Computational protocol: Decreased Subcortical and Increased Cortical Degree Centrality in a Nonclinical College Student Sample with Subclinical Depressive Symptoms: A Resting-State fMRI Study

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Protocol publication

[…] Functional MRI data preprocessing was performed using the Data Processing Assistant for rs-fMRI advanced edition (DPARSF; Chao-Gan and Yu-Feng, ), which works with SPM8 implemented in the MATLAB (The Math Works, Inc., Natick, MA, USA) platform. Consistent with our previous work (Wei et al., ), before the preprocessing, the first 10 functional volume images of each subject’s dataset were discarded due to magnetization effects. Then, the remaining rs-fMRI data were corrected for slice timing and realigned for motion correction. The standard Montreal Neurological Institute (MNI) template provided by SPM8 was used for spatial normalization with a resampling voxel size of 3 mm × 3 mm × 3 mm. No subjects had head motion exceeding 3 mm of movement or 3° rotation in any direction. The covariates including the white matter signal, cerebrospinal fluid signal and Friston 24 motion parameters, were regressed out from the time series of every voxel. The rs-fMRI dataset was then filtered using a typical temporal bandpass (0.01–0.08 Hz) to reduce the low-frequency drift and high-frequency respiratory and cardiac noise. Given the controversy of removing the global signal in the preprocessed rs-fMRI data (Murphy et al., ), we did not regress the global signal out in the present study. […]

Pipeline specifications

Software tools DPABI, SPM
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Diseases Brain Diseases