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
基本信息
- 批准号:10434955
- 负责人:
- 金额:$ 41.09万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:3-DimensionalAdoptionAlzheimer&aposs DiseaseAmyloidBayesian AnalysisBiologicalBiologyBiomedical EngineeringBloodBrainBrain ChemistryBrain DiseasesCellsChemical AgentsChemicalsClinicalCommunitiesComplementComplexComputational BiologyComputersDendritesDevelopmentDifferential EquationDiffusionDiseaseDocumentationEdemaEducationEducational process of instructingEducational workshopElectrophysiology (science)EpilepsyEquationExtracellular SpaceFailureFunctional disorderFundingFutureGap JunctionsGatekeepingGenomeHeartHigh Performance ComputingHomeostasisHormonesHumanInformation TheoryIntracellular SpaceIschemiaKineticsLearningLinkManualsMedicalMemoryMental disordersModalityModelingMyocardial InfarctionNerveNerve DegenerationNerve FibersNervous system structureNeurologicNeuronsNeurosciencesNeurotransmittersOrganOxygenPathologyPattern RecognitionPerformancePersonsPharmaceutical PreparationsPharmacologic SubstancePharmacologyPlayProcessProteomePythonsReactionReadingRecoveryResearchResearch PersonnelRestRoleRunningSavingsSecond Messenger SystemsSignal TransductionSpeedStrokeStructureSynapsesSynaptic TransmissionSystems BiologyTechniquesThinkingTimeTissuesToxinTravelTreesVertebral columnWorkapplication programming interfaceartificial neural networkautism spectrum disorderbasebody systembrain dysfunctionbrain researchchemical reactioncomputational neurosciencecomputer scienceexperimental studyimprovedin vivointeroperabilitymeetingsmulti-scale modelingneglectneocorticalnervous system disorderneurotechnologynovelonline courseonline tutorialpersonalized medicinepostsynapticpressurepresynapticreconstructionrelating to nervous systemreuptakesimulationsyntaxsynucleintau Proteinstooltranscriptome
项目摘要
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.
模拟生物工程技术在医学神经科学中的发展受到限制,
计算神经科学的重点是人类的更高的能力,如玩的能力,
象棋或围棋。这导致了这样一种观点,即最好通过求助于大脑来了解大脑。
计算机科学的概念: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
在神经和精神病理学中观察到的功能障碍。脑疾病,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,
氧合,血液和脑压,以及化学反应和毒素的扩散,
大药厂这种全器官模拟将需要与其他模拟器的连接。通过这样
链接,以及通过内部扩展,我们一直在扩展广泛使用的神经元
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、神经变性毒性级联和药物作用。在当前的融资期内,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
通过将突触前体积、间隙和突触后体积一起考虑来处理离子型
突触、代谢型突触、缝隙连接和复杂组合突触;沿着
再摄取、扩散、电扩散、神经递质、第二信使和逆行
神经递质的协调作用。2.允许更快速和更广泛地探索
参数空间,通过提高仿真速度,并允许充分的状态变量保存,
改进的模拟初始化和从高性能计算故障中恢复。3.
开发基于Python和基于套接字的应用程序编程接口(API),
与其他模拟器的连接,包括用于电扩散和用于各种类型的随机
仿真4.继续软件包的传播和教育,以获得更多的计算和
实验NRxD用户。我们将继续提供每年两次的教程,并赞助
在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
提供程序员参考和生物学参考的教程和文档
在线手册。我们将开发一套与这些相关的视频教程,
连接在一起,形成一个在线课程。总的来说,我们希望我们的新模拟
神经技术将越来越多地用于研究用途和未来用途,
个性化医疗的临床应用。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
William W Lytton其他文献
Multiscale modeling of cortical information flow in Parkinson's disease
- DOI:
10.1186/1471-2202-14-s1-o21 - 发表时间:
2013-07-08 - 期刊:
- 影响因子:2.300
- 作者:
Cliff C Kerr;Sacha J van Albada;Samuel A Neymotin;George L Chadderdon III;Peter A Robinson;William W Lytton - 通讯作者:
William W Lytton
Transformation of inputs in a model of the rat hippocampal CA1 network
- DOI:
10.1186/1471-2202-11-s1-p56 - 发表时间:
2010-07-20 - 期刊:
- 影响因子:2.300
- 作者:
Andrey V Olypher;William W Lytton;Astrid A Prinz - 通讯作者:
Astrid A Prinz
Ih modulates theta rhythm and synchrony in computer model of CA3
- DOI:
10.1186/1471-2202-13-s1-p80 - 发表时间:
