Inter-modal Coupling Image Analytics
Inter-modal Coupling Image Analytics
批准号:
10530041
负责人:
Theodore Satterthwaite
金额:
$76.24万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
未结题
起止时间:
2017-05-10 至 2027-06-30
关键词:
AccountingAddressBiological MarkersBrainBrain imagingComplexCouplingData ScientistDevelopmentDiagnosticExecutive DysfunctionGene set enrichment analysisGenomicsGoalsHumanImageLeftMachine LearningMapsMeasurementMeasuresMental disordersMethodologyMethodsModalityMultimodal ImagingNon-linear ModelsPhiladelphiaPsychopathologyReproducibilityResearch PersonnelStatistical MethodsStructureWorkYouthcohortconnectomedata resourcehigh dimensionalityimaging modalityimaging studyinterestoutcome predictionsuccesstool
中文摘要
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英文摘要
PROJECT SUMMARY
Almost all brain imaging studies now collect multiple imaging modalities, in an effort to derive measures of both
structure and function from diverse imaging sequences. While quantitative data scientists have focused on
machine learning approaches for predicting outcomes using multi-modal imaging, rigorous statistical methods
for examining the relationship between imaging modalities have lagged behind. At present, the lack of statistical
methodologies for assessing inter-modal coupling (IMCo) has left investigators with ad hoc solutions that lack
statistical power and are prone to type I error, posing a threat to scientific rigor and reproducibility. In this
application, we propose robust methods that leverage subject-specific measurements and use nonlinear
modeling to address complex relationships in brain maps or networks, while accounting for important covariates
(Aim 1). Furthermore, we will develop powerful approaches for assessing whether effects of interest (e.g.,
psychopathology, development) are enriched within brain networks (Aim 2). Assessment of this coupling
between statistical associations and brain networks will capitalize upon tools from statistical genomics (e.g.,
gene set enrichment analysis) to provide principled methods for conducting enrichment analyses using high-
dimensional, personalized brain networks. Finally, we will use these tools to delineate how trans-diagnostic
executive dysfunction in youth with mental illness is related to abnormalities in structure-function coupling within
brain networks (Aim 3). To do this, we will leverage three massive data resources: the Philadelphia
Neurodevelopmental Cohort (PNC; n=1,601), the Healthy Brain Network (n=3,200), and the Human
Connectome-Development (HCP-D; n=1,300) study Taken together, the proposed work builds upon the notable
success in the first project period, promising to yield rigorous and generalizable methods for delineating the
relationships between complementary measures of brain structure and function.
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Inter-modal Coupling Image Analytics
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批准号:9918452
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项目类别:
-
资助金额:$44.37万
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财政年份:2017
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负责人:Theodore Satterthwaite
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依托单位:
Longitudinal multi-modal neuroimaging of irritability in youth
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批准号:9129728
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项目类别:
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资助金额:$61.32万
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财政年份:2015
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负责人:Theodore Satterthwaite
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依托单位:
Longitudinal multi-modal neuroimaging of irritability in youth
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批准号:8956455
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项目类别:
-
资助金额:$62.11万
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财政年份:2015
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负责人:Theodore Satterthwaite
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依托单位:
Neuroimaging of Dimensional Reward Dysfunction in Adolescence
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批准号:8505546
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项目类别:
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资助金额:$18.12万
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财政年份:2012
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负责人:Theodore Satterthwaite
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依托单位:
Neuroimaging of Dimensional Reward Dysfunction in Adolescence
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批准号:8352367
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项目类别:
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资助金额:$18.2万
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财政年份:2012
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负责人:Theodore Satterthwaite
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依托单位:
Neuroimaging of Dimensional Reward Dysfunction in Adolescence
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批准号:8656442
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项目类别:
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资助金额:$18.05万
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财政年份:2012
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负责人:Theodore Satterthwaite
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依托单位:
海外基金