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data preprocessing assistant for resting-state fmri (dparsf) software  (MathWorks Inc)


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    MathWorks Inc data preprocessing assistant for resting-state fmri (dparsf) software
    Data Preprocessing Assistant For Resting State Fmri (Dparsf) Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/fmri+data+preprocessing/pmc11978534-132-22-27
    Average 90 stars, based on 1 article reviews
    data preprocessing assistant for resting-state fmri (dparsf) software - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Reduced local functional connectivity correlates with atypical performances in children with autism spectrum disorder
    Article Snippet: The rs-fMRI data of the 28 ASD subjects and the 23 control images were separately processed using the Data Preprocessing Assistant for Resting-State fMRI (DPARSF) software in Matlab 2017b (David & Skilbeck, ).

    Article Title: Potential correlations between asymmetric disruption of functional connectivity and metabolism in major depressive disorder.
    Article Snippet: Brain Research 1838 (2024) 148977 Processing Assistant for Resting-State fMRI (DPARSF) software (5.1) in MATLAB (Chao-Gan and Yu-Feng, 2010).

    Article Title: Brain overlapping system-level architecture influenced by external magnetic stimulation and internal gene expression in AD-spectrum patients.
    Article Snippet: The brain overlapping system-level architecture is associated with functional information integration in the multiple roles of the same region, and it has been developed as an underlying novel biomarker of brain disease and may characterise the indicators for the treatment of Alzheimer’s disease (AD).. However, it remains uncertain whether these changes are influenced by external magnetic stimulation and internal gene expression.. A total of 73 AD-spectrum patients (52 with true stimulation and 21 with sham stimulation) were underwent four-week neuronavigated transcranial magnetic stimulation (rTMS).

    Article Title: Functional MRI Analysis of Brain Activity in Rats With Diabetic Bladder Dysfunction
    Article Snippet: Finally, 12 NC rats and 12 DM rats were included in the comparative analysis of rs‐fMRI. fMRI data were preprocessed using Statistical Parametric Mapping (SPM12, Wellcome Trust Centre for Neuroimaging) and Data Processing Assistant for Resting‐State fMRI (DPARSF) on MATLAB R2014b.

    Article Title: Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.
    Article Snippet: Background: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in clinical practice.. Traditional neuroimaging studies have focused on specific regions of interest, but few have employed whole-brain analyses like regional homogeneity (ReHo).. This study aims to differentiate MDD from BD by identifying key brain regions with abnormal ReHo and using advanced machine learning techniques to improve diagnostic accuracy.

    Magnetic Resonance Imaging:

    Article Title: Altered brain activity associated with premature ejaculation improved by electroacupuncture in rats
    Article Snippet: .. The MRI data preprocessing was performed with Statistical Parametric Mapping (SPM8) and Data Processing Assistant for Resting-State fMRI (DPARSF) software based on MATLAB, with the following steps: (1) data format conversion; (2) discarding the first 10 functional time points; (3) slice timing correction; (4) head motion correction; (5) functional and structural image reorientation; (6) structural image coregistration to corresponding functional images; (7) structural images segmented into grey matter, white matter, and cerebrospinal fluid; (8) functional images spatially normalized into the standard space. ..

    Software:

    Article Title: Altered brain activity associated with premature ejaculation improved by electroacupuncture in rats
    Article Snippet: .. The MRI data preprocessing was performed with Statistical Parametric Mapping (SPM8) and Data Processing Assistant for Resting-State fMRI (DPARSF) software based on MATLAB, with the following steps: (1) data format conversion; (2) discarding the first 10 functional time points; (3) slice timing correction; (4) head motion correction; (5) functional and structural image reorientation; (6) structural image coregistration to corresponding functional images; (7) structural images segmented into grey matter, white matter, and cerebrospinal fluid; (8) functional images spatially normalized into the standard space. ..

    Article Title: Neural basis underlying the effects of trait and state anxiety on premature ejaculation revealed by resting-state interhemispheric functional connectivity.
    Article Snippet: Introduction: Anxiety is considered to play a key role in the development and maintenance of premature ejaculation (PE).. In addition, PE patients often co-occur with anxiety, however, the central mechanisms underlying this comorbidity have remained elusive.. This study aimed to explore whether trait and state anxiety-related PE shared common or distinct mechanisms in the brain.

