NEW STATISTICAL METHODS FOR fMRI APPLIED TO VISUAL REFERENCE FRAMES IN HUMANS
NEW STATISTICAL METHODS FOR fMRI APPLIED TO VISUAL REFERENCE FRAMES IN HUMANS
批准号:
8243545
负责人:
CHRISTOPHER R GENOVESE
金额:
$11.49万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-01-01 至 2015-04-30
关键词:
AddressAlgorithmsAreaAttention deficit hyperactivity disorderBiometryBrainBrain regionCerebral cortexCollectionDataData SetDependenceDevelopmentDiagnostic testsElementsExhibitsEyeEye MovementsFunctional Magnetic Resonance ImagingHumanImageIndividualKnowledgeLeadLocationMacular degenerationMethodologyMethodsMinorMonkeysNeighborhoodsNeuronsNoiseOcular orbitPerformancePeripheralPositioning AttributeProcessProtocols documentationPublic HealthResolutionRetinaSaccadesSchizophreniaSeriesShapesSignal TransductionSorting - Cell MovementStimulusStructureSystemTechniquesTestingTimeVisionVisualVisual CortexVisual FieldsVisual attentionVisual system structurehuman subjectimprovedneglectneuroimagingneuropsychologicalnovelnovel strategiespatient populationreceptive fieldreconstructionresearch studyresponsetool
中文摘要
功能性磁共振成像(fMRI)的最新技术进展
使得研究大脑不仅仅是将其作为一个体积元素的集合
(体素)而是作为相互作用的组件的系统。而不是考虑
在单个区域,我们可以研究功能网络。而不是计算体素的
个体的反应曲线,我们可以估计他们对刺激的集体反应。
我们可以用精细的空间图像来代替大脑区域的平均反应,
结构这种面向系统的方法需要成像和
统计方法。该项目由两个相互交织的部分组成。第一
正在进行功能磁共振成像实验,以解决三个问题,
人类大脑中的空间。第二个是开发和验证三个新的统计
技术,允许系统级的推理需要回答神经科学
问题.这些技术的动机和发展的建议
实验研究,但有轻微的调整,他们将广泛适用于其他
神经影像学研究。在目标1中,该项目将制定方法,
表征分布式功能网络。这些方法将用于研究
视觉重映射的皮层回路。在目标2中,该项目将开发
同时估计fMRI响应场的方法。这些方法将
用于测试视觉和眼动信号的相互作用。目标3:项目
将为高分辨率功能磁共振成像数据开发自适应空间平滑技术。这些
将使用工具来测试视觉皮层中的眼睛位置信号的精细尺度结构。
本项目中开发的实验方案和理论原理将
增进对人类视觉系统基本功能的了解。统计
在这个项目中开发的技术将提供新的方法来理解功能
系统与神经成像,并将推进广泛适用的方法,使
关于时空数据中区域的推断。
英文摘要
Recent technological improvements in functional Magnetic Resonance Imaging (fMRI)
are making it possible to study the brain as more than a collection of volume elements
(voxels) but rather as a system of interacting components. Instead of considering
individual regions, we can study functional networks. Instead of computing voxels'
individual response curves, we can estimate their collective response to a stimulus.
Instead of settling for responses averaged over brain regions, we can image fine spatial
structure. Such a system-oriented approach requires advances in both imaging and
statistical methodology. This project consists of two intertwined components. The first
is performing fMRI experiments to address three questions about the representation of
space in the human brain. The second is developing and validating three new statistical
techniques that allow the system-level inferences needed to answer the neuroscientific
questions. These techniques are motivated by and developed for the proposed
experimental studies, but with minor adaptation, they will be broadly applicable to other
neuroimaging studies. In Aim 1, the project will develop methods for identifying and
characterizing distributed functional networks. These methods will be used to study the
cortical circuit that underlies visual remapping. In Aim 2, the project wil develop
methods for simultaneously estimating fMRI response fields. These methods will be
used to test the interaction of visual and eye movement signals. In Aim 3, the project
will develop adaptive spatial smoothing techniques for high-resolution fMRI data. These
tools will be used to test the fine-scale structure of eye position signals in visual cortex.
