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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