<p>The mean correlation matrices derived from sub-dataset 1 (A) and sub-dataset 1 (B) are highly similar to each other (C). The regional nodal metrics also exhibited strong correlations between the two sub-datasets (D) over a wide range of sparsity thresholds (degree: r = 0.79±0.06; efficiency: r = 0.81±0.08; and betweenness: r = 0.68±0.14). These results suggest a high reproducibility of fNIRS-based brain network metrics over time.</p
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...
<p>The mean correlation matrices derived from subgroup 1 (A) and subgroup 2 (B) are highly similar t...
<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 ...
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attr...
<div><p>Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) ...
Graph theory provides many metrics of complex network organization that can be applied to analysis o...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
The reliability of graph metrics calculated in network analysis is essential to the interpretation o...
<p>(A) Hierarchy coefficients,, and (B) modularity, <i>Q</i>, of the real (red) and random (green) n...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
An increasing number of network metrics have been applied in network analysis. If metric relations w...
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...
<p>The mean correlation matrices derived from subgroup 1 (A) and subgroup 2 (B) are highly similar t...
<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 ...
Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attr...
<div><p>Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) ...
Graph theory provides many metrics of complex network organization that can be applied to analysis o...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize...
The reliability of graph metrics calculated in network analysis is essential to the interpretation o...
<p>(A) Hierarchy coefficients,, and (B) modularity, <i>Q</i>, of the real (red) and random (green) n...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
An increasing number of network metrics have been applied in network analysis. If metric relations w...
Computational network analysis provides new methods to analyze the human connectome. Brain structura...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...
Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be rela...