<p>The mean correlation matrices derived from subgroup 1 (A) and subgroup 2 (B) are highly similar to each other (C). The regional nodal metrics also exhibited strong correlations between the two subgroups (D) over a wide range of sparsity thresholds (degree: r = 0.56±0.14; efficiency: r = 0.57±0.16; and betweenness: r = 0.57±0.20). These results suggest a high reproducibility of fNIRS-based brain network metrics across subjects.</p
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuati...
Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping t...
<p>The mean correlation matrices derived from sub-dataset 1 (A) and sub-dataset 1 (B) are highly sim...
<div><p>Recent research has demonstrated the feasibility of combining functional near-infrared spect...
Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy ...
<div><p>Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) ...
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attr...
<p>(A) Hierarchy coefficients,, and (B) modularity, <i>Q</i>, of the real (red) and random (green) n...
Graph theory provides many metrics of complex network organization that can be applied to analysis o...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
The reliability of graph metrics calculated in network analysis is essential to the interpretation o...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuati...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuati...
Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping t...
<p>The mean correlation matrices derived from sub-dataset 1 (A) and sub-dataset 1 (B) are highly sim...
<div><p>Recent research has demonstrated the feasibility of combining functional near-infrared spect...
Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy ...
<div><p>Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) ...
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attr...
<p>(A) Hierarchy coefficients,, and (B) modularity, <i>Q</i>, of the real (red) and random (green) n...
Graph theory provides many metrics of complex network organization that can be applied to analysis o...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
The reliability of graph metrics calculated in network analysis is essential to the interpretation o...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuati...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuati...
Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping t...