Synaptic dynamics on different time scales in a parallel fiber feedback pathway of the weakly electric fish.

Abstract

Synaptic dynamics comprise a variety of interacting processes acting on a wide range of time scales. This enables a synapse to perform a large array of computations, from temporal and spatial filtering to associative learning. In this study, we describe how changing synaptic gain via long-term plasticity can act to shape the temporal filtering of a synapse through modulation of short-term plasticity. In the weakly electric fish, parallel fibers from cerebellar granule cells provide massive feedback inputs to the pyramidal neurons of the electrosensory lateral line lobe. We demonstrate a long-term synaptic enhancement (LTE) of these synapses that is biochemically similar to the presynaptic long-term potentiation expressed by parallel fibers in the mammalian cerebellum. Using a novel stimulation protocol and a simple modeling paradigm, we then quantify the changes in short-term plasticity during the induction of LTE and show that these changes can be explained by gradual changes in only one model parameter, that which is associated with the baseline probability of transmitter release. These changes lead to a shift in the spike frequency preference of the synapse, suggesting that long-term plasticity is not only involved in controlling the gain of the parallel fiber synapse, but also provides a means of controlling synaptic filtering over multiple time scales.