Faster permutation inference in brain imaging
Abstract
Permutation tests are increasingly being used as a reliable method for inference in neuroimaging analysis. However, they are computationally intensive. For small, non-imaging datasets, recomputing a model thousands of times is seldom a problem, but for large, complex models this can be prohibitively slow, even with the availability of inexpensive computing power. Here we exploit properties of statistics used with the general linear model (GLM)...
Paper Details
Title
Faster permutation inference in brain imaging
Published Date
Nov 1, 2016
Journal
Volume
141
Pages
502 - 516
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