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spm 12 matlab toolbox  (MathWorks Inc)


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    MathWorks Inc spm 12 matlab toolbox
    Spm 12 Matlab Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 447 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/spm 12 matlab toolbox/product/MathWorks Inc
    Average 96 stars, based on 447 article reviews
    spm 12 matlab toolbox - by Bioz Stars, 2026-04
    96/100 stars

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    Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
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    Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
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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 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:

    Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding SPM rmANOVA results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.

    Journal: Journal of biomechanics

    Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

    doi: 10.1016/j.jbiomech.2025.112615

    Figure Lengend Snippet: Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding SPM rmANOVA results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.

    Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

    Techniques:

    Fig. 2. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different running speeds (10 km/h and 15 km/h) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of three shoe conditions are represented for each running speed. The significant speed effects in SPM rmANOVA are shown as the gray areas. Lower row shows the corresponding SPM rmANOVA results for the main factor speed with clustered p- values. F* values indicate the corresponding thresholds for α = 0.05.

    Journal: Journal of biomechanics

    Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

    doi: 10.1016/j.jbiomech.2025.112615

    Figure Lengend Snippet: Fig. 2. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different running speeds (10 km/h and 15 km/h) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of three shoe conditions are represented for each running speed. The significant speed effects in SPM rmANOVA are shown as the gray areas. Lower row shows the corresponding SPM rmANOVA results for the main factor speed with clustered p- values. F* values indicate the corresponding thresholds for α = 0.05.

    Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

    Techniques:

    Fig. 3. SPM rmANOVA results for the interaction effects between shoe and speed conditions. F* values indicate the corresponding thresholds for α = 0.05.

    Journal: Journal of biomechanics

    Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

    doi: 10.1016/j.jbiomech.2025.112615

    Figure Lengend Snippet: Fig. 3. SPM rmANOVA results for the interaction effects between shoe and speed conditions. F* values indicate the corresponding thresholds for α = 0.05.

    Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

    Techniques: