Imaging and Neural Circuits Core
成像和神经电路核心
基本信息
- 批准号:10152569
- 负责人:
- 金额:$ 49.05万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-07-01 至 2024-04-30
- 项目状态:已结题
- 来源:
- 关键词:Animal ModelAnimalsBehaviorBehavior ControlBrainBrain imagingCalciumCellsCessation of lifeCodeCommunitiesCore FacilityCuesData AnalysesData ScienceData SetDetectionDevelopmentDrug abuseEducational workshopEndoscopyEpidemicExposure toFundingGoalsImageInfrastructureLaboratoriesLearningLightLogisticsMethodologyModelingMolecularNational Institute of Drug AbuseNeuronsOpiate AddictionOpioidOpioid AnalgesicsOpsinOpticsPharmaceutical PreparationsPhotometryPilot ProjectsPositioning AttributeResearchResearch PersonnelResolutionResourcesRewardsRoleSensorySiteStimulusStressSubstance abuse problemSystemTechniquesTechnologyTherapeutic UsesTimeTrainingUnited StatesUnited States National Institutes of HealthUniversitiesWashingtonWireless TechnologyWorkaddictionawakebasecell typecomputational neurosciencecomputerized toolsdata analysis pipelineillicit opioidimaging approachimaging facilitiesin vivoin vivo calcium imagingin vivo imaginginnovative technologiesinsightmeetingsneural circuitneurotechnologynovel strategiesopen dataopioid abuseopioid use disorderoptogeneticsprescription opioid abuseranpirnaserelating to nervous systemremote controlsensorspatiotemporaltooltwo photon microscopytwo-photonvoltage
项目摘要
Summary:
Opioid abuse is a major epidemic in the United States. In 2017 alone, abuse of prescription and illicit opioids
resulted in over 60,000 deaths. The transition from therapeutic use of opioid pain relievers to destructive
substance abuse occurs, in part, through maladaptive activation of mesocorticolimbic brain circuits. How these
various sensory, reward, and stress neural circuits act at the systems, cellular and molecular levels remain
poorly understood. As we work to advance our understanding of the development of opioid use disorder, we
need to develop fundamental insights into how opioid circuits function in reward and aversion. In addition, we
need to learn how these circuits are modulated, altered, and adapted over time in animal models of opioid
addiction. We aim to leverage the diverse team of investigators at UW towards answering these questions. We
propose to establish an advanced Imaging and Addiction Neural Circuits Core (INCC) to provide UW addiction
researchers, neuroscientists, and the wider community with a suite of advanced neurotechnologies, for in vivo
neural circuit perturbation and analysis. Beyond building and continually renewing a state-of-the-art imaging
facility, a principal role of the Core will be to train the NIDA P30 Investigators in its uses in order to enhance the
research of their NIDA funded projects. We will also disseminate these tools to the larger research community
by providing on-site training. Collectivity, these resources will enable researchers at UW and beyond to identify
and correct neurocircuit maladaptation observed in opioid addiction models.
总结:
阿片类药物滥用是美国的一个主要流行病。仅在2017年,滥用处方药和非法阿片类药物
导致超过六万人死亡从阿片类止痛药的治疗性使用到破坏性使用的转变
药物滥用部分是由于中皮层边缘脑回路的不适应激活而发生的。如何将这些
各种感觉、奖赏和压力神经回路在系统、细胞和分子水平上起作用,
不太了解。随着我们努力推进对阿片类药物使用障碍发展的理解,我们
我们需要对阿片类药物回路在奖励和厌恶中的作用有基本的了解。另外我们
我们需要了解这些回路是如何在阿片类药物的动物模型中随着时间的推移而调节、改变和适应的
成瘾我们的目标是利用UW多元化的调查团队来回答这些问题。我们
建议建立一个先进的成像和成瘾神经回路核心(INCC),以提供UW成瘾
研究人员、神经科学家和更广泛的社区,利用一套先进的神经技术,
神经回路扰动和分析。除了构建和不断更新最先进的成像技术之外,
核心的一个主要作用是培训NIDA P30调查人员使用该设施,以提高
研究其NIDA资助的项目。我们还将向更大的研究社区传播这些工具
提供现场培训。总的来说,这些资源将使研究人员在华盛顿大学和超越,以确定
并纠正阿片类药物成瘾模型中观察到的神经回路适应不良。
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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Charles Chavkin其他文献
Charles Chavkin的其他文献
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{{ truncateString('Charles Chavkin', 18)}}的其他基金
University of Washington Center of Excellence in Opioid Addiction Research
华盛顿大学阿片类药物成瘾研究卓越中心
- 批准号:
10611870 - 财政年份:2019
- 资助金额:
$ 49.05万 - 项目类别:
University of Washington Center of Excellence in Opioid Addiction Research
华盛顿大学阿片类药物成瘾研究卓越中心
- 批准号:
10152567 - 财政年份:2019
- 资助金额:
$ 49.05万 - 项目类别:
University of Washington Center of Excellence in Opioid Addiction Research
华盛顿大学阿片类药物成瘾研究卓越中心
- 批准号:
10394246 - 财政年份:2019
- 资助金额:
$ 49.05万 - 项目类别:
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