BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain
BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain
批准号:
9360100
负责人:
MOO K CHUNG
金额:
$37.61万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-27 至 2019-06-30
关键词:
AddressAlgorithmsBRAIN initiativeBase of the BrainBrainBrain imagingBrain regionBypassCommunitiesComplexComputer softwareDataData AnalysesDatabasesDizygotic TwinsFunctional Magnetic Resonance ImagingFutureGeneticGenetic studyGoalsGraphHeritabilityHumanImageIndividualMagnetic Resonance ImagingMapsMeasuresMethodologyMethodsModelingPhenotypePopulationPropertyPsychopathologyResearch DesignResolutionSame-sexSamplingSoftware ToolsStructureTechniquesTestingTimeTwin Multiple BirthTwin Studiesbasecostimaging modalityimaging studyinterestmultimodalitynetwork modelsneural circuitnovel strategiesopen sourcetheories
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Abstract
The twin study design in brain imaging offers a very effective way of determining heritability of the human
brain. The difference in variability between monozygotic (MZ) and same-sex dizygotic (DZ) twins can be used
in determining heritability. We propose to determine the extent of heritability of both structural and functional
brain networks at the voxel-level using 200 pairs of twin (400 individuals) of fMRI/DTI and MRI. To obtain high-
resolution heritability map of the brain networks, the project requires taking more than 25 thousands voxels for
fMRI and 1.2million voxels for MRI/DTI as network nodes, which is a serious computational challenge. The
project proposes many new algorithms for constructing large-scale brain networks and subsequently mapping
the heritability of the networks. This study will provide the brain imaging community with the baseline brain
network heritability maps as well as a versatile open-source toolbox of algorithms for modeling and visualizing
large-scale brain networks of three different imaging modalities.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Dynamic embedding time series models in functional brain imaging
-
批准号:10711521
-
项目类别:
-
资助金额:$36.41万
-
财政年份:2023
-
负责人:MOO K CHUNG
-
依托单位:
Dynamic manifold-valued time series model in functional brain imaging
-
批准号:10374109
-
项目类别:
-
资助金额:$31.24万
-
财政年份:2020
-
负责人:MOO K CHUNG
-
依托单位:
BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain
-
批准号:9170211
-
项目类别:
-
资助金额:$37.61万
-
财政年份:2016
-
负责人:MOO K CHUNG
-
依托单位:
海外基金