<p>Thin solid curve: firing rates of both populations in a stable symmetric state (both populations at equal rates); thick solid curves: _ring rates of the two selective populations in an asymmetric state (one population at high rate, the other at low rate). Thick dashed lines show the position of the unstable fixed point. Dotted vertical lines indicate the boundaries of the three different regimes present in the system, as predicted by the mean field approximation. At <i>λ̅</i> = <i>λ̅</i><i><sub>c</sub></i> the spontaneous state loses its stability. Error bars indicate the sample standard deviation of the firing rates.</p
<p>A) Mean firing rate of the excitatory neurons. B) Integral of the auto-covariance function of the...
<p>(<b>A</b>) Solid line: as a function of the learning rate (cf. <a href="http://www.ploscompbiol...
<p><b>a-b-c.</b> Statistical characterization for <i>τ</i><sub><i>r</i></sub> = 0.5 ms: input varian...
<p>Mean field analysis of the model assessing the dependence of the network behaviour on the potenti...
<p>The fraction of infected population , versus for different network adaptation rates, with parame...
<p>(A) The bifurcation diagram of Eq. (16) for the mean field . (B) Activity distribution in the sta...
<p>(<b>A</b>) Schematic of the mean field model. Plastic synapses are indicated by <b>*</b>. (<b>B</...
<p>Discrete-time rate evolution. <b>a-b.</b> Network discrete-time activity: numerical integration o...
<p>The joint degree distributions <i>N</i><sub><i>kk</i>′</sub> for the mean-field calculations were...
<p><b>A:</b> The number of unique complexes in independent simulations as a function of time: each c...
<p>(A) Bifurcation diagram with and with the variation of . Here, the asymptotical dynamics of the ...
<p>Panel A: noisy mean-field simulations; panel B: <i>ex-vivo</i> data. Random large excursions of t...
<p>Panel <b>A</b> represents the sketch of a recurrent network where a clear segregation between sub...
<p>The dynamical mean field results are shown in full lines, numerical simulations as points. <b>a.<...
<p>Dependence of the modulations of the mean activity and covariances on the driving frequency <i>ω<...
<p>A) Mean firing rate of the excitatory neurons. B) Integral of the auto-covariance function of the...
<p>(<b>A</b>) Solid line: as a function of the learning rate (cf. <a href="http://www.ploscompbiol...
<p><b>a-b-c.</b> Statistical characterization for <i>τ</i><sub><i>r</i></sub> = 0.5 ms: input varian...
<p>Mean field analysis of the model assessing the dependence of the network behaviour on the potenti...
<p>The fraction of infected population , versus for different network adaptation rates, with parame...
<p>(A) The bifurcation diagram of Eq. (16) for the mean field . (B) Activity distribution in the sta...
<p>(<b>A</b>) Schematic of the mean field model. Plastic synapses are indicated by <b>*</b>. (<b>B</...
<p>Discrete-time rate evolution. <b>a-b.</b> Network discrete-time activity: numerical integration o...
<p>The joint degree distributions <i>N</i><sub><i>kk</i>′</sub> for the mean-field calculations were...
<p><b>A:</b> The number of unique complexes in independent simulations as a function of time: each c...
<p>(A) Bifurcation diagram with and with the variation of . Here, the asymptotical dynamics of the ...
<p>Panel A: noisy mean-field simulations; panel B: <i>ex-vivo</i> data. Random large excursions of t...
<p>Panel <b>A</b> represents the sketch of a recurrent network where a clear segregation between sub...
<p>The dynamical mean field results are shown in full lines, numerical simulations as points. <b>a.<...
<p>Dependence of the modulations of the mean activity and covariances on the driving frequency <i>ω<...
<p>A) Mean firing rate of the excitatory neurons. B) Integral of the auto-covariance function of the...
<p>(<b>A</b>) Solid line: as a function of the learning rate (cf. <a href="http://www.ploscompbiol...
<p><b>a-b-c.</b> Statistical characterization for <i>τ</i><sub><i>r</i></sub> = 0.5 ms: input varian...