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Neurobiology of Dyspnea: An Overview
Published in Donald A. Mahler, Denis E. O’Donnell, Dyspnea, 2014
Karleyton C. Evans, Robert B. Banzett
There are now several validated statistical software packages that are specifically designed to preprocess and analyze neuroimaging data that include Statistical Parametric Mapping (http://www.fil.ion.ucl.ac.uk/spm), Functional MRI of the Brain Software Library (http://fsl.fmrib.ox.ac.uk), and Analysis of Functional Neuroimages (http://afni.nimh.nih.gov). Additional information regarding image preprocessing and analyses is now available in several texts; for example, the comprehensive text by Friston et al.24
Altered connectivity of default mode and executive control networks among female patients with persistent post-concussion symptoms
Published in Brain Injury, 2023
Jimmy K. Y. Wong, Nathan W. Churchill, Simon J. Graham, Andrew J. Baker, Tom A. Schweizer
The rs-fMRI data were preprocessed using Analysis of Functional Neuroimages (AFNI; https://afni.nimh.nih.gov) and in-house software (29). Preprocessing steps included discarding the first 2 timepoints to allow scans to reach equilibrium, with rigid-body motion correction using 3dvolreg, and removal of outlier volumes using SPIKECOR (nitrc.org/projects/spikecor). The latter step controls for effects of abrupt head movements by computing the root-mean-square (RMS) displacement at each time point for both the 6 rigid-body motion parameter estimates from 3dvolreg and the BOLD signal within a brain mask, computed via 3dAutomask. For both RMS displacement measures, a Gamma distribution was fit, and significant outlier volumes were removed if identified at p < 0.05 for both. Any outlier volumes were replaced by interpolated values from neighboring volumes, using cubic splines.
Use of neuroimaging to measure neurocognitive engagement in health professions education: a scoping review
Published in Medical Education Online, 2022
Serkan Toy, Dana D Huh, Joshua Materi, Julie Nanavati, Deborah A. Schwengel
If researchers are going to use neuroimaging data as a continuous measure of task-related brain activation patterns, they must also ensure data quality and integrity when addressing the specific research question. For instance, some observed changes in brain activation patterns may be attributable to environmental factors or activities unrelated to the task in question. Thus, all of the studies used at least one software package along with filtering and classification techniques to remove noise and signal artifacts such as environmental or muscle and eye movement. The following are some of the software packages reported by the included research studies for neuroimaging data preprocessing and transformation: Analysis of Functional Neuroimages (AFNI) [77], fMRI Expert Analysis Tool (FEAT) [78,79], or FLIRT/MCFLIRT (Motion Correction FMRIB’s Linear Image Registration Tool) [80] for fMRI; HOMER2 [81], Functional optical signal analysis (fOSA) [82], or Imperial College Neuroimaging Analysis (ICNA) [83] or now known as Imperial College Near Infrared Spectroscopy Neuroimaging Analysis (ICNNA) [84] for fNIRS; and EEG lab [85] or Brain Vision Analyzer (Brain Products GmbH, Gilching, Germany) for EEG.
Differential effects of recent versus past traumas on mood, social support, binge drinking, emotional eating and BMI, and on neural responses to acute stress
Published in Stress, 2021
Gretchen Hermes, Nia Fogelman, Dongju Seo, Rajita Sinha
fMRI data were converted from Digital Imaging and Communication in Medicine format to analyze format using XMedCon (Nolfe, 2003). Individual-level analysis was conducted using a General Linear Model (GLM) on each voxel in the entire brain volume with a task-specific regressor (2.5 min imagery relative to a 1.5 min baseline) using Yale BioImageSuite (http://www.bioimagesuite.org) (Duncan et al., 2004). To account for potential variability in baseline fMRI signal, drift correction was included in the GLM model for each run. Group analysis was conducted with Analysis of Functional NeuroImages Software (AFNI) (Cox, 1996); http://afni.nimh.nih.gov) using random mixed effects models. To examine the relationship between trauma measures (recent trauma and past trauma) with brain activity during the task, whole brain correlation analysis was conducted using Bioimagesuite. To correct for multiple comparisons, a Family Wise Error rate (FWE) correction was applied using 3dClustSim in AFNI (corrected version 16.0.09) (Cox, 1996; Xiong et al., 1995).