Sentence examples for dual regression from inspiring English sources

This flexibility owes to the reduced spatial and temporal orthogonality constraints of template based rotation as compared to dual regression.

For inter group analysis was carried out using dual regression (FSL technique) that allows for voxel-wise comparisons of resting-state [21, 22].

The dual regression analysis was performed with variance normalization because reflects differences in both activity and spatial spread of the network.

Regarding examined metrics, independent component analysis with dual regression, local functional homogeneity and functional homotopic connectivity were the three mostly reliable RFMRI metrics.

We observed that template based rotation and dual regression are approximately equivalent in detecting fcMRI differences between young and old subjects, demonstrating similar effect sizes for group differences and similar reliability metrics across 12 cortical networks.

When performing inter-network and sub-network connectivity analyses, we observed that template based rotation offered greater flexibility, larger group differences, and more stable connectivity estimates as compared to dual regression and seed based analyses.

Next, a standard dual-regression approach was used to regress these group level RSNs of interest against each individual subject's data.

Using independent component analysis (ICA) and dual-regression, the results revealed age-related increases in RSFC across a range of RSNs, including task-positive networks in frontal and parietal regions.

Both template based rotation and dual-regression demonstrated larger effect sizes and comparable reliabilities as compared to seed based correlation analysis, though all three methods yielded similar patterns of network differences.

The dual-regression (DR) retrieval algorithm is a fast computational procedure designed to maximize the information content; minimize the propagation of noise; and retrieve the most probable atmospheric profiles, cloud properties, and surface properties from satellite-observed high-spectral-resolution radiance measurements.

This study proposes an iterative dual-regression (DR) approach with sparse prior regularization to better estimate an individual's neuronal activation using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method).