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. 2010 May 14:4:13.
doi: 10.3389/fnsys.2010.00013. eCollection 2010.

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI

Yan Chao-Gan  1 , Zang Yu-Feng
Affiliations

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI

Yan Chao-Gan et al. Front Syst Neurosci. .

Abstract

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 Digital Imaging and Communications in Medicine (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, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. 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.

Keywords: DPARSF; REST; SPM; data analysis; resting-state fMRI.

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Figures

Figure 1
Figure 1
Graphical user interface of DPARSF.
Figure 2
Figure 2
Pictures for checking normalization. The normalized functional image was overlaid on a high resolution 3D anatomical image (the opaque one with skull. From “Colin Holmes,” http://imaging.mrc-cbu.cam.ac.uk/downloads/Colin/, also distributed with MRIcroN as ch2) in the MNI space. Users can easily check the accuracy of spatial normalization by visual inspection.
Figure 3.
Figure 3.
Within-condition patterns of ReHo (A), ALFF (B), fALFF (C) and PCC-FC (D). All these methods revealed the pattern of the default mode network. The numbers below the images refer to the MNI z coordinates. The statistical threshold was set at t > 3.89 (P < 0.0001) for one-tailed t-tests (for ReHo, ALFF and fALFF) and |t| > 4. 08 (P < 0.0001) for two-tailed t-test (for FC) and cluster size >135 mm3, which corresponds to a corrected P < 0.0001. LH, left hemisphere; RH, right hemisphere.
See this image and copyright information in PMC

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