The experimental protocols and theoretical principles developed in this project will
increase understanding of the basic function of the human visual system. The statistical
techniques developed in this project will give new ways to understand of functional
systems with neuroimaging and will advance broadly applicable methods for making
inferences about regions in spatio-temporal data.
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DOI:
10.1214/12-aos1044
发表时间:
2013-04
期刊:
Annals of statistics
影响因子:
4.5
作者:
[Shalizi CR, Rinaldo A]
通讯作者:
Rinaldo A
DOI:
10.1080/01621459.2013.779829
发表时间:
2013-07-01
期刊:
Journal of the American Statistical Association
影响因子:
3.7
作者:
[Friedenberg DA, Genovese CR]
通讯作者:
Genovese CR
Motion direction biases and decoding in human visual cortex.
人类视觉皮层的运动方向偏差和解码。
DOI:
10.1523/jneurosci.1034-14.2014
发表时间:
2014
期刊:
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子:
--
作者:
[Wang,HelenaX, Merriam,ElishaP, Freeman,Jeremy, Heeger,DavidJ]
通讯作者:
Heeger,DavidJ
Comment on "Why and When 'Flawed' Social Network Analyses Still Yield Valid Tests of no Contagion".
评论“为什么以及何时'有缺陷的'社交网络分析仍会产生无传染的有效测试”。
DOI:
10.1515/2151-7509.1053
发表时间:
2012-02
期刊:
Statistics, politics, and policy
影响因子:
--
作者:
[Shalizi CR]
通讯作者:
Shalizi CR
DOI:
10.1111/j.2044-8317.2011.02037.x
发表时间:
2013-02
期刊:
The British journal of mathematical and statistical psychology
影响因子:
--
作者:
[Gelman A, Shalizi CR]
通讯作者:
Shalizi CR
共 9 条
New Statistical Methods for fMRI Applied to Remapping
-
批准号:6837683
-
项目类别:
-
资助金额:$18.82万
-
财政年份:2004
-
负责人:CHRISTOPHER R GENOVESE
-
依托单位:
NEW STATISTICAL METHODS FOR fMRI APPLIED TO VISUAL REFERENCE FRAMES IN HUMANS
-
批准号:7816813
-
项目类别:
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资助金额:$27.62万
-
财政年份:2004
-
负责人:CHRISTOPHER R GENOVESE
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依托单位:
New Statistical Methods for fMRI Applied to Remapping
-
批准号:6989122
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项目类别:
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资助金额:$18.47万
-
财政年份:2004
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负责人:CHRISTOPHER R GENOVESE
-
依托单位:
New Statistical Methods for fMRI Applied to Remapping
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批准号:6715731
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项目类别:
-
资助金额:$18.73万
-
财政年份:2004
-
负责人:CHRISTOPHER R GENOVESE
-
依托单位:
New Statistical Methods for fMRI Applied to Remapping
-
批准号:7185138
-
项目类别:
-
资助金额:$18.02万
-
财政年份:2004
-
负责人:CHRISTOPHER R GENOVESE
-
依托单位:
NEW STATISTICAL METHODS FOR fMRI APPLIED TO VISUAL REFERENCE FRAMES IN HUMANS
-
批准号:8060476
-
项目类别:
-
资助金额:$27.67万
-
财政年份:2004
-
负责人:CHRISTOPHER R GENOVESE
-
依托单位:
IMPROVED MODELING AND INFERENCE IN FUNCTIONAL MRI
-
批准号:2647504
-
项目类别:
-
资助金额:$10.0万
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财政年份:1997
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负责人:CHRISTOPHER R GENOVESE
-
依托单位:
海外基金