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data visualization intermediate toolbox users  (MathWorks Inc)


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    MathWorks Inc data visualization intermediate toolbox users
    Figure 4. Demonstrations of voxel-wise <t>visualization.</t> This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS <t>toolbox.</t> (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional <t>data”,</t> several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.
    Data Visualization Intermediate Toolbox Users, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2335 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    1) Product Images from "MACS - a new SPM toolbox for model assessment, comparison and selection."

    Article Title: MACS - a new SPM toolbox for model assessment, comparison and selection.

    Journal: Journal of neuroscience methods

    doi: 10.1016/j.jneumeth.2018.05.017

    Figure 4. Demonstrations of voxel-wise visualization. This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS toolbox. (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional data”, several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.
    Figure Legend Snippet: Figure 4. Demonstrations of voxel-wise visualization. This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS toolbox. (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional data”, several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.

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    data visualization intermediate toolbox users  (MathWorks Inc)
    96
    MathWorks Inc data visualization intermediate toolbox users
    Figure 4. Demonstrations of voxel-wise <t>visualization.</t> This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS <t>toolbox.</t> (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional <t>data”,</t> several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.
    Data Visualization Intermediate Toolbox Users, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/data visualization intermediate toolbox users/product/MathWorks Inc
    Average 96 stars, based on 1 article reviews
    data visualization intermediate toolbox users - by Bioz Stars, 2026-06
    96/100 stars
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    Figure 4. Demonstrations of voxel-wise visualization. This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS toolbox. (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional data”, several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.

    Journal: Journal of neuroscience methods

    Article Title: MACS - a new SPM toolbox for model assessment, comparison and selection.

    doi: 10.1016/j.jneumeth.2018.05.017

    Figure Lengend Snippet: Figure 4. Demonstrations of voxel-wise visualization. This figure shows SPM graphics windows resulting from voxel-wise visualization tools included in the MACS toolbox. (A) Using the module “inspect goodness of fit”, measured and predicted fMRI signal are shown alongside goodness-of-fit measures (see Section 2.1.1) which can be browsed for every in-mask voxel included in a particular first-level analysis (see Ashburner et al., 2016, sec. 31.2). The lower panel highlights voxels with the top 5% (yellow, good fit) and the bottom 5% (red, bad fit) in terms of coefficient of determination (R2) for this GLM. (B) Using the module “visualize high-dimensional data”, several data points in each brain region can be displayed and browsed in a voxel-wise fashion. The lower panel highlights voxels in which the R2 of a GLM (the same as in A) is larger than 0.¯3. The upper panel bar plots beta estimates from the four experimental condition regressors of this model, indicating a negative effect of both two-level factors in this voxel (see Ashburner et al., 2016, fig. 31.1). Note that this feature may also be used to display voxel-wise posterior probabilities or model frequencies in large model spaces for comparing model preferences in different regions of interest.

    Article Snippet: Examples are given in Figures 3 and 4: - Figure 3 : batch for cross-validated Bayesian model selection - Figure 4A: output from goodness-of-fit inspection for a GLM - Figure 4B: output from high-dimensional data visualization Intermediate toolbox users may also use the batch editor, but will additionally call the interface functions via MATLAB’s command-line interface.

    Techniques: