<p>The brain networks under each condition showed higher local efficiency than the matched random networks (A) and higher global efficiency than the matched regular networks (B) at the whole cost range between 0.1 and 0.4 used in the present study. Thus, the brain networks under each condition exhibited small-world properties. The brain networks were also found to be economical because both the local and global efficiency were much higher than the required cost.</p
<p>Plots show the changes in small-world parameters (Cp, Lp, γ, λ and σ), network efficiency (Local ...
<p>Note: <i>Cp</i>, the average clustering coefficient of all of the nodes in the brain network; <i>...
<p>Local and global efficiency values of the generated network consisting of 2000 neurons, placed in...
<p>The functional brain networks showed higher local efficiency than that of the matched random netw...
<p>Global (E<sub>g</sub>) and local (E<sub>l</sub>) efficiencies are depicted as a function of wired...
<p>Global and local efficiency (<i>y</i>-axis) as a function of cost (<i>x</i>-axis) for a random gr...
<p>(A) The functional networks of all cognitive conditions showed a higher clustering coefficient (<...
It is widely believed that the formation of brain network architecture is under the pressure of opti...
Brain anatomical networks are sparse, complex, and have economical small-world properties. We invest...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
<p>Error bars correspond to standard deviation of the mean for 1000 comparable random null networks ...
We introduce the concept of efficiency of a network as a measure of how efficiently it exchanges inf...
<p>(A) The clustering coefficient and (B) the characteristic path length are shown as a function of ...
<p>Error bars correspond to standard deviation of the mean for 1000 comparable random null networks ...
<p>(A) global efficiency and (B) local efficiency over the whole range of 0.03~0.50 for random (gree...
<p>Plots show the changes in small-world parameters (Cp, Lp, γ, λ and σ), network efficiency (Local ...
<p>Note: <i>Cp</i>, the average clustering coefficient of all of the nodes in the brain network; <i>...
<p>Local and global efficiency values of the generated network consisting of 2000 neurons, placed in...
<p>The functional brain networks showed higher local efficiency than that of the matched random netw...
<p>Global (E<sub>g</sub>) and local (E<sub>l</sub>) efficiencies are depicted as a function of wired...
<p>Global and local efficiency (<i>y</i>-axis) as a function of cost (<i>x</i>-axis) for a random gr...
<p>(A) The functional networks of all cognitive conditions showed a higher clustering coefficient (<...
It is widely believed that the formation of brain network architecture is under the pressure of opti...
Brain anatomical networks are sparse, complex, and have economical small-world properties. We invest...
<p>(A) Clustering coefficient, <i>C<sub>p</sub></i>; (B) characteristic path length, <i>L<sub>p</sub...
<p>Error bars correspond to standard deviation of the mean for 1000 comparable random null networks ...
We introduce the concept of efficiency of a network as a measure of how efficiently it exchanges inf...
<p>(A) The clustering coefficient and (B) the characteristic path length are shown as a function of ...
<p>Error bars correspond to standard deviation of the mean for 1000 comparable random null networks ...
<p>(A) global efficiency and (B) local efficiency over the whole range of 0.03~0.50 for random (gree...
<p>Plots show the changes in small-world parameters (Cp, Lp, γ, λ and σ), network efficiency (Local ...
<p>Note: <i>Cp</i>, the average clustering coefficient of all of the nodes in the brain network; <i>...
<p>Local and global efficiency values of the generated network consisting of 2000 neurons, placed in...