Mapping the developing infant connectome
绘制发育中的婴儿连接组图
基本信息
- 批准号:10413004
- 负责人:
- 金额:$ 44.57万
- 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:2019-09-01 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAdultAge-MonthsAnatomyAreaBenchmarkingBirthBrainBrain imagingCharacteristicsCodeCommunitiesComplexCross-Sectional StudiesDataData SetDevelopmentDevelopmental ProcessDiffusionDiffusion Magnetic Resonance ImagingDisadvantagedFunctional Magnetic Resonance ImagingGoalsGraphGrowthImageIndividualInfantInfant DevelopmentLeadLifeLightLongitudinal StudiesMagnetic Resonance ImagingMapsMathematicsMeasuresMethodologyMethodsModelingNeurodevelopmental DisorderNeurosciencesNodalPrincipal Component AnalysisPropertyResearchResearch Project GrantsRestSample SizeSamplingScanningScientific InquiryShapesSpecific qualifier valueStatistical Data InterpretationSystemTechniquesTestingTimeVariantage groupanalytical toolbasebrain researchcognitive developmentcognitive functionconnectomecourse developmentcurve fittingdesigndisabilityfrontiergraph theoryimprovedindividual variationinfancyinnovationinsightlongitudinal analysislongitudinal designmethod developmentneural growthneuroimagingneuropsychiatrynovelpostnatalpostnatal developmentprospectiverate of changetool
项目摘要
PROJECT SUMMARY/ABSTRACT
The overarching goal of this proposal is to develop new and innovative analytic tools for longitudinal infant
brain research and to leverage these tools to chart the development of infant brain networks during the first 6
months of life, a period of unparalleled postnatal growth and change. Describing the developmental trajectory
of brain systems during this formative period has the potential to provide groundbreaking insights into major
areas of scientific inquiry, including the identification of brain systems that underlie the development of
cognitive functions, the discovery of how structural and functional network specializations arise, and the
identification of brain networks that contribute to neuropsychiatric illness. However, despite this potential,
longitudinal studies of infant brain development are still nascent, and prevailing analytic tools—largely
designed for cross-sectional analyses of adult data—are ill-suited for fully capturing fast-pace developmental
processes during infancy. This proposal aims to 1) develop innovative analytic tools that are specifically
designed to address challenges inherent to longitudinal infant brain research; 2) leverage these tools to
examine graph theoretic measures of brain network development in typical infancy; and 3) disseminate these
tools and approaches to the broader research community. Methods development will focus on two key areas:
registration (the approach for transforming individual brain images to a common space) and statistical analysis
of longitudinal data (the approach for constructing and analyzing growth curves of brain development).
Methods development and analyses will be conducted on anatomical, diffusion tensor imaging and resting-
state functional MRI data collected from infants at three longitudinal time points between birth and 6 months of
age. Aim 1 of this proposal is to develop and validate a novel hierarchical, tensor-based registration approach,
designed to handle the challenges associated with registering highly heterogeneous images, a characteristic of
longitudinal infant data. Aim 2 will improve an already state-of-the-art approach for the analysis of longitudinal
data and pioneer its application to the case of longitudinal neuroimaging data. Finally, Aim 3 will leverage these
methods to produce a temporally-precise mapping of typical growth curves of brain network development in the
first postnatal months, providing a benchmark against which to interpret and understand how alternate
trajectories of brain development can lead to disability. These aims will help advance the frontier of studies of
brain development into early infancy, a formative, and yet relatively uncharted, period of development.
项目总结/文摘
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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VINCE D CALHOUN其他文献
VINCE D CALHOUN的其他文献
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{{ truncateString('VINCE D CALHOUN', 18)}}的其他基金
ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits
ENIGMA-COINSTAC:价系统脑回路的先进全球跨诊断分析
- 批准号:
10410073 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuit
ENIGMA-COINSTAC:价系统脑回路的先进全球跨诊断分析
- 批准号:
10656608 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain CircuitsPD
ENIGMA-COINSTAC:价系统脑回路的先进全球跨诊断分析PD
- 批准号:
10252236 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers
物质使用行为及其大脑生物标志物的分散宏观和微观基因与环境相互作用分析
- 批准号:
10197867 - 财政年份:2019
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$ 44.57万 - 项目类别:
A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers
物质使用行为及其大脑生物标志物的分散宏观和微观基因与环境相互作用分析
- 批准号:
10443779 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers
物质使用行为及其大脑生物标志物的分散宏观和微观基因与环境相互作用分析
- 批准号:
9811339 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
Flexible multivariate models for linking multi-scale connectome and genome data in Alzheimer's disease and related disorders
用于连接阿尔茨海默病和相关疾病的多尺度连接组和基因组数据的灵活多变量模型
- 批准号:
10157432 - 财政年份:2019
- 资助金额:
$ 44.57万 - 项目类别:
A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers
物质使用行为及其大脑生物标志物的分散宏观和微观基因与环境相互作用分析
- 批准号:
10645089 - 财政年份:2019
- 资助金额:
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COINSTAC:松散耦合数据的去中心化、可扩展分析
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9268713 - 财政年份:2015
- 资助金额:
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COINSTAC 2.0: decentralized, scalable analysis of loosely coupled data
COINSTAC 2.0:松散耦合数据的去中心化、可扩展分析
- 批准号:
10622017 - 财政年份:2015
- 资助金额:
$ 44.57万 - 项目类别:
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