<p>(A) Fraction of time network adopts synchronous dynamics as a function of rewiring parameter for noise driven identical (I<sup>e</sup><sub>ext</sub> = 1.05 for all neurons f<sub>N</sub> = 0.00005, blue line), non-identical (I<sup>e</sup><sub>ext</sub> = 0.95–1.15, f<sub>N</sub> = 0.00005, green line) and deterministic dynamics for network of non-identical cells (I<sup>e</sup><sub>ext</sub> = 0.95–1.15, red line). (B) The effect of the increasing noise level on the dynamics for the excitatory-only network with P<sub>e</sub> = 0.15 for noise driven identical (I<sup>e</sup><sub>ext</sub> = 1.05 for all neurons, blue line) and non-identical (I<sup>e</sup><sub>ext</sub> = 0.95–1.15, green line).</p
The brain consists of complex interacting networks of excitatory and inhibitory neurons. The spatio-...
<p>(<b>A</b>) The network consists of excitatory (E) and inhibitory (I) neurons. The neurons are cou...
<p>(A) Network performance is compared between a heterogeneous, non-connected network (broken lines,...
<p>(A-D) Raster plots and ISI histograms associated with deterministic dynamics of networks having P...
<p>The synchronous fraction of dynamics as a function of inhibitory connectivity when excitatory con...
<p>(A) Excitatory networks (P<sub>e</sub> = 0.15); (B) excitatory and inhibitory networks (P<sub>e</...
<p>The dynamical mean field results are shown in full lines, numerical simulations as points. <b>a.<...
<p>For noise intensity (a) <i>D</i><sub>0</sub> = 0.005, (b) <i>D</i><sub>0</sub> = 0.01, (c) <i>D</...
<p>For noise intensity (a) <i>D</i><sub>0</sub> = 0.005, (b) <i>D</i><sub>0</sub> = 0.01, (c) <i>D</...
Numerical integration of the dynamics with units receiving additive external white noise, as a proxy...
Inhibition is crucial for the stability of network dynamics. In particular, rewiring inhibitory conn...
<p>(A) Topology of interacting network of excitatory and inhibitory neurons. Here P<sub>e</sub> = 0....
<p>Discrete-time rate evolution. <b>a-b.</b> Network discrete-time activity: numerical integration o...
<p><b>A</b> Color panel is the surface plot of firing rate (averaged ove...
<p><b>A</b> Network-averaged firing rate (meanS.E.M.) vs. ...
The brain consists of complex interacting networks of excitatory and inhibitory neurons. The spatio-...
<p>(<b>A</b>) The network consists of excitatory (E) and inhibitory (I) neurons. The neurons are cou...
<p>(A) Network performance is compared between a heterogeneous, non-connected network (broken lines,...
<p>(A-D) Raster plots and ISI histograms associated with deterministic dynamics of networks having P...
<p>The synchronous fraction of dynamics as a function of inhibitory connectivity when excitatory con...
<p>(A) Excitatory networks (P<sub>e</sub> = 0.15); (B) excitatory and inhibitory networks (P<sub>e</...
<p>The dynamical mean field results are shown in full lines, numerical simulations as points. <b>a.<...
<p>For noise intensity (a) <i>D</i><sub>0</sub> = 0.005, (b) <i>D</i><sub>0</sub> = 0.01, (c) <i>D</...
<p>For noise intensity (a) <i>D</i><sub>0</sub> = 0.005, (b) <i>D</i><sub>0</sub> = 0.01, (c) <i>D</...
Numerical integration of the dynamics with units receiving additive external white noise, as a proxy...
Inhibition is crucial for the stability of network dynamics. In particular, rewiring inhibitory conn...
<p>(A) Topology of interacting network of excitatory and inhibitory neurons. Here P<sub>e</sub> = 0....
<p>Discrete-time rate evolution. <b>a-b.</b> Network discrete-time activity: numerical integration o...
<p><b>A</b> Color panel is the surface plot of firing rate (averaged ove...
<p><b>A</b> Network-averaged firing rate (meanS.E.M.) vs. ...
The brain consists of complex interacting networks of excitatory and inhibitory neurons. The spatio-...
<p>(<b>A</b>) The network consists of excitatory (E) and inhibitory (I) neurons. The neurons are cou...
<p>(A) Network performance is compared between a heterogeneous, non-connected network (broken lines,...