure involves spatial scales spanning many orders of magnitude, from the individual neuron to the entire nervous system. Moreover, typical clinical recordings provide only a limited view of the vast mechanisms underlying the seizure. In this project, an interdisciplinary research group consisting of clinicians, statisticians, and mathematicians will study the dynamical mechanisms that support epilepsy and, in doing so, suggest novel therapies to treat the disease. The research will focus on three fundamental aspects of the seizure - how it begins, how it spreads over the brain, and how it ends - observed in voltage recordings from human patients with epilepsy. These recordings will span multiple spatial scales and include activity generated by individual neurons, small neural populations, and large brain regions. To characterize these data, sophisticated analysis techniques will be applied that link the activity across spatial scales. In addition, computational models of the neural activity will be developed and constrained using the multiscale data. These models will then be applied to suggest the mechanisms that support multiscale interactions during seizure and to propose novel therapies to treat epilepsy. Completion of the proposed research will represent a significant step forward toward a deeper and more complete understanding of epileptic physiology, and toward a system for exploring and testing innovative methods for seizure control.
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Rigorous Research Principles for Practicing Neuroscientists
Sleep Spindle Dynamics as a Clinical Biomarker of Aging, Alzheimer's Disease, and Trisomy 21
  • 批准号:
    10733629
  • 项目类别:
  • 资助金额:
    $257.69万
  • 财政年份:
    2023
  • 负责人:
    Uri Tzvi Eden
  • 依托单位:
Statistical machine learning tools for understanding neural ensemble representations and dynamics
Measuring, Modeling, and Modulating Cross-Frequency Coupling
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