Spontaneous Activity Defines Effective Convergence Ratios in an Inhibitory Circuit

Many neurons fire spontaneously, and the rate of this firing is subject to neuromodulation. How this firing affects functional connectivity within a neural network remains largely unexplored. Here we show that changes in spontaneous firing of cartwheel interneurons in the mouse dorsal cochlear nucleus (DCN) alter the effective convergence ratio of interneurons onto their postsynaptic targets through short-term synaptic plasticity. Spontaneous firing of cartwheel cells led to activity-dependent synaptic depression of individual cartwheel synapses. Depression was rapid and profound at stimulation frequencies between 10 and 200 Hz, suggesting the presence of high release probability (Pr) vesicles at these inhibitory synapses. Weak, transient synaptic facilitation could be induced after synapses were predepressed, indicating that low-Pr vesicles are also recruited, and may thus support steady-state transmission. A two-pool vesicle depletion model with 10-fold differences in Pr could account for the synaptic depression over a wide range of stimulus conditions. As a result of depression during high spontaneous activity, more cartwheel interneurons were required for effective inhibition. Convergence of four interneurons was sufficient to compensate for the effects of depression during physiologically expected rates of activity. By simulating synaptic release during spontaneous firing, we found that recruitment of low-Pr vesicles at the synapse plays a critical role in maintaining effective inhibition within a small population of interneurons. The interplay between spontaneous spiking, short-term synaptic plasticity, and vesicle recruitment thus determines the effective size of a convergent neural network.