Connectivity of anatomical and functional MRI data

被引：0

作者：

Worsley, KJ ^{[1
]}

Charil, A ^{[1
]}

Lerch, J ^{[1
]}

Evans, AC ^{[1
]}

机构：

[1] McGill Univ, Dept Math & Stat, Montreal, PQ, Canada

来源：

Proceedings of the International Joint Conference on Neural Networks (IJCNN), Vols 1-5 | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We are all familiar with the correlation coefficient between two sets of numbers. Now suppose we replace the numbers by vector-valued images in any number of dimensions. The correlation random field is the 'image' of correlations at all possible pairs of points in the two images. We use random field theory to set a threshold on the correlations so that those above the threshold are statistically significant, corrected for searching over all pairs of points. We apply this idea to resting state networks of fMRI images of brain activity, and networks of connectivity in cortical thickness.

引用

页码：1534 / 1536

页数：3

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