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- W2008092020 abstract "A statistical test for detecting activated pixels in functional MRI (fMRI) data is proposed. For the derivation of this test, the fMRI time series measured at each voxel is modeled as the sum of a response signal which arises due to the experimentally controlled activation‐baseline pattern, a nuisance component representing effects of no interest, and Gaussian white noise. The test is based on comparing the dimension of the voxels fMRI time series fitted data models with and without controlled activation‐baseline pattern. The Jeffrey divergence is used for this comparison. The test has the advantage of not requiring a level of significance or a threshold to be provided." @default.
- W2008092020 created "2016-06-24" @default.
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- W2008092020 date "2009-01-01" @default.
- W2008092020 modified "2023-09-23" @default.
- W2008092020 title "Activation Detection in fMRI Using Jeffrey Divergence" @default.
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- W2008092020 doi "https://doi.org/10.1063/1.3275623" @default.
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