Computational protocol: Altered intrinsic regional spontaneous brain activity in patients with optic neuritis: a resting-state functional magnetic resonance imaging study

Similar protocols

Protocol publication

[…] All the functional data were checked by MRIcro software (McCausland Center for Brain Imaging, Columbia, SC, USA) ( to exclude the defective ones. The first ten volumes of each session were discarded for the initial unstable magenetization state and the unadaptability of participants. The rest of the data were preprocessed using SPM8 ( and DPARSFA ( software. The following steps were slice timing, head-motion correction, spatial normalization, smooth with a Gaussian kernel of 6×6×6 mm3 full width at half maximum. In head-motion correction, participants whose head motion was more than 1.5 mm or 1.5° in any of the six parameters (x, y, z, pitch, roll, yaw) were excluded. Then, the fMRI images were spatially normalized to the Montreal Neurological Institute space using the standard echo-planar imaging template and resampled at a resolution of 3×3×3 mm. Finally, detrending and band-pass filtering (0.01–0.08 Hz) of the fMRI data were conducted to reduce the effects of low-frequency drift and physiological high-frequency respiratory and cardiac noise.ReHo computation based on Kendall’s coefficient of concordance (KCC) was performed with REST software ( Individual ReHo maps were generated by calculating the KCC of the time series of a given voxel with those of its nearest neighbors (26 voxels) in a voxel-wise manner with the formula: ReHo=Σ(Ri)2−n(R¯)2k2(n3−n)12,(1)where ReHo is the KCC for a given voxel, ranging from 0 to 1. When the ranked time series is more consistent with its adjacent ones, the KCC value is closer to 1; k is the voxel number among time series (in our study, k =27, including one given voxel that was located in the cubic center and its adjacent 26 voxels); n is the number of ranks; Ri is the sum rank of the ith time point, and R¯ = (n+1)/2*k/2 is the mean of the Ri’s. The KCC value refers to the central voxel among the cluster. The individual KCC ReHo map was generated on a voxel-wise basis for all data sets. To reduce the influence of individual variations in the KCC value, normalization of ReHo maps was done by dividing the KCC among each voxel by the averaged KCC of the whole brain. The resulting fMRI data were then spatially smoothed with a Gaussian kernel of 6×6×6 mm3 full width at half maximum. […]

Pipeline specifications

Software tools MRIcro, SPM, DPABI
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens
Diseases Brain Diseases, Optic Neuritis