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metric version of mds  (MathWorks Inc)


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    Structured Review

    MathWorks Inc metric version of mds
    The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric <t>MDS</t> analyses with <t>two</t> <t>dimensions</t> (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).
    Metric Version Of Mds, 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/metric+version+of+mds/pmc06919311-145-20-21?v=MathWorks+Inc
    Average 90 stars, based on 1 article reviews
    metric version of mds - by Bioz Stars, 2026-07
    90/100 stars

    Images

    1) Product Images from "Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics"

    Article Title: Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics

    Journal: NeuroImage

    doi: 10.1016/j.neuroimage.2019.116289

    The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric MDS analyses with two dimensions (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).
    Figure Legend Snippet: The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric MDS analyses with two dimensions (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).

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    Similar Products

    metric version of mds  (MathWorks Inc)
    90
    MathWorks Inc metric version of mds
    The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric <t>MDS</t> analyses with <t>two</t> <t>dimensions</t> (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).
    Metric Version Of Mds, 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/metric+version+of+mds/pmc06919311-145-20-21?v=MathWorks+Inc
    Average 90 stars, based on 1 article reviews
    metric version of mds - by Bioz Stars, 2026-07
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric MDS analyses with two dimensions (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).

    Journal: NeuroImage

    Article Title: Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics

    doi: 10.1016/j.neuroimage.2019.116289

    Figure Lengend Snippet: The unthresholded group-average voxelwise correlation matrices calculated on the volume registered data were converted to distances and submitted to metric MDS analyses with two dimensions (Set 1 in left column, Set 2 in right column). The top row shows scatterplots for all voxels in the field of view of the Yeo et al. (2011) parcellations, using black dots to represent each voxel’s column in the all-to-all distance matrices. The 2- and 4-network parcellations show results by network using color for voxels that agree in their network classification. The 7-network parcellation of Yeo et al. (2011) is shown in the bottom row, with the limbic network (white in the key) rendered as black dots for visibility on a white background. Viewing the progression from 2 to 7 networks provides a concrete rendition of the hierarchical arrangement of the networks at the voxel level, with high dot densities corresponding best visually to the top levels of the hierarchical tree (2 and 4 networks).

    Article Snippet: All MDS analyses compressed the full similarity space to two dimensions for ease of viewing, employed the metric version of MDS (Matlab’s mdscale ), and minimized the squared stress goodness-of-fit criterion.

    Techniques: