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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| Veröffentlicht in: | Frontiers in systems neuroscience Jg. 4; S. 13 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Switzerland
Frontiers Research Foundation
01.01.2010
Frontiers Media S.A |
| Schlagworte: | |
| ISSN: | 1662-5137, 1662-5137 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | 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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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 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 |