    Functional Assay:

    Article Title: Altered brain activity associated with premature ejaculation improved by electroacupuncture in rats
    Article Snippet: .. The MRI data preprocessing was performed with Statistical Parametric Mapping (SPM8) and Data Processing Assistant for Resting-State fMRI (DPARSF) software based on MATLAB, with the following steps: (1) data format conversion; (2) discarding the first 10 functional time points; (3) slice timing correction; (4) head motion correction; (5) functional and structural image reorientation; (6) structural image coregistration to corresponding functional images; (7) structural images segmented into grey matter, white matter, and cerebrospinal fluid; (8) functional images spatially normalized into the standard space. ..



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    Figure 1. The schematic illustration of the main method. (A) The procedures to obtain multiscale FCNs. (i) the <t>fMRI</t> <t>data</t> from one individual is inputted and preprocessed. (ii) The application of the Schaefer’s multiscale atlases to the fMRI data. The black border lines indicate boundaries of ROIs and the colors encode the resting-state network (RSN) to which the ROI belongs. The RSNs include DMN, frontoparietal network (FP), limbic network (LIM), salience network (SAL), attention network (ATT), somatomotor network (SM), and visual network (VIS). (iii) The extraction of ROI-averaged signals. (iv) The construction of multiscale FCNs from individual fMRI data. (B) The architecture for multiscale atlas-based GCN (MAGCN). The multiscale FCNs are extracted via a series of GCNs connected by the APs. The nodal features h are integrated with skip connections and concatenations, based on which individualized diagnosis is generated.
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    Image Search Results


    Figure 1. The schematic illustration of the main method. (A) The procedures to obtain multiscale FCNs. (i) the fMRI data from one individual is inputted and preprocessed. (ii) The application of the Schaefer’s multiscale atlases to the fMRI data. The black border lines indicate boundaries of ROIs and the colors encode the resting-state network (RSN) to which the ROI belongs. The RSNs include DMN, frontoparietal network (FP), limbic network (LIM), salience network (SAL), attention network (ATT), somatomotor network (SM), and visual network (VIS). (iii) The extraction of ROI-averaged signals. (iv) The construction of multiscale FCNs from individual fMRI data. (B) The architecture for multiscale atlas-based GCN (MAGCN). The multiscale FCNs are extracted via a series of GCNs connected by the APs. The nodal features h are integrated with skip connections and concatenations, based on which individualized diagnosis is generated.

    Journal: Cerebral cortex (New York, N.Y. : 1991)

    Article Title: Multiscale functional connectome abnormality predicts cognitive outcomes in subcortical ischemic vascular disease.

    doi: 10.1093/cercor/bhab507

    Figure Lengend Snippet: Figure 1. The schematic illustration of the main method. (A) The procedures to obtain multiscale FCNs. (i) the fMRI data from one individual is inputted and preprocessed. (ii) The application of the Schaefer’s multiscale atlases to the fMRI data. The black border lines indicate boundaries of ROIs and the colors encode the resting-state network (RSN) to which the ROI belongs. The RSNs include DMN, frontoparietal network (FP), limbic network (LIM), salience network (SAL), attention network (ATT), somatomotor network (SM), and visual network (VIS). (iii) The extraction of ROI-averaged signals. (iv) The construction of multiscale FCNs from individual fMRI data. (B) The architecture for multiscale atlas-based GCN (MAGCN). The multiscale FCNs are extracted via a series of GCNs connected by the APs. The nodal features h are integrated with skip connections and concatenations, based on which individualized diagnosis is generated.

    Article Snippet: The sagittal T1-weighted images covering the whole brain were acquired by a 3Dfast spoiled gradient recalled echo sequence: TR = 5.6 ms, TE = 1.8 ms, matrix = 256 × 256, inversion time = 450 ms, flip angle = 15◦, slice thickness/gap = 1/0 mm, number of slices = 156, gap = 0, and FOV = 256 × 256 mm2. fMRI Data Preprocessing We adopt the standardized pipeline from the public available toolbox Data Processing Assistant for Resting-State fMRI (Yan and Zang 2010) in Matlab (Mathworks.

    Techniques: Extraction, Biomarker Discovery, Generated