2.5 Acquisition and prepossessing of resting state functional MRI data
REGRESSION, BEST
We acquired T1-weighted and functional scans in a Philips 3T Achieva scanner (Philips Medical Systems, Best, Netherlands), with a 32-channel head coil. The image acquisition consisted of structural T1-weighted scans with a 3D Turbo Spin Echo sequence and the following parameters: TR/TE = 8.2/3.8 ms, flip angle = 8°, field of view = 256 × 256 mmWe performed standard fMRI preprocessing and denoising steps, using Statistical Parametric Mapping 12 (SPM12) and functional connectivity toolbox (CONN 20.b) in MATLAB 2021b. To summarize the preprocessing steps, we conducted functional realignment and unwarping, artifact detection by artifact detection tool (using an intermediate setting with 97%-percentiles), segmentation and direct normalization of both functional and structural data to the MNI space, and finally spatial smoothing of functional data with a Gaussian kernel with a size of 6 mm full width at half maximum.We further accomplished the denoising by applying a linear regression of confounding effects, including nuisance signals from white matter and cerebrospinal fluid areas [Moreover, we assessed frame-wise displacement (FD) [