An Ecosystem of Technology and Protocols for Adaptive Neuromodulation Research in Humans
人类自适应神经调节研究的技术和协议生态系统
基本信息
- 批准号:10516471
- 负责人:
- 金额:$ 117.59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-21 至 2026-08-31
- 项目状态:未结题
- 来源:
- 关键词:AchievementAddressAdoptionAffectAnimalsAreaBase of the BrainBasic ScienceBehavioralBrainCardiovascular DiseasesClinicalClinical ProtocolsClinical ResearchCommunicationCommunitiesComputer softwareConceptionsDataDevelopmentDevicesDiabetes MellitusDiagnosisDisabled PersonsDocumentationEcosystemEducational workshopEngineeringFeedbackGoalsHealth Care CostsHumanImplantInvestigationLeadMalignant NeoplasmsMental DepressionMental disordersMovement DisordersMusNervous system structureOperative Surgical ProceduresPainPerformancePersonsPhysiologyProtocols documentationResearchResistanceScientistSignal TransductionSiteSpinal cord injuryStrokeStructureSupport SystemSystemTechnologyTestingTimeTrainingUnited StatesWorkbasecanine modelclinical applicationcommunication aidexperimental studyimplantationimprovednervous system disorderneuroregulationneurotechnologynonhuman primatenovelnovel therapeuticsopen sourcerelating to nervous systemresearch clinical testingsuccesssymptomatic improvementtheories
项目摘要
Project Summary/Abstract
Neurological and psychiatric disorders affect millions of people in the United States and worldwide, and produce
a third of all health care costs. Recent research has produced encouraging evidence that adaptive neuromodulation
can induce nervous system plasticity that produces long-lasting improvements in certain neurological disorders
such as stroke. At the same time, it is becoming increasingly clear that the technologies that support these
demonstrations remain painfully inadequate and inaccessible for both research and clinical application: current
non-invasive technologies are typically imprecise; and current invasive technologies, which are more precise, are
currently only available with serious restrictions for human use. Moreover, all of the few existing neuromodulation
platforms for human use require substantial expertise in diverse areas of engineering, physiology, and regulatory
domains that is not available to most groups. This lack of availability of sufficiently capable and readily useable
neuromodulation technologies greatly impedes the development, application, and optimization of new adaptive
protocols for improving symptoms of devastating neurological and psychiatric disorders.
The purpose of the project proposed here is to address this critical issue by developing, validating, and widely
sharing with the community an easy-to-use adaptive neuromodulation ecosystem (comprised of technology and
protocols) that is optimized for the needs of invasive basic and clinical research. We will validate this ecosystem in
a canine model, and disseminate it with appropriate documentation to other scientists and clinicians through three
project-related test sites and three workshops. In accord with this objective, we will:
1. Develop a general-purpose hardware/software neuromodulation platform for invasive neuromodulation research
2. Develop and validate an ecosystem for adaptive neuromodulation research and clinical application
3. Disseminate this ecosystem of technologies and protocols
Achieving these three aims will create, validate, and disseminate the first comprehensive ecosystem that
facilitates the conception, development, and clinical application of invasive adaptive neuromodulation protocols.
We expect that the availability of this ecosystem will greatly increase activities in basic and clinical neuromodulation
research that will lead to new understanding of the neural underpinnings of normal and abnormal function and will
thereby accelerate the development of novel adaptive neuromodulation protocols to improve treatment for many
devastating neurological disorders.
项目总结/摘要
神经和精神疾病影响着美国和全世界数百万人,
三分之一的医疗费用。最近的研究已经产生了令人鼓舞的证据,适应性神经调节
可以诱导神经系统的可塑性,从而对某些神经系统疾病产生持久的改善
例如中风。与此同时,越来越清楚的是,支持这些技术的技术
目前的研究和临床应用仍然远远不够,
非侵入性技术通常是不精确的;而目前的侵入性技术,更精确,
目前仅可用于人类使用的严重限制。此外,所有现有的少数神经调节
人类使用的平台需要在工程学、生理学和管理学等不同领域的大量专业知识
大多数人无法使用的域名。缺乏足够的能力和易用的
神经调节技术极大地阻碍了新的自适应神经调节技术的开发、应用和优化。
改善严重神经和精神疾病症状的方案。
这里提出的项目的目的是通过开发、验证和广泛地
与社区分享易于使用的自适应神经调节生态系统(由技术和
协议),该协议针对侵入性基础和临床研究的需求进行了优化。我们将验证这个生态系统,
犬模型,并通过三个适当的文件传播给其他科学家和临床医生
与项目有关的试验场地和三个讲习班。根据雅阁,我们将:
1.开发用于有创神经调节研究的通用硬件/软件神经调节平台
2.开发和验证适应性神经调节研究和临床应用的生态系统
3.传播这种技术和协议生态系统
实现这三个目标将创建、验证和传播第一个全面的生态系统,
促进侵入性自适应神经调节协议的概念、开发和临床应用。
我们预计,该生态系统的可用性将大大增加基础和临床神经调节的活动
这项研究将导致对正常和异常功能的神经基础的新理解,
从而加速新的适应性神经调节方案的开发,
严重的神经系统疾病
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)
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Peter Brunner其他文献
Peter Brunner的其他文献
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{{ truncateString('Peter Brunner', 18)}}的其他基金
Non-invasive vagus nerve stimulation to mitigate subarachnoid hemorrhage induced inflammation
无创迷走神经刺激减轻蛛网膜下腔出血引起的炎症
- 批准号:
10665166 - 财政年份:2023
- 资助金额:
$ 117.59万 - 项目类别:
An Ecosystem of Technology and Protocols for Adaptive Neuromodulation Research in Humans
人类自适应神经调节研究的技术和协议生态系统
- 批准号:
10707462 - 财政年份:2022
- 资助金额:
$ 117.59万 - 项目类别:
International Workshop on Advances in Electrocorticography
皮质电图进展国际研讨会
- 批准号:
10077123 - 财政年份:2020
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000: Software Resource for Adaptive Neurotechnology Research
BCI2000:自适应神经技术研究软件资源
- 批准号:
10649719 - 财政年份:2019
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000: Software Resource for Adaptive Neurotechnology Research
BCI2000:自适应神经技术研究软件资源
- 批准号:
10336760 - 财政年份:2019
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000: Software Resource for Adaptive Neurotechnology Research
BCI2000:自适应神经技术研究软件资源
- 批准号:
9912872 - 财政年份:2019
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000: Software Resource for Adaptive Neurotechnology Research
BCI2000:自适应神经技术研究软件资源
- 批准号:
10071302 - 财政年份:2019
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000+: A Software Platform for Adaptive Neurotechnologies
BCI2000:自适应神经技术的软件平台
- 批准号:
10394429 - 财政年份:2018
- 资助金额:
$ 117.59万 - 项目类别:
BCI2000+: A Software Platform for Adaptive Neurotechnologies
BCI2000:自适应神经技术的软件平台
- 批准号:
10037665 - 财政年份:2018
- 资助金额:
$ 117.59万 - 项目类别:
Dynamics and Causal Functions of Large-Scale Cortical and Subcortical Networks
大规模皮层和皮层下网络的动力学和因果函数
- 批准号:
10291321 - 财政年份:2018
- 资助金额:
$ 117.59万 - 项目类别:
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