DPARSF: a MATLAB toolbox for" pipeline" data analysis of resting-state fMRI

C Yan, Y Zang - Frontiers in systems neuroscience, 2010 - frontiersin.org
Frontiers in systems neuroscience, 2010frontiersin.org
Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more
attention because of its effectiveness, simplicity and non-invasiveness in exploration of the
intrinsic functional architecture of the human brain. However, user-friendly toolbox for"
pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in
Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST),
we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State …
Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the DICOM files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity (FC), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF). DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.
Frontiers
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