2001
DOI: 10.1006/nimg.2001.0931
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Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data

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Cited by 2,588 publications
(2,074 citation statements)
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References 24 publications
(35 reference statements)
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“…Grandmean intensity normalization (by a single multiplicative factor) and high-pass temporal filtering (using a Gaussian-weighted least-squares straight line fitting, with sigma ¼60.0 s) were performed. FMRIB's Improved Linear Model was used to perform time-series statistical analyses with local autocorrelation correction (Woolrich et al, 2001). FMRIB's Linear Image Registration Tool (Jenkinson and Smith, 2001;Jenkinson et al, 2002) was used to register functional scans via a twostep transformation.…”
Section: Fmri Data Preprocessingmentioning
confidence: 99%
“…Grandmean intensity normalization (by a single multiplicative factor) and high-pass temporal filtering (using a Gaussian-weighted least-squares straight line fitting, with sigma ¼60.0 s) were performed. FMRIB's Improved Linear Model was used to perform time-series statistical analyses with local autocorrelation correction (Woolrich et al, 2001). FMRIB's Linear Image Registration Tool (Jenkinson and Smith, 2001;Jenkinson et al, 2002) was used to register functional scans via a twostep transformation.…”
Section: Fmri Data Preprocessingmentioning
confidence: 99%
“…Subject-level time-series statistical analysis was carried out using FILM (FMRIB's Improved Linear Model) with local autocorrelation correction (Woolrich 2001). The three condition events were modeled using a canonical hemodynamic response function and its temporal derivative.…”
Section: Image Processing and Statistical Analysismentioning
confidence: 99%
“…31 For the categorization task three explanatory variables were modelled: 'negative', 'positive' and 'control' words. For the recognition condition two explanatory variables were modelled: 'positive remembered' and 'negative remembered'.…”
Section: Visual Stimulation Paradigmmentioning
confidence: 99%