Time-varying spatiotemporal causal interactions in the functional brain networks

功能性大脑网络中时变的时空因果相互作用

• 批准号: 10590411
• 负责人: Nan Xu
• 金额: $ 9.29万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10590411
• 关键词: Address; Alzheimer' s Disease; Animal Experiments; Animal Model; Biological Markers; Biomedical Engineering; Blood Vessels; Brain; Brain Concussion; Brain Diseases; Brain imaging; Brain region; Clinical; Clinical Research; Cognitive; Communication; Commuting; Data; Development; Doctor of Philosophy; Functional Magnetic Resonance Imaging; Functional disorder; Human; Image Analysis; Impairment; Length; Measures; Mentors; Methodology; Methods; Modeling; Multimodal Imaging; Neurology; Neurons; Neurosciences; Pathologic; Pathology; Pathway interactions; Patients; Pattern; Performance; Phase; Play; Post-Concussion Syndrome; Postdoctoral Fellow; Program Development; Rehabilitation therapy; Research Institute; Research Personnel; Rest; Rodent; Role; Severities; Signal Transduction; Slide; Symptoms; Syndrome; System; Techniques; Testing; Therapeutic; Time; Training; Translating; Uncertainty; Universities; Variant; Visual Motion; Work; algorithm development; blood oxygen level dependent; career; career development; clinical phenotype; clinical practice; clinical training; cognitive neuroscience; experimental study; hemodynamics; image translation; imaging biomarker; innovation; insight; machine learning model; mathematical model; method development; motion sensitivity; multimodality; multisensory; nervous system disorder; neurophysiology; novel; patient response; response; spatiotemporal; visual-vestibular

This proposal describes a five-year career development program to prepare the candidate, Dr. Nan Xu, for a career as independent investigator at a major academic research institute, with the expertise of modeling dynamics of brain causal system to provide novel insights into the basic pathophysiology of neurologic disorders. This proposal develops upon Dr. Nan Xu’s expertise in mathematical modeling and algorithm development to translate model inferences in neurologic disorders and therapeutic practices; while training her to ask scientific questions relevant to clinical practice and neurophysiological pathology. The PI will be mentored at Biomedical Engineering at Georgia Tech and Emory University by Drs. Shella Keilholz (blood oxygenation level dependent (BOLD) dynamics and their neurophysiological origins), Vince Calhoun (translational image analysis and biomarkers), and Jason Allen (clinical training in neurologic disorders). Their complementary expertise will help PI to bridge the gap between her analytical expertise and problems in clinical neurology and cognitive neuroscience that need to be addressed. In the brain causal system, evidence has shown that the directed information transfer may comprise not only a strength, but also a duration and a capacity. The latter two metrics imply important neuroscientific aspects that have not been well studied in the past. They may play key roles in pathological dysfunctions such as the vestibular syndrome which occurs in 80% of patients following concussion. In PI’s thesis work, an innovative measure was developed to predict the first two metrics. Building upon this work, novel theoretical and computational approaches will be developed in this study to further evaluate the temporal variability in the strength and duration of information transfer (K99) , and then to characterize the information capacity as well as to evaluate the temporal variability of all three causal metrics (R00) . The causal estimates of resting BOLD data will be validated against the estimates of the concurrently recorded local field potential (LFP) data, and task- evoked BOLD data ( for both K99 and R00 ). Finally, findings ( in both K99 and R00 ) will be translated into clinical studies of patients with different severity of vestibular syndromes. The specific aims are to: (1) model and compute the time-varying spatiotemporal functional causal interactions among functional brain regions; (2) evaluate the reliability and sensitivity of the estimated time-varying causal metrics using multimodal brain imaging data of rodents and human, and (3) access the time-varying causal patterns in patient brains with different severity of post-concussive visual motion sensitivity, which is one type of vestibular syndromes that were commonly occurred in patients after concussion. Successful project completion would potentially transform the rapidly evolving field of dynamics modeling in brain causal system, facilitate basic neuroscience discovery, enable comprehensive identification of neurologic disorders, and inspiring new animal experiments for studying neurological diseases.

本建议书描述了一个为期五年的职业发展计划，以帮助候选人徐南博士为将来的职业发展做好准备。 职业生涯作为一个主要的学术研究机构的独立调查员，与建模的专业知识， 脑因果系统的动力学，为神经系统疾病的基本病理生理学提供新的见解。 该提案基于Nan Xu博士在数学建模和算法开发方面的专业知识， 翻译神经系统疾病和治疗实践中的模型推理;同时训练她询问科学的 与临床实践和神经生理病理学相关的问题。PI将在生物医学部接受指导 Shella Keilholz博士在格鲁吉亚理工和埃默里大学的工程学（血氧水平依赖 （BOLD）动力学及其神经生理学起源），文斯卡尔霍恩（翻译图像分析和 生物标志物）和Jason艾伦（神经疾病临床训练）。他们互补的专业知识将有助于 PI弥合她的分析专业知识与临床神经病学和认知问题之间的差距 神经科学需要解决的问题 在大脑因果系统中，有证据表明，定向信息传递可能不仅包括 力量，但也是一个持续时间和能力。后两个指标意味着重要的神经科学方面， 在过去没有得到很好的研究。它们可能在病理性功能障碍中发挥关键作用，例如： 前庭综合征，80%的患者在脑震荡后出现。在PI的论文工作中， 测量被开发来预测前两个度量。在这项工作的基础上，新的理论和 计算方法将在这项研究中开发，以进一步评估的时间变化， 信息传递的强度和持续时间 （K99） ，然后描述信息容量以及 评估所有三个因果度量的时间变异性 （R00） .静息BOLD数据的因果估计 将根据同时记录的局部场电位（LFP）数据的估计值进行验证，并执行任务- 数据来源：BOLD数据库（ 对于K99和R 00 ).最后，调查结果（ 在K99和R 00中 ）将转化为临床 不同程度前庭综合征患者的研究。具体目标是：（1）建模和 计算功能脑区之间随时间变化的时空功能因果相互作用;（2） 使用多模态脑评估估计的时变因果度量的可靠性和灵敏度 啮齿动物和人类的成像数据，以及（3）访问患者大脑中随时间变化的因果模式， 不同程度的脑震荡后视觉运动敏感性，这是一种类型的前庭综合征， 多见于脑震荡后。 项目的成功完成可能会改变快速发展的动力学建模领域， 大脑因果系统，促进基础神经科学发现，使神经系统的全面识别 疾病，并启发新的动物实验研究神经系统疾病。