Sentence examples for each of the connectivity from inspiring English sources

We entered each of the connectivity values reflecting dopaminergic modulation of striato-cortical connectivity (putamen-to-preSMA, putamen-to-M1, preSMA-to-putamen, M1-to-putamen) into the regression model starting with the variable explaining most variance (Scheller et al., 2013; Herz et al., 2014 a ).

The primary justification for this choice of k is that when cluster analyses with higher k were performed on our data set, each of the connectivity maps associated with the resulting clusters typically corresponded closely with one of the 3 maps found using k = 3.

After that, a preselected T-value (T-threshold = 2) is used to threshold the statistical value calculated at each edge of the connectivity matrix to identify the set of suprathreshold edges.

Each row/column of the connectivity matrix corresponds to a distinct seed region of interest (ROI) or a node, such that position (i, j) represents the correlation between the ith and jth regions.

We use the option "classification targets" of probtrackx to obtain per each target a map of the connectivity of the STN where for each STN voxel we compute the number of tracts (on a total of 5,000) reaching the target.

Both an analytical and a numerical implementation of the formulation are described; each require a description of the connectivity of the tensegrity, with the iterative numerical method also requiring a random starting vector of member force densities.

Because large numbers of compounds and associated structure-activity relationships (SAR) data are published in journals and patents every year, many new data sources have become available, each covering different aspects of the connectivity between the SAR-related entities [4].

We identify reserve site configurations that provide the highest persistence values for each of the metapopulation connectivity models.

In these cases networks are constructed separately for each condition and the context of the connectivity can then be examined to identify modules (or gene sets) putatively causal for phenotypic traits.

To reach the most economical process configuration, the superstructure model has been developed including binary interaction parameter regression of the NRTL-RK thermodynamic model, unit operation modeling, and identification of the connectivity of each of the unit operations in the superstructure.

Evaluation of the connectivity within each network using edges/node reveals large differences between the networks.