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Chunk #3 — Methods — Functional Magnetic Resonance Imaging Data

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Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function.
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Data preprocessing (using AFNI software29) included slice timing and motion correction, spatial normalization to Talairach space with a resampled resolution of 3 × 3 × 3 mm3, nonlinear registration,30 quadratic detrending, gaussian spatial smoothing (full width half maximum, 6 mm), and mean-based intensity normalization. Mean relative head movement (||motion||2) was evaluated with the following mean Euclidean norm of the 6-motion parameter derivatives: ‖motion‖2=1N∑i=1N‖motioni‖2 where ‖motioni‖2=Δdix2+Δdiy2+Δdiz2+Δαi2+Δβi2+Δγi2 The rotational displacements were converted from radians to millimeters by calculating displacement on the surface of a sphere with a radius of 60 mm. We excluded participants with excessive head motion, including 14 during the resting scan and 6 during the WM task scan (including 4 with overlap from the resting scan) (||motion||2, > 0.25 mm). We also excluded 1 participant with poor WM task accuracy (>2.5 SD below the mean), leaving 37 participants (including 19 women) in the analysis. Mean (SD) head movement was 0.11 (0.05) mm (during abstinence) and 0.09 (0.05) mm (during smoking).