CRCNS: Model Based Data Assimilation & Control of Sleep-Wake Regulation in Epilepsy

CRCNS：基于模型的数据同化

• 批准号: 9087227
• 负责人: Kevin Douglas Alloway
• 金额: $ 30.56万
• 依托单位: PENNSYLVANIA STATE UNIV HERSHEY MED CTR
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-17 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9087227
• 关键词: Accounting; Animals; Assimilations; Behavior; Behavioral; Biological; Brain; Cell Nucleus; Cells; Chronic; Computer Simulation; Coupled; Coupling; Data; Development; Diagnosis; Disease; Electric Stimulation; Engineering; Epilepsy; Feedback; Hippocampus (Brain); Implant; Investigation; Measurement; Mental Health; Metabolic; Methodology; Methods; Modeling; Monitor; Neurologic; Neurosciences; Pattern; Performance; Predisposition; Process; Quality of life; Rattus; Regulation; Reporting; Reproduction; Research; Role; Schizophrenia; Seizures; Sensory; Series; Sleep; System; Techniques; Temporal Lobe Epilepsy; Time; Validation; Work; base; biological systems; disorder control; information processing; learning materials; mathematical model; nervous system disorder; network models; neural stimulation; outreach; reconstruction; relating to nervous system; sleep epilepsy; sleep regulation; statistics; therapy development

DESCRIPTION (provided by applicant): Sleep is a fundamental biological cycle that is coupled into every aspect of body function from behavior and information processing to metabolic storage and release. Sleep-wake patterns correlate with, and sleep disruptions are comorbid with, many neurological and mental health disease dynamics including epilepsy. Abnormal sleep can be disruptive to quality of life and further exacerbate the primary disorders. Within the past decade a number of groups have developed mathematical and computational dynamical models for the network of brain nuclei and cell groups that regulate sleep-wake dynamics. But their validation to date has been substantially limited to reproduction of statistic of cycle time and dwell time durations, and their application to understanding and control of diseases limited. The first objective of this project is to validate and optimize these models for reconstruction, forecasting, and control of sleep-wake regulation. This involves experimentally recording activity from select cell groups of the sleep-wake regulatory system (SWRS) along with cortical, hippocampal, and behavioral activity. The mathematical models will be incorporated into model-based data assimilation (DA). The parameters and models will be optimized for reconstruction and forecasting, and performance will be used to establish the 'best' model. Experimental perturbation of sleep state and sleep cycle dynamics will be done with both sensory and direct neural stimulation. The models will then be modified to account for and predict changed dynamics from such perturbations. The second objective of this project is to apply these models and framework to understand and control sleep-cycle dis-regulation in a model of temporal lobe epilepsy. This involves experimentally recording activity from the SWRS in epileptic animals, modifying and optimizing the models to reconstruct and forecast the observed sleep cycle dynamics. The models will then be used in closed feedback form to prescribe control perturbations to regularize the sleep cycles of the epileptic animals. The project embodies a paradigm shift for neuroscience and neural-engineering in which computational models are validated and optimized through their capacity to reconstruct and forecast detailed time series from real neurological measurements, that such model-based reconstruction is used to observe detailed state dynamics from less costly (invasive or damaging) measurements, and in which such biologically based models are used to control neurological systems and treat neurological disorders. The approach of this proposed research will have a major impact in diagnosing, monitoring, and controlling neurological disorders by both incorporating detailed biologically based models into the measurement or observation process, and by allowing remote observation through measurement of identified less costly measurements. The specific validation and improvement of computational models and observation methodology of the sleep-wake regulatory system will allow detailed investigation of its role in a host of neurological diseases in which sleep regulatin is implicated either as a cause or consequence, such as epilepsy and schizophrenia, and thereby the development of interventions or therapy. In addition to the theoretical and experimental advances, educational and outreach will be served through this project, including development of new course materials and enhancing underrepresented participation in research.

描述(申请人提供)：睡眠是一个基本的生物循环，它与身体功能的各个方面相结合，从行为和信息处理到新陈代谢的储存和释放。睡眠-觉醒模式与包括癫痫在内的许多神经和心理健康疾病的动态相关，并且睡眠中断与之共生。睡眠不正常可能会扰乱生活质量，并进一步加剧原发疾病。 在过去的十年里，许多研究小组为大脑核团和细胞群网络开发了数学和计算动力学模型，以调节睡眠-觉醒动力学。但到目前为止，它们的有效性基本上限于复制周期时间和停留时间的统计数据，并且它们在理解和控制疾病方面的应用有限。该项目的第一个目标是验证和优化这些用于重建、预测和控制睡眠-觉醒调节的模型。这包括实验记录睡眠-觉醒调节系统(SWRS)中选定细胞组的活动，以及大脑皮层、海马体和行为活动。这些数学模式将并入基于模式的数据同化(DA)。将对参数和模型进行优化以进行重建和预测，并将根据性能建立“最佳”模型。睡眠状态和睡眠周期动力学的实验扰动将通过感官刺激和直接神经刺激来完成。然后将对模型进行修改，以解释和预测从此类扰动中发生的动态变化。本项目的第二个目标是应用这些模型和框架来理解和控制颞叶癫痫模型中的睡眠周期失调。这包括通过实验记录癫痫动物的SWRS活动，修改和优化模型以重建和预测观察到的睡眠周期动力学。然后，这些模型将以封闭反馈的形式使用，以规定控制扰动，以规范癫痫动物的睡眠周期。该项目体现了神经科学和神经工程的范式转变，其中计算模型通过其根据真实神经测量重建和预测详细时间序列的能力得到验证和优化，这种基于模型的重建用于从成本较低的(侵入性或破坏性)测量观察详细的状态动态，并且这种基于生物学的模型被用于控制神经系统和治疗神经疾病。这项拟议研究的方法将通过将详细的基于生物学的模型纳入测量或观察过程，并通过测量已识别的成本较低的测量来允许远程观察，从而在诊断、监测和控制神经疾病方面产生重大影响。对睡眠-觉醒调节系统的计算模型和观察方法的具体验证和改进将使人们能够详细研究它在许多神经疾病中的作用，这些疾病涉及睡眠调节作为原因或结果，如癫痫和精神分裂症，从而发展干预或治疗。除了理论和实验方面的进展外，还将通过该项目提供教育和宣传服务，包括编写新的课程材料和加强对人数不足的研究的参与。