A manually denoised audio-visual movie watching fMRI dataset for the studyforrest project

摘要

A schematic overview of the four-step denoising workflow. Preprocessing was performed on the original fMRI data and included motion correction, slice timing correction, non-brain structure removal, high-pass filtering (200 s cut-off); all steps were performed without or with spatial smoothing (i.e., FWHM = 0 mm or FWHM = 5 mm). A spatial ICA was next run on the preprocessed data in individual space, producing spatial maps and time series files of the decomposed ICs for each run and each participant. All decomposed ICs were then manually classified into either a known signal, unknown signal, or different categories of artifacts. Finally, all the ICs classified as artifacts were filtered out, producing the final denoised fMRI data. (fMRI: functional magnetic resonance imaging, FWHM: full width half maximum, IC: independent component, ICA: independent component analysis).