MATHEMATICAL MODELING AND SIMULATION

数学建模与仿真

• 批准号: 8172256
• 负责人: Rob S. MacLeod
• 金额: $ 17.38万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8172256
• 关键词: Acceleration; Address; Architecture; Area; Behavior; Body Surface; Brain; Cardiac; Cell membrane; Characteristics; Communities; Computer Retrieval of Information on Scientific Projects Database; Computer Simulation; Computer software; Consensus; Deep Brain Stimulation; Development; Disease; Electric Countershock; Electrophysiology (science); Epilepsy; Functional disorder; Funding; Future; Goals; Grant; Head; Heart; Institution; Ion Channel; Knowledge; Measurement; Microscopic; Modeling; Myocardial Ischemia; Myocardial tissue; Nature; Pharmacy (field); Process; Publishing; Research; Research Activity; Research Personnel; Resources; Simulate; Solutions; Source; Speed; Stream; Structure; Tissue Model; Tissues; Translating; Translations; United States National Institutes of Health; Work; base; cell behavior; improved; multi-scale modeling; response; simulation; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. MATHEMATICAL MODELING AND SIMULATION Subproject Description As a Center, we have established expertise in the area of simulation in bioelectric fields, have built on that expertise in the current funding period, and propose to continue to make this form of simulation a centerpiece of our future research activities. At the start of the Center our focus was on passive electrical characteristics of the torso and head and their response to endogenous bioelectric sources (the heart and brain); we solved both forward problems, based on known sources, as well as inverse problems, in which we sought to identify and localize bioelectric sources from measurements on (or outside) the body surface. We have continued this research thrust through the current year and propose to continue it in the next funding cycle, working closely with collaborators. In recent years, we have also begun to simulate bioelectric activity itself and thus to study the nature of bioelectric sources; these sources are highly dynamic and increased knowledge of their behavior will help improve our ability to predict the consequences of their function and dysfunction in disease. We propose to continue this research, with emphasis on simulating the effects of myocardial ischemia and defibrillation on the heart and epilepsy and deep brain stimulation in the brain. In order to translate the discoveries and computational developments within the Center to the broader biomedical user community, we will continue to develop, publish, release, and support software that will incorporate models of dynamic bioelectric sources as well as the tools with which to create efficient solutions to the associated forward and inverse problems. One application of the simulation of bioelectric activity has been in the computation of the spread of excitation in microscopic models of myocardial tissue. The goal of this research was to address a longstanding gap in the multiscale modeling of cardiac electrophysiology between the very evolved and well-characterized behavior of cardiac cell membranes and the simulation of electrical activity in the whole heart. Simulation of the heart has advanced mainly because there exist models at each of the meaningful scales from stochastic models of ion channels to the whole heart and torso. However, there is a need for simplification at each transition of scale, and hence a requirement that results at one scale are established as an associated expression at the next scale. For example, a model of tissue must be able to incorporate the effects of changes in the behavior of the cell in order to mimic or predict pathophysiology or the mechanisms of pharmaceutics. It is also essentialand until recently a significant omissionin this translation across scales, that changes in microscopic structure find expression in tissue level models. We have begun to address this omission. In addition, within this TRD we have begun to explore the use of acceleration hardware such as graphical processing units, GPU's, and, in general, streaming architectures for use in biomedical simulation. As the speed and efficiency of GPU's grows at rates even faster than those of conventional central processing units (CPU's), there is a growing consensus that the streaming architecture embodied in most modern graphics processors has inherent advantages in scalability.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 数学建模与仿真 子项目描述 作为一个中心，我们在生物电场模拟领域建立了专业知识，并在此基础上建立了以下领域的专业知识： 当前的资助期限，并建议继续将这种形式的模拟作为我们未来研究的核心 活动。在中心成立之初，我们的重点是躯干和头部的被动电气特性及其 对内源性生物电源（心脏和大脑）的反应；我们根据已知的情况解决了两个前向问题 源，以及反问题，其中我们试图通过测量来识别和定位生物电源 在身体表面（或外部）。我们今年继续开展这项研究工作，并建议 在下一个融资周期中继续与合作者密切合作。 近年来，我们也开始模拟生物电活动本身，从而研究生物电的本质 来源；这些来源是高度动态的，增加对其行为的了解将有助于提高我们的能力 预测它们在疾病中的功能和功能障碍的后果。我们建议继续这项研究， 强调模拟心肌缺血和除颤对心脏和癫痫及脑深部的影响 对大脑的刺激。为了将中心的发现和计算发展转化为 为了更广泛的生物医学用户社区，我们将继续开发、发布、发布和支持软件，这些软件将 结合动态生物电源模型以及用于创建有效解决方案的工具 相关的正向和逆向问题。 生物电活动模拟的一项应用是计算激发的传播 心肌组织的显微模型。 这项研究的目标是解决多尺度方面长期存在的差距 在心肌细胞的高度进化和良好表征的行为之间建立心脏电生理学模型 膜和整个心脏电活动的模拟。 心脏模拟主要先进 因为从离子通道的随机模型到整个心脏的每个有意义的尺度都存在模型 和躯干。 然而，每次规模转变都需要简化，因此需要结果 在一个尺度上建立为下一个尺度上的关联表达式。 例如，组织模型必须能够 纳入细胞行为变化的影响，以模拟或预测病理生理学或 药剂学机制。 这也是至关重要的，直到最近，这个翻译中还存在重大遗漏。 尺度，微观结构的变化在组织水平模型中得到表达。 我们已经开始解决这个问题 省略。 此外，在这个TRD中我们已经开始探索加速硬件的使用，例如图形处理 用于生物医学模拟的单元、GPU 以及一般的流式架构。随着速度和效率 GPU 的增长速度甚至比传统中央处理单元 (CPU) 还要快， 人们一致认为，大多数现代图形处理器所体现的流式架构在以下方面具有固有的优势： 可扩展性。