Spike-Timing-Dependent Plasticity and Short-Term Plasticity Jointly Control the Excitation of Hebbian Plasticity without
Weight Constraints in Neural Networks
Distribution of the coefficient of variation (CV) at each synapse at Poisson inputs with 10 Hz. Each subfigure Figure 8 depicts the distribution of the CV at the given synapse of both neuron A and neuron B at Poisson inputs mean firing rate 10 Hz. For example, As shown in the leftmost subfigure shows the variation of CV of synapses from presynaptic neuron B to postsynaptic neuron A. Similarly, depicts the distribution of CV of synapses from presynaptic neuron A to postsynaptic neuron B. Moreover, the slopes of the mean release probability, and , were determined using linear regression analysis and give the slope of CV of from bin 1 to 150 and bin 150 to 200, respectively. Similarly, and give the CV of from bin 1 to bin 150 and from 150 to 200, respectively. As depicted in all these subfigures, at all the synapses when its around 200 bins, the difference of the CVs of neuron A and neuron B was about 0.001 and time functions of CVs of both neurons were paralleled to each other.