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

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 anal...

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Vydané v:Frontiers in systems neuroscience Ročník 4; s. 13
Hlavný autor: Yan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland Frontiers Research Foundation 01.01.2010
Frontiers Media S.A
Predmet:
data analysis
DPARSF
Neuroscience
Rest
Resting-state fMRI
SPM
SPM
REST
data analysis
resting-state fMRI
DPARSF
ISSN:1662-5137, 1662-5137
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Shrnutí: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.
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Edited by: Lucina Q. Uddin, Stanford University, USA
Reviewed by: Martin Walter, Otto-von-Guericke-Universität Magdeburg, Germany; Srikanth Ryali, Stanford University, USA
ISSN:1662-5137
1662-5137
DOI:10.3389/fnsys.2010.00013