Dynamics and stability of learned weights.

<p><b>(A)</b> Evolution of synaptic weights in the network during plasticity. After each batch of learning, weights are frozen and compared to the weights in the previous batch. The difference in the weights is averaged over populations, for all synapses, respectively. On average, weight changes decrease over batches, indicating the convergence of the learning process. The weights established under evoked activity are also stable for spontaneous activity, in absence of any specific stimulation (batch 41 and later, after the vertical dashed line). Here, the plasticity period is continued for extra 10 batches, where neurons are only receiving an untuned background input (with an input rate of <i>s</i>_<i>b</i>/2 and <i>μ</i> = 0, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004307#sec011" target="_blank">Materials and Methods</a>). <b>(B)</b> Distribution of weights are shown separately for E → E, E → I and I → E weights, for evoked and spontaneous states, respectively. In each case, two distributions are shown, one sampling the beginning and one sampling the end of the corresponding learning phase. <b>(C)</b> Distribution of weights extracted at the end of each trial batch (every 2 s) is plotted for all plastic connections in a pseudo-color map. Note the logarithmic scale of the color code.