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

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          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.

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          Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI.

          In children with attention deficit hyperactivity disorder (ADHD), functional neuroimaging studies have revealed abnormalities in various brain regions, including prefrontal-striatal circuit, cerebellum, and brainstem. In the current study, we used a new marker of functional magnetic resonance imaging (fMRI), amplitude of low-frequency (0.01-0.08Hz) fluctuation (ALFF) to investigate the baseline brain function of this disorder. Thirteen boys with ADHD (13.0+/-1.4 years) were examined by resting-state fMRI and compared with age-matched controls. As a result, we found that patients with ADHD had decreased ALFF in the right inferior frontal cortex, [corrected] and bilateral cerebellum and the vermis as well as increased ALFF in the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem. This resting-state fMRI study suggests that the changed spontaneous neuronal activity of these regions may be implicated in the underlying pathophysiology in children with ADHD.
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            Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis.

            Recent neuroimaging studies have lead to the proposal that rest is characterized by an organized, baseline level of activity, a default mode of brain function that is suspended during specific goal-oriented mental activity. Previous studies have shown that the primary function subserved by the default mode is that of an introspectively oriented, self-referential mode of mental activity. The default mode of brain function hypothesis is readdressed from the perspective of the presence of low-frequency blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal changes (0.012-0.1 Hz) in the resting brain. The results show that the brain during rest is not tonically active in a single mode of brain function. Rather, the findings presented here suggest that the brain recurrently toggles between an introspectively oriented mode (default mode) and a state-of-mind that tentatively might be interpreted as an extrospectively oriented mode that involves a readiness and alertness to changes in the external and internal environment.
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              Unified segmentation

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                Author and article information

                Journal
                Front Syst Neurosci
                Front. Syst. Neurosci.
                Frontiers in Systems Neuroscience
                Frontiers Research Foundation
                1662-5137
                24 February 2010
                14 May 2010
                2010
                : 4
                : 13
                Affiliations
                [1] 1simpleState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University Beijing, China
                Author notes

                Edited by: Lucina Q. Uddin, Stanford University, USA

                Reviewed by: Martin Walter, Otto-von-Guericke-Universität Magdeburg, Germany; Srikanth Ryali, Stanford University, USA

                *Correspondence: Yan Chao-Gan, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China. e-mail: ycg.yan@ 123456gmail.com ; Zang Yu-Feng, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China. e-mail: zangyf@ 123456bnu.edu.cn
                Article
                10.3389/fnsys.2010.00013
                2889691
                20577591
                e00215dd-7384-4504-ad01-a0dd2009fe13
                Copyright © 2010 Yan and Zang.

                This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

                History
                : 30 January 2010
                : 15 April 2010
                Page count
                Figures: 3, Tables: 0, Equations: 0, References: 46, Pages: 7, Words: 5558
                Categories
                Neuroscience
                Methods Article

                Neurosciences
                data analysis,dparsf,rest,spm,resting-state fmri
                Neurosciences
                data analysis, dparsf, rest, spm, resting-state fmri

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