Computational protocol: Sleep deprivation affects fear memory consolidation: bi-stable amygdala connectivity with insula and ventromedial prefrontal cortex

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Protocol publication

[…] Resting-state fMRI data were analyzed using SPM12, DPABI2.1 and REST1.8 software packages (; ; Song et al., 2011). The first five functional volumes were discarded to allow MRI equilibration. For the functional T2* -weighted images, slice timing was used to correct slice acquisition order, realigned was used to control motion effects and to estimate the six head motion parameters. For normalization, the T1-weighted structural images were co-registered to the EPI mean images and segmented into white matter, gray matter, and Cerebrospinal fluid (CSF). The functional images were next normalized to MNI space using a 3 × 3 × 3 mm3 voxel resolution. The normalized data were spatially smoothed using a 6 mm the full width at half maximum (FWHM) kernel, and linear drift was removed and a band pass filter of 0.01–0.08 Hz was applied before the calculation of voxel wise and ROI wise indices for each subject. For the voxel wise analysis, the correlation was calculated between the amygdala seeds and the whole brain (brain activation map), whereas for the region of interest (ROI) wise analysis, a correlation analysis was performed between extracted time courses from the amygdala, insula and vmPFC, respectively (correlation coefficient) ( , ). […]

Pipeline specifications

Software tools SPM, DPABI
Application Functional magnetic resonance imaging
Diseases Adrenal Cortex Diseases