Determining synaptic parameters using high-frequency activation

Abstract

Background The specific properties of a synapse determine how neuronal activity evokes neurotransmitter release. Evaluating changes in synaptic properties during sustained activity is essential to understanding how genetic manipulations and neuromodulators regulate neurotransmitter release. Analyses of postsynaptic responses to high-frequency stimulation have provided estimates of the size of the readily-releasable pool (RRP) of vesicles (N0) and the probability of vesicular release (p) at multiple synapses. New Method Here, we introduce a model-based approach at the calyx of Held synapse in which depletion and the rate of replenishment (R) determine the number of available vesicles, and facilitation leads to a use-dependent increase in p when initial p is low. Results When p is high and R is low, we find excellent agreement between estimates based on all three methods and the model. However, when p is low or when significant replenishment occurs between stimuli, estimates of different methods diverge, and model estimates are between the extreme estimates provided by the other approaches. Comparison with Other Methods We compare our model-based approach to three other approaches that rely on different simplifying assumptions. Our findings suggest that our model provides a better estimate of N0 and p than previously-established methods, likely due to inaccurate assumptions about replenishment. More generally, our findings suggest that approaches commonly used to estimate N0 and p at other synapses are often applied under experimental conditions that yield inaccurate estimates. Conclusions Careful application of appropriate methods can greatly improve estimates of synaptic parameters.

Synaptic Specializations Support Frequency-Independent Purkinje Cell Output from the Cerebellar Cortex

“…We determined whether the observed properties of the PC-DCN synapse could be described by a simple depletion model, which has been used to describe release at a number of depressing synapses (Neher and Sakaba, 2008; Ruiz et al, 2011; Thanawala and Regehr, 2013, 2016). This model consists of a uniform pool of vesicles with three parameters: N, the number of vesicles in the readily releasable pool at rest, P, the release probability, and the time constant of vesicle replenishment τ R (Fig.…”

“…The parameter τ R was determined from the time course of recovery from depression (Fig. 2B, see Thanawala and Regehr, 2013, 2016, methods) and P was unconstrained. Experimental data for 100 Hz trains was fit with an exponential to the initial rate of decay of the IPSC amplitude (Fig.…”

“…The PC-DCN synapse cannot be described by a simple depletion model consisting of a single pool of vesicles, even though such a model describes depression at many other synapses (Dittman et al, 2000; Neher and Sakaba, 2008; Ruiz et al, 2011; Thanawala and Regehr, 2013, 2016). We found that a model with two pools of vesicles could account for transmission at this synapse.…”

“…The single pool model has been introduced previously (Thanawala and Regehr, 2013, 2016). Two pool models were generated by running two sets of single pools that are added together.…”

Fusion Competent Synaptic Vesicles Persist upon Active Zone Disruption and Loss of Vesicle Docking

“…Here, we measure the RRP as vesicles that are released by the application of hypertonic sucrose, and we assume that the same vesicles are accessible to action potentials although differences may exist (Rosenmund and Stevens, 1996; Schikorski and Stevens, 2001; Thanawala and Regehr, 2016; Zucker and Regehr, 2002). We use the term ‘fusion competent’ for vesicles in the RRP and vesicles that are released through spontaneous miniature events (Augustin et al, 1999).…”