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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
项目摘要:行政核心 基于神经科学的心理健康评估和预测的管理核心(NeuroMAP) 科布雷将继续提供以下具体目标:(1)方案发展的基础设施 和监督;(2)研究项目负责人综合培训和指导计划;(3) RPL和试点项目调查员(PPI)日常运作的业务支持;以及(4)管理 试点项目计划。NeuroMAP管理核心的基本前提是一个支持性框架 有必要建立一支强大的、跨学科的、翻译的初级调查团队,以过渡到R- 具有竞争力的研究人员。NeuroMAP第一阶段管理核心成就由 对领导班子和咨询委员会的战略/科学监督包括:(1)基金会 在1-3年级期间为5名残疾儿童提供支助基地和培训平台,在4-5年级为3名残疾儿童建立支持性基地和培训平台,以及 8项绩效指标;(2)成功地将具有丰富R01级筹资经验的外部导师与RPL相匹配 促进职业发展;(3)4名由NeuroMAP调查员资助的R01(2名RPL和2名PPI) 和PPI提交的14份拨款申请;(4)积极将NeuroMAP融入当地学术 通过俄克拉荷马州立大学、俄克拉荷马大学和塔尔萨大学参与的社区 (5)成功招募初级调查人员申请试点项目。在第一阶段,空调 提出了多项改善NeuroMAP第二阶段的建议,其中包括:(1)更严格地关注能够 根据RPL数据申请;(2)增加统计咨询;(3)扩大生物评估 超越神经成像;(4)考虑为RPL和PPI提供本地导师。因此,第二阶段添加了 以下基础设施发展:(1)过去获得R01级资金的NeuroMAP RPL和PPI将 现在担任当前RPL的内部导师;(2)第一阶段NeuroMAP多层核心数据的可用性 (神经成像、行为、问卷、临床评估)用于新的试点项目,从而促进 未来R01拨款申请的假设检验;(3)成功招聘韦斯利·汤普森博士, 在R01级资助方面有成功记录的统计员,将指导RPL和PPI进行数据分析 规划/执行;以及(4)扩大培训机会,将涉及血液的研究包括在内 生物标记物和遗传数据的处理和分析。实现行政核心意志的这些目标 扩大NeuroMAP主题所需的大量独立调查人员,以继续 接受美国国立卫生研究院的资助并确定新的治疗目标,以减轻个人、经济和社会负担 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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The Center for Neuroscience-based Mental Health Assessment and Prediction (NeuroMAP)
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