Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data

By Mark William Woolrich, B. D. Ripley, M. Brady, Stephen M. Smith. NeuroImage, 2001

2,941 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/d31884b9f1ec4469e477043c9c524d7d251a68ee

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Probabilistic independent component analysis for functional magnetic resonance imaging (2004, methodology): “Estimation of from residuals in the case of autocorrelated noise is discussed in detail in [23] which is the approach used in this case.”
On the distribution of cross-validated Mahalanobis distances (2016, methodology): “To simulate the temporal dependence of fMRI noise [23,27], we approximated the temporal autocorrelation observed in this experiment using a double exponential function:”
Correlation between motor improvements and altered fMRI activity after rehabilitative therapy. (2002, methodology): “Statistical analysis was carried out using FILM (Woolrich et al., 2001) with local autocorrelation correction.”
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images (2002, methodology): “Analysis was carried out using FEAT, FMRIBs easy analysis tool using an improved linear model (Woolrich et al., 2001).”
Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: An fMRI study (2005, methodology): “Time-series statistical analysis was carried out with local autocorrelation correction [Woolrich et al., 2001].”
Imaging how attention modulates pain in humans using functional MRI. (2002, methodology): “In FEAT, the GLM method is known as FILM (fMRIB's improved linear model) (Woolrich et al., 2000, 2001).”
On the Plurality of (Methodological) Worlds: Estimating the Analytic Flexibility of fMRI Experiments (2012, background): “, 1999), autocorrelation correction (Purdon and Weisskoff, 1998; Woolrich et al., 2001), global signal regression (Murphy et al.”
Impact of In-Scanner Head Motion on Multiple Measures of Functional Connectivity: Relevance for Studies of Neurodevelopment in Youth (2012, methodology): “Voxelwise PCC time-series analysis was carried out using FILM with local autocorrelation correction as implemented in FEAT (Woolrich et al., 2001).”
Brain Mechanisms Supporting Modulation of Pain by Mindfulness Meditation (2011, positive): “Statistical analysis of regional signal changes was performed on each acquisition series (first-level analyses) using a fixed-effects general linear modeling approach (Woolrich et al., 2001).”
Advances in functional and structural MR image analysis and implementation as FSL. (2004, methodology): “Using the above approach, we were able to demonstrate close to zero bias at probability levels as low as 0.00001 ( Woolrich et al., 2001 ).”
Search for patterns of functional specificity in the brain: A nonparametric hierarchical Bayesian model for group fMRI data (2011, methodology): “In the application of this model to fMRI data, we first apply temporal filtering to the signal to decorrelate the noise in the preprocessing stage (Burock and Dale, 2000; Bullmore et al., 2001; Woolrich et al., 2001).”
Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics (2008, methodology): “…tool (Jezzard et al., 2001); www.fmrib.ox.ac.uk/fsl] The fMRI signal was linearly modeled on a voxel-by-voxel basis using FILM (FMRIB’s improved linear model) with local autocorrelation correction (Woolrich et al., 2001, 2004), yielding statistical parametric maps for each subject and condition.”
Constrained linear basis sets for HRF modelling using Variational Bayes (2004, methodology): “Previous work has shown that neighbouring voxels have similar temporal autocorrelation (Woolrich et al., 2001; Worsley et al., 2002).”
Visual inspection of independent components: Defining a procedure for artifact removal from fMRI data (2010, methodology): “FSL FEAT with FILM local autocorrelation correction (Woolrich et al., 2001) was used to generate Gaussianised, z-statistic images reflecting parameter estimates in relation to their standard errors and degrees of freedom.”