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NeuroMAP Phase II - Administrative Core

NeuroMAP Phase II - Administrative Core
NeuroMAP 第二阶段 - 管理核心
批准号:
10711135
负责人:
MARTIN P. PAULUS
金额:
$65.18万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2028-06-30

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中文摘要
翻译
项目概要:行政核心 基于神经科学的心理健康评估和预测管理核心(NeuroMAP) COBRE将继续提供以下具体目标:(1)方案发展的基础设施 (2)研究项目负责人(RPL)的综合培训和指导计划;(3) 为过往资历研究计划及先导计划研究员的日常运作提供运作支援;及(4)管理 试点项目方案。NeuroMAP管理核心的基本前提是, 有必要建立一个强大的,跨学科的,初级研究人员的翻译团队,以过渡到R- 有竞争力的研究人员。NeuroMAP第一阶段行政核心成就由 领导团队和咨询委员会(AC)的战略/科学监督包括:(1)基础 在第1-3年为5个RPL提供支持基础和培训平台,在第4-5年为3个RPL提供支持基础和培训平台, 8个PPI;(2)成功地将具有丰富R 01级供资经验的外部导师与RPL配对 促进职业发展;(3)NeuroMAP研究者资助的4个R 01(2个RPL和2个PPI) 和14个PPI提交的资助申请;(4)NeuroMAP积极融入当地学术 通过俄克拉荷马州州立大学、俄克拉荷马州大学和塔尔萨大学的参与, (5)成功招募初级研究员申请先导计划。在第一阶段,AC 提出了各种建议,以改善NeuroMAP第二阶段,其中包括:(1)更密切地关注赠款, 基于RPL数据申请;(2)增加统计咨询;(3)扩大生物评估 (4)考虑RPL和PPI的当地导师。因此,第二阶段增加了 以下基础设施的发展:(1)过去的NeuroMAP RPL和PPI谁赢得了R 01级的资金将 现在担任当前RPL的内部导师;(2)I期NeuroMAP多级核心数据的可用性 (神经影像学,行为,问卷调查,临床评估)的新试点项目,从而促进 假设检验未来的R 01赠款申请;(3)成功招聘博士韦斯利汤普森, 具有R 01级资助成功记录的统计学家,将在数据分析中指导RPL和PPI 规划/执行;以及(4)扩大培训机会,包括涉及血液的研究 生物标志物和遗传数据处理和分析。实现行政核心的这些目标将 扩大NeuroMAP主题所需的独立调查人员的临界质量, 接受NIH的资助,并确定新的治疗目标,以减少个人,财政和社会负担, 情绪和焦虑症
英文摘要
PROJECT SUMMARY: Administrative Core The Administrative Core for Neuroscience-based Mental Health Assessment and Prediction (NeuroMAP) CoBRE will continue to provide the following specific aims: (1) infrastructure for programmatic development and oversight; (2) an integrated training and mentoring plan for Research Project Leaders (RPLs); (3) operational support of RPL and Pilot Project Investigator (PPI) day-to-day operations; and (4) management of the Pilot Project program. The basic premise of NeuroMAP Administrative Core is that a supportive framework is necessary to create a strong, interdisciplinary, translational team of junior investigators to transition to R- level competitive researchers. NeuroMAP Phase I Administrative Core accomplishments facilitated by the strategic/scientific oversight of the Leadership Team and Advisory Committee (AC) include: (1) the foundation of a supportive base and training platform for five RPLs during Years 1-3, three RPLs during Years 4-5, and eight PPIs; (2) successful matching of External Mentors with extensive R01-level funding experience to RPLs to facilitate career development; (3) four funded R01s by NeuroMAP investigators (two RPLs and two PPIs) and 14 grant applications submitted by PPIs; (4) active integration of NeuroMAP into the local academic community via participation from Oklahoma State University, University of Oklahoma, and University of Tulsa faculty; and (5) successful recruitment of junior investigators to apply for Pilot Projects. During Phase I, the AC made various suggestions to improve NeuroMAP Phase II, which included: (1) tighter focus on grants that can be applied for based on RPL data; (2) increased statistical consultation; (3) expanding biological assessments beyond neuroimaging; (4) consideration of local mentors for RPLs and PPIs. As a result, Phase II adds the following infrastructure developments: (1) past NeuroMAP RPLs and PPIs who earned R01-level funding will now serve as Internal Mentors to current RPLs; (2) availability of Phase I NeuroMAP multilevel Core data (neuroimaging, behavior, questionnaires, clinical assessments) for new Pilot Projects, thereby facilitating hypothesis testing for future R01 grant applications; (3) successful recruitment of Dr. Wesley Thompson, a statistician with a successful track record of R01-level funding who will guide RPLs and PPIs in data analysis planning/execution; and (4) expansion of training opportunities to include research involving blood-based biomarker and genetic data processing and analysis. Accomplishing these aims of the Administrative Core will extend the critical mass of independent investigators necessary for the theme of NeuroMAP to continue to receive NIH funding and identify new treatment targets to reduce the personal, financial and societal burden of mood and anxiety disorders.
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Project 1: TBD
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Administrative Core
The Center for Neuroscience-based Mental Health Assessment and Prediction (NeuroMAP)
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