Multiscale Multiphysiology Models of the Brain

大脑的多尺度多生理学模型

• 批准号: 1951446
• 负责人: Daniela Calvetti
• 金额: $ 30万
• 依托单位: Case Western Reserve University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951446&HistoricalAwards=false
• 关键词: Multiscale; Multiphysiology; Models; Brain

This project will develop mathematical models to study the link between electrophysiology, metabolism, and hemodynamics in the human brain. The human brain, accounting for only 2% of total body weight, consumes about 20% of the oxygen supply to produce energy needed to support its functions. Brain functions depend in a crucial way on the vascular system delivering oxygen and metabolites where needed and removing waste products in a timely fashion. Several questions related to the coordination of blood flow and brain activity level are still waiting for a definite answer, for example why an oversupply of oxygenated blood is delivered to activated brain regions. Understanding the coupling between brain electrophysiological activity and cerebral blood flow is crucial in many brain studies, and a model explaining the mechanism connecting cerebral electrophysiology and hemodynamics will be the key to interpret experimental data. The metabolic processes guaranteeing brain functions require a coordination between different types of brain cells, neurons and astrocytes, and are the crucial link between electrophysiology and hemodynamics. Multiscale, multi-physiology mathematical models are necessary to evaluate the feasibility of proposed interaction mechanisms, test novel oxygen transport paradigms, and understand the interplay between local and global brain phenomena. This project will open a mathematical window on the interactions and feedback of different human brain functions, with potential to uncover metabolic or vascular causes behind some brain disease states. Students will be trained through involvement in the research project. The integrated spatially distributed mathematical models developed as part of the project will be used to understand the signaling mechanisms linking neural activation to changes in the cerebral metabolism and hemodynamics, with a particular interest in the role of oxygen in normal brain activity and in the presence of cortical spreading depolarization waves related to migraine and traumatic brain injury. The new predictive computational models for the electric, metabolic, and blood flow dynamics of brain activation under normal and abnormal conditions will be based on ordinary and partial differential equations and will account for multiple spatial and temporal time scales. Modeling challenges arise from the need to interface brain functions at widely different spatial and temporal scales, involving quantities as different as electric charges and biochemical species concentrations. The design of a model capable of relating phenomena occurring in the gap junctions to changes at the organ level, e.g., in the concentrations of biochemical species or hemodynamic response, will be a great asset for the mathematical modeling community and may serve as a template for a variety of spatial and temporal multiscale paradigms. The models will depend on a multitude of parameters, whose estimation will be carried out within a Bayesian framework utilizing the tools developed for computational inverse problems. An important contribution of the project will be the quantification of uncertainty in the model predictions, which will indicate how much variability can be expected.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个项目将开发数学模型来研究人类大脑中电生理学，新陈代谢和血液动力学之间的联系。人类大脑仅占总体重的2%，消耗约20%的氧气供应来产生支持其功能所需的能量。大脑功能在很大程度上依赖于血管系统，它在需要的地方输送氧气和代谢物，并及时清除废物。与血流和大脑活动水平的协调有关的几个问题仍在等待一个明确的答案，例如为什么过量的含氧血液被输送到激活的大脑区域。了解脑电生理活动和脑血流之间的耦合是许多脑研究的关键，解释脑电生理和血流动力学之间的联系机制的模型将是解释实验数据的关键。保证大脑功能的代谢过程需要不同类型的脑细胞、神经元和星形胶质细胞之间的协调，并且是电生理学和血液动力学之间的关键联系。多尺度，多生理学的数学模型是必要的，以评估拟议的相互作用机制的可行性，测试新的氧运输模式，并了解局部和全球的大脑现象之间的相互作用。该项目将为不同人脑功能的相互作用和反馈打开一个数学窗口，有可能揭示某些大脑疾病状态背后的代谢或血管原因。学生将通过参与研究项目进行培训。作为该项目的一部分开发的集成空间分布数学模型将用于了解将神经激活与脑代谢和血液动力学变化联系起来的信号机制，特别关注氧在正常脑活动中的作用以及与偏头痛和创伤性脑损伤相关的皮质扩散去极化波的存在。在正常和异常条件下，大脑激活的电、代谢和血流动力学的新预测计算模型将基于常微分方程和偏微分方程，并将考虑多个空间和时间尺度。建模的挑战来自于需要在广泛不同的空间和时间尺度上连接大脑功能，涉及电荷和生化物质浓度等不同的量。设计能够将发生在差距连接处的现象与器官水平的变化联系起来的模型，在浓度的生化物种或血液动力学反应，将是一个很大的资产的数学建模社区，并可能作为一个模板，为各种空间和时间的多尺度范例。这些模型将取决于众多的参数，其估计将在贝叶斯框架内进行，利用为计算逆问题开发的工具。该项目的一个重要贡献将是量化模型预测的不确定性，这将表明有多少可变性可以预期。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Bayesian hierarchical dictionary learning

• DOI: 10.1088/1361-6420/acad21
• 发表时间: 2022-12
• 期刊: Inverse Problems
• 影响因子: 2.1
• 作者: Nathan Waniorek;D. Calvetti;E. Somersalo

Modeling surface pH measurements of oocytes

模拟卵母细胞表面 pH 测量

• DOI: 10.1088/2057-1976/ac71d0
• 发表时间: 2022
• 期刊: Biomedical Physics & Engineering Express
• 影响因子: 1.4
• 作者: Bocchinfuso, A;Calvetti, D;Somersalo, E
• 通讯作者: Somersalo, E

On the fast track: Rapid construction of stellar stream paths

快车道上：快速构建恒星流路径

• DOI: 10.1093/mnras/stad1166
• 发表时间: 2023
• 期刊: Monthly Notices of the Royal Astronomical Society
• 影响因子: 4.8
• 作者: Starkman, Nathaniel;Bovy, Jo;Webb, Jeremy J;Calvetti, Daniela;Somersalo, Erkki
• 通讯作者: Somersalo, Erkki

Modeling Epidemic Spread among a Commuting Population Using Transport Schemes

• DOI: 10.3390/math9161861
• 发表时间: 2021-08-01
• 期刊: MATHEMATICS
• 影响因子: 2.4
• 作者: Calvetti, Daniela;Hoover, Alexander P.;Somersalo, Erkki
• 通讯作者: Somersalo, Erkki

Bayesian particle filter algorithm for learning epidemic dynamics

• DOI: 10.1088/1361-6420/ac2cdc
• 发表时间: 2021-11-01
• 期刊: INVERSE PROBLEMS
• 影响因子: 2.1
• 作者: Calvetti, D.;Hoover, A.;Somersalo, E.
• 通讯作者: Somersalo, E.