Collaborative Research: Extreme Mechanics of the Human Brain via Integrated In Vivo and Ex Vivo Mechanical Experiments
合作研究:通过体内和离体综合力学实验研究人脑的极限力学
基本信息
- 批准号:2331294
- 负责人:
- 金额:$ 37.02万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-04-01 至 2027-03-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The human brain exhibits complex mechanical behavior. Its deformation under external forces depends on the extent and speed of loading. Rapid deformation of the brain during events such as blasts and automotive crashes can cause traumatic brain injury. Understanding the mechanical behavior of the human brain under such extreme conditions is critical to developing computer models for predicting brain injury. This knowledge is also needed to design safer personal protective equipment and brain injury management and prevention strategies. Unfortunately, the current understanding of the mechanical behavior of living humans' brains is restricted to small deformations and a narrow range of loading rates that do not represent the full spectrum of injury-causing conditions. This award supports fundamental research combining high-rate mechanical testing, analytical and computational modeling, and machine learning to generate insights into how the living human brain responds to large and rapid loading. Results from this research will positively impact U.S. national health and welfare and will contribute to the fields of tissue mechanics, traumatic brain injury, and machine learning. This project will lead to new courses and involve contributions from underrepresented minorities.The overarching goal of this research is to understand the high strain rate mechanics of the brain in its native biophysical environment. The first stage will focus on tissue responses under small deformations and dynamic strain rates. Wide-band Magnetic Resonance Elastography experiments will be conducted on brain tissue specimens from multiple brain regions to develop linear viscoelastic constitutive models. Multi-fidelity models will be developed to fuse the observed responses with available narrow-band in vivo brain tissue responses for predicting linear viscoelastic properties of the in vivo brain tissue in a wide range of loading frequencies. The second stage will focus on tissue responses under large deformations and extreme strain rates. Quasi-static and dynamic mechanical testing will be conducted to develop visco-hyperelastic constitutive models. Physics-informed multi-fidelity models will be developed to fuse the ex vivo visco-hyperelastic responses with the in vivo linear viscoelastic responses characterized in the previous stage. This study will significantly advance our understanding of brain biomechanics by generating insights into the relationship between in vivo and ex vivo tissue mechanics and the first-ever full-field maps of the living brain’s mechanical properties applicable under extreme loading conditions.This project is jointly funded by the Biomechanics and Mechanobiology (BMMB) program and the Established Program to Stimulate Competitive Research (EPSCoR).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.
人脑表现出复杂的机械行为。它在外力下的变形取决于负载的程度和速度。在爆炸和汽车崩溃等事件期间,大脑的快速变形会导致脑外伤。在这种极端条件下,了解人脑的机械行为对于开发用于预测脑损伤的计算机模型至关重要。还需要这些知识来设计更安全的个人保护设备,脑损伤管理和预防策略。不幸的是,目前对活人大脑机械行为的理解仅限于较小的变形和狭窄的载荷速率,而范围不代表全部造成伤害的条件。该奖项支持基础研究,结合了高速机械测试,分析和计算建模以及机器学习,以产生对生命的人脑如何对大型和快速载荷做出反应的见解。这项研究的结果将对美国国家健康和福利产生积极影响,并将为组织机制,创伤性脑损伤和机器学习的领域做出贡献。该项目将导致新课程,并涉及代表性不足的少数群体的贡献。这项研究的总体目标是了解大脑在其本地生物物理环境中的高应变率机制。第一阶段将集中于小变形和动态应变速率下的组织反应。宽带磁共振弹性实验将在来自多个大脑区域的脑组织样品上进行,以开发线性粘弹性组成型模型。将开发多效率模型,以融合观察到的响应与可用的窄带体内脑组织反应,以预测体内脑组织的线性粘弹性特性,以较大的负载频率。第二阶段将集中于大变形和极端应变速率下的组织反应。将进行准静态和动态机械测试,以开发粘性弹性组成型模型。将开发物理信息的多保真模型,以融合离体粘性 - 透明度响应与上一个阶段中特征的体内线性粘弹性响应。这项研究将通过对体内与体内组织机械的关系以及活体大脑的机械特性的第一个全景图产生有关在极端载荷条件下的机械特性的第一个全景图来大大提高我们对脑生物力学的理解。该项目共同资助了由生物力学和机械学研究(BMMB)计划(EPSC)竞争的计划(EPSTIS)(EPST)的竞争力(EPST)。法定使命,并使用基金会的知识分子优点和更广泛的影响标准通过评估被认为是宝贵的支持。
项目成果
期刊论文数量(0)
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Kshitiz Upadhyay其他文献
First Daytime Red‐Line Emission Measurements of the Stable Auroral Red (SAR) Arcs
稳定极光红 (SAR) 弧的首次白天红线发射测量
- DOI:
10.1029/2023gl106292 - 发表时间:
2024 - 期刊:
- 影响因子:5.2
- 作者:
Kshitiz Upadhyay;D. Pallamraju - 通讯作者:
D. Pallamraju
Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-based Machine Learning Approach.
人体头部形状对脑外伤风险的影响:基于高斯过程回归的机器学习方法。
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:1.2
- 作者:
Kshitiz Upadhyay;Roshan Jagani;Dimitris G. Giovanis;A. Alshareef;A. Knutsen;Curtis L. Johnson;Aaron Carass;P. Bayly;Michael D. Shields;K. T. Ramesh - 通讯作者:
K. T. Ramesh
Kshitiz Upadhyay的其他文献
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