Computational protocol: Reconfiguration of the Brain Functional Network Associated with Visual Task Demands

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Protocol publication

[…] All MRI data were processed using DPARSF_V2.0 [] based on the SPM8 toolkit ( Consistent data processing procedures were applied for the three cognitive conditions. The fMRI data of the three conditions for each subject were processed separately. To minimize the effects of the length of the time series on network analysis [], we used the first 8 min fMRI data of VSW and VSD to yield 240 time points that are comparable to the RS condition. As described previously [], the following procedures were adopted. First, the first 10 volume images were removed from the fMRI data for scanner stabilization and participant adaptation to the environment. Subsequently, slice timing and realignment were performed to correct for the acquisition time delay and head motions, respectively. We assessed the head motion of each participant, and no participant was excluded according to these criteria (i.e., the head motion in any direction was not more than 1.5 mm or 1.5°). We adopted the maximum head motion of the time series to represent the head motion profile in any direction for each condition of each subject, and used repeated measures ANOVA to analyze the differences of head motion in any direction among the three conditions. Notably, the head motion profiles were matched among the three conditions (i.e., RS, VSW and VSD) (p > 0.118 in any direction). The acquired functional images were further spatially normalized to a standard MNI template and resampled to a voxel size of 3×3×3 mm3. Here, we did not perform spatial smoothing, consistent with several previous studies [, ]. To reduce low frequency drift and the physiological noise of fMRI data, the linear detrend was removed, and 0.01Hz high-pass filtering was used. Moreover, we regressed out the nuisance covariates, including the 6 head motion parameters and the white matter and cerebrospinal fluid (CSF) signals. The global signal was not regressed out due to recent debates [–]. […]

Pipeline specifications

Software tools DPABI, SPM
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Diseases Heart Septal Defects, Ventricular