Extension of NEURON simulator for simulation of reaction-diffusion in neurons

用于模拟神经元反应扩散的神经模拟器的扩展

• 批准号: 10299041
• 负责人: William W Lytton
• 金额: $ 42.64万
• 依托单位: SUNY DOWNSTATE MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10299041
• 关键词: 3-Dimensional; Adoption; Alzheimer' s Disease; Amyloid; Bayesian Analysis; Biological; Biology; Biomedical Engineering; Blood; Brain; Brain Chemistry; Brain Diseases; Cells; Chemical Agents; Chemicals; Clinical; Communities; Complement; Complex; Computational Biology; Computers; Dendrites; Development; Differential Equation; Diffusion; Disease; Documentation; Edema; Education; Educational process of instructing; Educational workshop; Electrophysiology (science); Epilepsy; Equation; Extracellular Space; Failure; Functional disorder; Funding; Future; Gap Junctions; Gatekeeping; Genome; Heart; High Performance Computing; Homeostasis; Hormones; Human; Information Theory; Intracellular Space; Ischemia; Kinetics; Learning; Link; Manuals; Medical; Memory; Mental disorders; Modality; Modeling; Myocardial Infarction; Nerve; Nerve Degeneration; Nerve Fibers; Nervous system structure; Neurologic; Neurons; Neurosciences; Neurotransmitters; Organ; Oxygen; Pathology; Pattern Recognition; Performance; Persons; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacology; Play; Process; Proteome; Pythons; Reaction; Reading; Recovery; Research; Research Personnel; Rest; Role; Running; Savings; Second Messenger Systems; Signal Transduction; Speed; Stroke; Structural Models; Structure; Synapses; Synaptic Transmission; Systems Biology; Techniques; Thinking; Time; Tissues; Toxin; Travel; Trees; Vertebral column; Work; application programming interface; artificial neural network; autism spectrum disorder; base; body system; brain dysfunction; brain research; chemical reaction; computational neuroscience; computer science; experimental study; improved; in vivo; interoperability; meetings; multi-scale modeling; neglect; neocortical; nervous system disorder; neurotechnology; novel; online course; online tutorial; personalized medicine; postsynaptic; pressure; presynaptic; reconstruction; relating to nervous system; reuptake; simulation; syntax; synuclein; tau Proteins; tool; transcriptome

Development of simulation bioengineering techniques in medical neuroscience has been limited due to computational neuroscience's focus on the higher capacities of humans, such as the ability to play chess or go. That has led to the notion that the brain can best be understood by recourse to the concepts of computer science: artificial neural networks, information theory, Bayesian inference, pattern recognition, etc. Whether or not these tools are sufficient for understanding human neocortical function, they are clearly not sufficient for understanding the nervous system dysfunction seen in neurological and psychiatric pathology. Brain disease, like diseases of other organ systems, is disease of biological tissue, and must eventually consider energetics and oxygenation, blood and brain pressures, as well as chemical reactions and diffusion of toxins and pharmaceuticals. Such full-organ simulation will require linkages to other simulators. Through such linkages, as well as through internal extensions, we have been extending the widely-used NEURON simulator to handle reaction-diffusion in neural tissue in order to better understand brain signaling, neurodegenerative toxic cascades, and drug effects. For the current funding period we will further augment NEURON's NRxD module through 4 Aims: 1. Improve synaptic modeling techniques by considering presynaptic volume, cleft and postsynaptic volume together to handle ionotropic synapses, metabotropic synapses, gap junctions and complex combination synapses; along with reuptake, diffusion, electrodiffusion, neurotransmitters, second messengers and retrograde neurotransmitters in a coordinated way. 2. Allow more rapid and more extensive exploration of parameter space by improving simulation speed and by allowing full state variable saving for improved simulation initialization and recovery from high-performance computing failures. 3. Develop both Python-based and socket-based application programming interfaces (APIs) for easier linkage with other simulators, including for electrodiffusion and for various types of stochastic simulation. 4. Continue package dissemination and education in order to get more computational and experimental NRxD users. We will continue to offer twice-yearly tutorials, and to sponsor additional workshops at Computational Neuroscience and at other meetings. We will integrate online tutorials with the documentation to provide both Programmer's Reference and Biological Reference online manuals. We will develop a set of video tutorials associated with these that will eventually be linked together to make an online course. Overall, we expect that our novel simulation neurotechnology will be of increasing use and utilization both for research use, and for future clinical adoption in personalized medicine.

由于以下原因，医学神经科学中的模拟生物工程技术的发展受到限制 计算神经科学关注人类的更高能力，例如玩耍的能力 下棋或围棋。这导致了这样一种观念：可以通过求助于大脑来最好地理解大脑。 计算机科学概念：人工神经网络、信息论、贝叶斯推理、 模式识别等。这些工具是否足以理解人类 新皮质功能，它们显然不足以理解神经系统 神经和精神病理学中所见的功能障碍。脑部疾病，就像其他疾病一样 器官系统，是生物组织的疾病，最终必须考虑能量学和 氧合作用、血液和脑压，以及化学反应和毒素和物质的扩散 药品。这种全器官模拟需要与其他模拟器连接。通过这样的 链接以及通过内部扩展，我们一直在扩展广泛使用的 NEURON 模拟器处理神经组织中的反应扩散，以便更好地了解大脑 信号传导、神经退行性毒性级联反应和药物效应。在当前的资助期内，我们 将通过 4 个目标进一步增强 NEURON 的 NRxD 模块： 1. 改进突触建模技术 通过同时考虑突触前体积、裂隙和突触后体积来处理离子型 突触、代谢性突触、间隙连接和复杂的组合突触；连同 再摄取、扩散、电扩散、神经递质、第二信使和逆行 神经递质以协调的方式。 2. 允许更快速、更广泛的探索 通过提高仿真速度和允许完整状态变量保存来实现参数空间 改进了模拟初始化和高性能计算故障的恢复。 3. 更轻松地开发基于 Python 和基于套接字的应用程序编程接口 (API) 与其他模拟器连接，包括电扩散和各种类型的随机 模拟。 4. 继续进行软件包传播和教育，以获得更多的计算和知识 实验性 NRxD 用户。我们将继续提供每年两次的教程，并赞助 计算神经科学和其他会议上的额外研讨会。我们将在线整合 教程和文档提供程序员参考和生物参考 在线手册。我们将开发一组与这些相关的视频教程，最终将 链接在一起以制作在线课程。总的来说，我们期望我们的新颖模拟 神经技术将越来越多地用于研究用途和未来 个性化医疗的临床采用。