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statistical parametric mapping toolbox in matlab  (MathWorks Inc)


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    MathWorks Inc statistical parametric mapping toolbox in matlab
    Statistical Parametric Mapping Toolbox In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 673 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/statistical+parametric+mapping+matlab+toolbox/Mapping+Toolbox/pmc13020800-423-18-23
    Average 96 stars, based on 673 article reviews
    statistical parametric mapping toolbox in matlab - by Bioz Stars, 2026-10
    96/100 stars

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    Related Articles

    other:

    Article Title: Evaluation of Statistical Inference on Empirical Resting State fMRI
    Article Snippet: Classical statistics here means least-squares centric approach that lies at the heart of the Statistical Parametric Mapping MATLAB toolbox [ 11 ], [ 12 ].

    Article Title: Characterizing Network Search Algorithms Developed for Dynamic Causal Modeling
    Article Snippet: Considering the computational demands of DCM, originally available as part of the Statistical Parametric Mapping (SPM, http://www.fil.ion.ucl.ac.uk/spm/ ) Matlab toolbox, evaluating large amounts of models requires unmanageable processor time.

    Article Title: Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric
    Article Snippet: In creating the initial conditions for the simulation we registered the second pre-treatment T2 scan to the T1Gd scan using the Statistical Parametric Mapping MATLAB toolbox .

    Article Title: Wearable MEG data recorded during human stepping
    Article Snippet: The code for these methods is freely available in the Statistical Parametric Mapping MATLAB toolbox ( https://github.com/spm ) providing a useful point of departure.

    Derivative Assay:

    Article Title: The effects of dexamphetamine on the resting‐state electroencephalogram and functional connectivity
    Article Snippet: .. The brain image used for Figures , , was derived from the Statistical Parametric Mapping MATLAB toolbox [Wellcome Trust Centre for Neuroimaging, 2009 ]. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 4 caption a7 Power–power coupling. ..



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    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    MathWorks Inc statistical parametric mapping 12 spm12 software with matlab
    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox <t>in</t> <t>MATLAB.</t>
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    Image Search Results


    A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox in MATLAB.

    Journal: NeuroImage

    Article Title: Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis

    doi: 10.1016/j.neuroimage.2025.121311

    Figure Lengend Snippet: A: Group-averaged t values of the contrast right-hand ME > left-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). B: Group-averaged t values of the contrast left-hand ME > right-hand ME ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). C: Group-averaged t values of the contrast right-hand MI > left-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). D: Group-averaged t values of the contrast left-hand MI > right-hand MI ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 17). Results are displayed using the BrainNet toolbox in MATLAB.

    Article Snippet: fMRI analyses were performed using the Statistical Parametric Mapping (SPM) MATLAB toolbox ( http://www.fil.ion.ucl.ac.uk/spm/ , version 12) and custom MATLAB scripts.

    Techniques:

    A: Group-averaged t values showing BOLD correlates of alpha rhythms in channel C3 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). B: group-averaged t values showing neural correlates of alpha rhythms in channel C4 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). C: Group-averaged t values showing neural correlates of alpha rhythms in channel C3 during MI tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). Results are displayed using the BrainNet toolbox in MATLAB.

    Journal: NeuroImage

    Article Title: Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis

    doi: 10.1016/j.neuroimage.2025.121311

    Figure Lengend Snippet: A: Group-averaged t values showing BOLD correlates of alpha rhythms in channel C3 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). B: group-averaged t values showing neural correlates of alpha rhythms in channel C4 during ME tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). C: Group-averaged t values showing neural correlates of alpha rhythms in channel C3 during MI tasks ( p < 0.001, uncorrected with k higher than the expected number of voxels) ( n = 10). Results are displayed using the BrainNet toolbox in MATLAB.

    Article Snippet: fMRI analyses were performed using the Statistical Parametric Mapping (SPM) MATLAB toolbox ( http://www.fil.ion.ucl.ac.uk/spm/ , version 12) and custom MATLAB scripts.

    Techniques: