Augmented pain-evoked primary sensorimotor cortex activation in adolescent girls with juvenile fibromyalgia.

"Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article."

"This work was funded by Cincinnati Children's Hospital Medical Center's Trustee Grant Award and NIH/NIAMS Grants R01 AR074795 and P30 AR076316. Marina López-Solà, PhD is hired as part of the Serra Hunter Programme of the Generalitat de Catalunya. The authors gratefully thank Matt Lanier, Kaley Ireland, Kelsey Murphy, Brynne Williams, Sarah Miozzi, and Lacey Haas (Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center) for their assistance in collecting MRI data."

"We preprocessed the neuroimaging data using FSL (FMRIB Software Library version 6.0.3, the Analysis Group, FMRIB, Oxford, United Kingdom) and AFNI (Analysis of Functional Neuroimages version 20.3.02, Medical College of Wisconsin, WI). For the structural images, we performed brain extraction using the Brain Extraction Tool (BET) in FSL. We performed bias correction and segmentation using FMRIB's Automated Segmentation Tool (FAST) in FSL. Then we normalized and resampled the brain-extracted image to the 2-mm isotropic MNI ICBM 152 nonlinear sixth generation template using FSL's FMRIB's Linear Image Registration Tool (FLIRT)., We preprocessed each participant's functional scans in the following steps: First, brain extraction was performed using FSL's BET. Next, outlying functional volumes (ie, spikes) were detected using the DVARS metric within FSL's “fsl_motion_outliers.” We performed motion correction of the functional time series using MCFLIRT. The motion corrected data were then high pass filtered at 0.00556 Hz (180 seconds) and smoothed with a 6-mm full width at half maximum (FWHM) filter using AFNI 3dBandpass. To minimize pain-induced global cerebral blood flow fluctuations,, we applied intensity normalization by scaling each fMRI volume by its mean global intensity.,, The intensity-normalized data were first coregistered with the participant's T1 image using FSL FLIRT (6-parameter rigid body model), then aligned to the MNI template."