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Abstract #4128

A high performance cluster-based test for subject- and group-level analysis of unsmoothed fMRI data

Huanjie Li 1 , Lisa D. Nickerson 2 , Jinhu Xiong 3 , and Jia-Hong Gao 1

1 Peking University, Beijing, Beijing, China, 2 Harvard Medical School, Massachusetts, United States, 3 University of Iowa, Iowa, United States

Most existing cluster-size tests used in fMRI data analysis to detect brain activation were formulated and validated under sufficiently smooth image conditions. Unfortunately, spatial smoothing degrades spatial specificity and increases false positives. Recently, a threshold-free cluster enhancement (TFCE) technique was proposed which does not require spatial smoothing, but this method can only be used for group level analysis. We propose a more reliable and effective 3D cluster-based method which can keep a higher sensitivity for localizing activation regions for both single-subject and group level analysis without the requirement of spatial smoothness.

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