2012-07-16 - 期刊:
- 影响因子:2.300
- 作者:
Markus M Hilscher;Thiago Moulin;Yosef Skolnick;William W Lytton;Samuel A Neymotin - 通讯作者:
Samuel A Neymotin
Interlaminar Granger causality and alpha oscillations in a model of macaque cortex
- DOI:
10.1186/1471-2202-12-s1-p208 - 发表时间:
2011-07-18 - 期刊:
- 影响因子:2.300
- 作者:
Cliff C Kerr;Jue Mo;Samuel Neymotin;Mingzhou Ding;William W Lytton - 通讯作者:
William W Lytton
Parallelizing large networks using NEURON-Python
- DOI:
10.1186/1471-2202-16-s1-p151 - 发表时间:
2015-12-18 - 期刊:
- 影响因子:2.300
- 作者:
Alexandra H Seidenstein;Robert A McDougal;Michael L Hines;William W Lytton - 通讯作者:
William W Lytton
William W Lytton的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('William W Lytton', 18)}}的其他基金
Microconnectomics of neocortex: a multiscale computer model
新皮质微连接组学:多尺度计算机模型
- 批准号:
8926428 - 财政年份:2014
- 资助金额:
$ 41.09万 - 项目类别:
Microconnectomics of neocortex: a multiscale computer model
新皮质微连接组学:多尺度计算机模型
- 批准号:
8743695 - 财政年份:2014
- 资助金额:
$ 41.09万 - 项目类别:
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:
9893029 - 财政年份:2010
- 资助金额:
$ 41.09万 - 项目类别:
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:
10615791 - 财政年份:2010
- 资助金额:
$ 41.09万 - 项目类别:
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 - 财政年份:2010
- 资助金额:
$ 41.09万 - 项目类别:
THALAMOCORTICAL NEURON DYNAMICS AND ABSENCE EPILEPSY
丘脑皮质神经元动力学与失神性癫痫
- 批准号:
2270191 - 财政年份:1993
- 资助金额:
$ 41.09万 - 项目类别:
相似海外基金
WELL-CALF: optimising accuracy for commercial adoption
WELL-CALF:优化商业采用的准确性
- 批准号:
10093543 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
Collaborative R&D
Investigating the Adoption, Actual Usage, and Outcomes of Enterprise Collaboration Systems in Remote Work Settings.
调查远程工作环境中企业协作系统的采用、实际使用和结果。
- 批准号:
24K16436 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Unraveling the Dynamics of International Accounting: Exploring the Impact of IFRS Adoption on Firms' Financial Reporting and Business Strategies
揭示国际会计的动态:探索采用 IFRS 对公司财务报告和业务战略的影响
- 批准号:
24K16488 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
EU-Funded
Assessing the Coordination of Electric Vehicle Adoption on Urban Energy Transition: A Geospatial Machine Learning Framework
评估电动汽车采用对城市能源转型的协调:地理空间机器学习框架
- 批准号:
24K20973 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 41.09万 - 项目类别:
EU-Funded
Our focus for this project is accelerating the development and adoption of resource efficient solutions like fashion rental through technological advancement, addressing longer in use and reuse
我们该项目的重点是通过技术进步加快时装租赁等资源高效解决方案的开发和采用,解决更长的使用和重复使用问题
- 批准号:
10075502 - 财政年份:2023
- 资助金额:
$ 41.09万 - 项目类别:
Grant for R&D
Engage2innovate – Enhancing security solution design, adoption and impact through effective engagement and social innovation (E2i)
Engage2innovate — 通过有效参与和社会创新增强安全解决方案的设计、采用和影响 (E2i)
- 批准号:
10089082 - 财政年份:2023
- 资助金额:
$ 41.09万 - 项目类别:
EU-Funded
De-Adoption Beta-Blockers in patients with stable ischemic heart disease without REduced LV ejection fraction, ongoing Ischemia, or Arrhythmias: a randomized Trial with blinded Endpoints (ABbreviate)
在没有左心室射血分数降低、持续性缺血或心律失常的稳定型缺血性心脏病患者中停用β受体阻滞剂:一项盲法终点随机试验(ABbreviate)
- 批准号:
481560 - 财政年份:2023
- 资助金额:
$ 41.09万 - 项目类别:
Operating Grants
Collaborative Research: SCIPE: CyberInfrastructure Professionals InnoVating and brOadening the adoption of advanced Technologies (CI PIVOT)
合作研究:SCIPE:网络基础设施专业人员创新和扩大先进技术的采用 (CI PIVOT)
- 批准号:
2321091 - 财政年份:2023
- 资助金额:
$ 41.09万 - 项目类别:
Standard Grant