Calcium and synaptic dynamics underlying reverberatory activity in neuronal networks

Persistent activity is postulated to drive neural network plasticity and learning. To investigate its underlying cellular mechanisms, we developed a biophysically tractable model that explains the emergence, sustenance, and eventual termination of short-term persistent activity. Using the model, we reproduced the features of reverberating activity that were observed in small (50-100 cells) networks of cultured hippocampal neurons, such as the appearance of polysynaptic current clusters, the typical inter-cluster intervals, the typical duration of reverberation, and the response to changes in extra-cellular ionic composition. The model relies on action potential-triggered residual presynaptic calcium, which we suggest plays an important role in sustaining reverberations. We show that reverberatory activity is maintained by enhanced asynchronous transmitter release from pre-synaptic terminals, which in itself depends on the dynamics of residual presynaptic calcium. Hence, asynchronous release, rather than being a "synaptic noise", can play an important role in network dynamics. Additionally, we found that a fast timescale synaptic depression is responsible for oscillatory network activation during reverberations, whereas the onset of a slow timescale depression leads to the termination of reverberation. The simplicity of our model enabled a number of predictions that were confirmed by additional analyses of experimental manipulations.