Sentence examples for connectivity preferences from inspiring English sources

Exact(3)

Three-dimensional plots of entorhinal connectivity preferences revealed a gradient of decreasing PRC and increasing PHC connectivity running from anterior-lateral to posterior-medial EC.

The functional connectivity preferences of these regions were assessed using an ANOVA with four main effects: group (blind/sighted), cortical region (FFA/PPA), eccentricity (centre/periphery) and hemisphere (right hemisphere/left hemisphere).

If the topographic organization is reliable across participants, then it should be possible to predict the connectivity preference of specific EC voxels within any participant, simply by knowing the connectivity preferences of corresponding voxels in other participants.

Similar(57)

Based on the relative connectivity preference of an EC voxel across subjects the classifier predicts PRC or PHC connectivity preference for the left out subject.

(C ) Classification of PRC vs PHC connectivity preference was tested across subjects based on the x-y-z coordinate of an EC voxel.

However, connectivity preference of voxels in the very anterior-lateral and posterior-medial EC could be predicted with more than 80% accuracy.

Connectivity preference was defined on the basis of the paired t-test t-maps (red: TPRC > PHC > 0; blue: TPHC > PRC > 0).

In addition, we visualized the differential topographic pattern of PRC vs PHC connectivity along the x-y-z direction in three-dimensional plot of connectivity preference for each voxel (see Figure 2B).

(B ) To visualize the 3-dimensional geometry of connectivity, the connectivity preference with PRC vs PHC of each EC voxel was plotted along the x-, y-, and z-axis (red: TPRC > PHC > 0, blue: TPHC > PRC > 0).

In addition, we plotted functional connectivity preference of unilateral (left and right) PRC/PHC seeds with both the ipsi- and contralateral EC to evaluate whether connectivity patterns were symmetric across hemispheres (see Figure 2 figure supplement 1B for results of data set 1).

Based on the predictions of the classifier we created a PRC-connectivity preference ('al-EC') and a PHC-connectivity preference EC ('pm-EC') mask.

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