Multigrid Priors for fMRI time series analysis
Multigrid Priors for fMRI time series analysis
复制标题
用于 fMRI 时间序列分析的多重网格先验
DOI：
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
S. R. Rabbani
中科院分区：
文献类型：
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作者：
N. Caticha;S. D. R. Amaral;S. R. Rabbani
为了在功能磁共振成像（fMRI）中评估大脑活动，我们处理构建先验数据分析的问题。我们的方法是一个例子，说明了先验分布是如何将所谓的传统先验信息以及其他信息（如源于合理可能性的知识）结合在一起的。在认知、感觉或运动任务中，大脑活动在问题涉及的不同尺度上表现出一定程度的定位和空间相关性。这表明了构建先验的多尺度迭代过程。在图像上构建不同尺度的网格。在空间上为每个尺度定义粗粒数据变量，直到获得单个体素时间序列。这个过程包括迭代回到更精细的尺度，为每个粗糙尺度确定一组后验概率。粗尺度上的后验被用作下一个细尺度上活动的先验。我们有app…
We deal with the problem of constructing priors for data analysis in order to asses brain activity in functional Magnetic Resonance Imaging (fMRI). Our method is an example of how a prior distribution can incorporate what could be termed as conventional prior information as well as other information such as that steming from knowledge of what constitues a reasonable likelihood.Brain activity during a cognitive, sensorial or motor task presents a certain level of localization and spatial correlations with different scales involved in the problem. These suggests a multiscale iterative procedure to construct the prior. Grids of different scales are constructed over the image. Spatially coarse grain data variables are defined for each scale, until a single voxel time series is obtained. The process consists in iterating back to finer scales, determining for each coarse scale a set of posterior probabilities. The posterior on a coarse scale is used as the prior for activity at the next finer scale. We have app...
影响因子：
56.9
作者：
BELLIVEAU, JW;KENNEDY, DN;ROSEN, BR
通讯作者：
ROSEN, BR
DOI：
10.1073/pnas.89.12.5675
发表时间：
1992-06-15
影响因子：
11.1
作者：
KWONG, KK;BELLIVEAU, JW;ROSEN, BR
通讯作者：
ROSEN, BR