Journal: Frontiers in Neuroscience

Article Title: Brain oscillatory activity during motor preparation: effect of directional uncertainty on beta, but not alpha, frequency band

doi: 10.3389/fnins.2015.00246

Figure Lengend Snippet: Multidimensional scaling analysis of the time-series of alpha and beta relative power from each voxel within the significant brain regions . (A) Projection of each data point in the 3-D MDS space. The data for alpha- (blue) and beta- (red) bands were colored differently to identify them in the MDS space. (B,C) Projection of the alpha-band and the beta-band data points, respectively. The data from the clusters obtained with the cluster analysis are identified by different colors (same as in Figure ). These results illustrate that each cluster was located in a specific region within the MDS space, but data points varied continuously between those regions.

Article Snippet: To this end, we entered the time-series from all voxels with significant alpha- and beta-band activity in the MDS analysis (implemented using MATLAB function mdscale).

Techniques:

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: