title: Comparison of a non-stationary voxelation-corrected cluster-size test with TFCE for group-Level MRI inference.
abstract: Two powerful methods for statistical inference on MRI brain images have been proposed recently, a non-stationary voxelation-corrected cluster-size test (CST) based on random field theory and threshold-free cluster enhancement (TFCE) based on calculating the level of local support for a cluster, then using permutation testing for inference. Unlike other statistical approaches, these two methods do not rest on the assumptions of a uniform and high degree of spatial smoothness of the statistic image. Thus, they are strongly recommended for group-level fMRI analysis compared to other statistical methods. In this work, the non-stationary voxelation-corrected CST and TFCE methods for group-level analysis were evaluated for both stationary and non-stationary images under varying smoothness levels, degrees of freedom and signal to noise ratios. Our results suggest that, both methods provide adequate control for the number of voxel-wise statistical tests being performed during inference on fMRI data and they are both superior to current CSTs implemented in popular MRI data analysis software packages. However, TFCE is more sensitive and stable for group-level analysis of VBM data. Thus, the voxelation-corrected CST approach may confer some advantages by being computationally less demanding for fMRI data analysis than TFCE with permutation testing and by also being applicable for single-subject fMRI analyses, while the TFCE approach is advantageous for VBM data. Hum Brain Mapp 38:1269-1280, 2017. © 2016 Wiley Periodicals, Inc.
authors: Department of Biomedical Engineering, Dalian University of Technology, Dalian, China.|Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.|Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|McLean Imaging Center, McLean Hospital/Harvard Medical School, Belmont, Massachusetts.
authors: Huanjie
authors: H
authors: Li
authors: McLean Imaging Center, McLean Hospital/Harvard Medical School, Belmont, Massachusetts.
authors: Lisa D
authors: LD
authors: Nickerson
authors: Department of Statistics and Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom.
authors: Thomas E
authors: TE
authors: Nichols
authors: Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.|Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|McGovern Institute for Brain Research, Peking University, Beijing, China.
authors: Jia-Hong
authors: JH
authors: Gao
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical
keywords: TFCE; VBM analysis; cluster size test; group-level analysis; permutation test; random field theory; spatial smoothness