Activity-dependent changes in temporal components of neurotransmission at the juvenile mouse calyx of Held synapse

Abstract

The temporal fidelity of synaptic transmission is constrained by the reproducibility of time delays such as axonal conduction delay and synaptic delay, but very little is known about the modulation of these distinct components. In particular, synaptic delay is not generally considered to be modifiable under physiological conditions. Using simultaneous paired patch-clamp recordings from pre- and postsynaptic elements of the calyx of Held synapse, in juvenile mouse auditory brainstem slices, we show here that synaptic activity (20-200 Hz) leads to activity-dependent increases in synaptic delay and its variance as well as desynchronization of evoked responses. Such changes were most robust at 200 Hz in 2 mM extracellular Ca(2+) ([Ca(2+)](o)), and could be attenuated by lowering [Ca(2+)](o) to 1 mM, increasing temperature to 35 degrees C, or application of the GABA(B)R agonist baclofen, which inhibits presynaptic Ca(2+) currents (I(Ca)). Conduction delay also exhibited slight activity-dependent prolongation, but this prolongation was only sensitive to temperature, and not to [Ca(2+)](o) or baclofen. Direct voltage-clamp recordings of I(Ca) evoked by repeated action potential train template (200 Hz) revealed little jitter in the timing and kinetics of I(Ca) under various conditions, suggesting that increases in synaptic delay and its variance occur downstream of Ca(2+) entry. Loading the Ca(2+) chelator EGTA-AM into terminals reduced the progression rate, the extent of activity-dependent increases in various delay components, and their variance, implying that residual Ca(2+) accumulation in the presynaptic nerve terminal induces these changes. Finally, by applying a test pulse at different intervals following a 200 Hz train (150 ms), we demonstrated that prolongation in the various delay components reverses in parallel with recovery in synaptic strength. These observations suggest that a depletion of the readily releasable pool of SVs during high-frequency activity may downregulate not only synaptic strength but also decrease the temporal fidelity of neurotransmission at this and other central synapses.

Figure 5. Temperature dependence of neurotransmission delay components

A and B, first (black lines) and last (grey lines) pairs of presynaptic current deflections and postsynaptic EPSCs from 30 repeated stimulation trains at 200 (A) and 400 Hz (B) are aligned and superimposed to illustrate the frequency dependence of changes in presynaptic and postsynaptic responses at 35°C. Note that time scales are different in A and B. C and D, plots for each measurable delay component against the number of stimuli in a train under the two experimental conditions described in A and B. Lines in these plots represent linear regression to scattered data points of 30 sweeps.

Figure 1. Experimental arrangement and analytical approaches for quantifying temporal delays of synaptic transmission

A, simultaneous recording from a presynaptic calyx, in cell-attached configuration, and a postsynaptic neuron in whole-cell configuration (top). Example current traces (middle) are also shown, in which the deflections are marked with dotted lines to define conduction delay (1, CD), synaptic delay (2, SD), response rise delay (3, RRD), and transmission delay (4, TD). B, the first (black line) and last (grey line) EPSCs recorded during a stimulation train (200 Hz, 150 ms) are superimposed to show activity-dependent changes in size, kinetics and timing of synaptic responses. Two analytical approaches, namely the ‘threshold method’ (top) and ‘intersection method’ (bottom), are depicted for determination of EPSC onset (arrows). Dotted lines showing the 10% of maximum line are used to determine the onset of EPSCs in the former, whereas dotted lines, fit to the baseline and the 10–90% rise portion of the EPSC, define the intersection point as the onset of EPSCs in the latter. C, graphic presentation of the ‘maximal curvature method’ for determination of synaptic delay. The rise phase of an EPSC (dotted line) is first fit with an equation of the form of the Boltzmann charge–voltage equation, and the fitted curve is shown (black line). The 4th derivative of the fitted curve is then set equal to zero and solved for its three solutions (right), of which t₁ or t₃ define the maximal curvature point as the onset of an EPSC.

Figure 4. Activity and Ca²⁺ dependence of neurotransmission delay components

A and B, first (black lines) and last (grey lines) pairs of presynaptic current deflections and postsynaptic EPSCs from 30 repeated stimulation trains (200 Hz, 150 ms) are aligned and superimposed to illustrate activity-dependent changes in presynaptic and postsynaptic responses in 2 mm[Ca²⁺]_o (A) and 1 mm[Ca²⁺]_o (B). C and D, plots for each measurable delay component against the number of stimuli in a train under the two experimental conditions described in A and B. Lines in these plots represent linear regression to scattered data points of 30 sweeps.

Figure 7. Intraterminal accumulation of residual Ca²⁺ underlies activity-dependent prolongation in neurotransmission delay components

A, examples of first (black lines) and last (grey lines) pairs of presynaptic current deflections and postsynaptic EPSCs from 30 repeated stimulation trains (200 Hz, 150 ms) in 2 mm[Ca²⁺]_o w/EGTA-AM pretreatment. B, pooled data showing the amplitude of the first EPSCs (top) and a plot of normalized EPSC amplitude against event number in 2 mm[Ca²⁺]_o with and without EGTA-AM pretreatment (bottom). C, plots for delay components against the number of stimuli in a train under the experimental conditions described in A. Continuous black lines represent linear regression to scattered data points shown. Dashed lines represent linear regression to scattered data shown in Fig. 4C.

Figure 9. Recovery of delay components from activity-dependent prolongation

A, stimulation protocol (top) for determining the recovery kinetics of delay components; 200 Hz, 150 ms trains were followed by a single test pulse at varying Δt from 10 to 1500 ms. Example traces showing averaged presynaptic current deflections (middle) and postsynaptic EPSCs (bottom), in response to the stimulation protocol in A, for Δt = 10, 500, 1000 and 1500 ms. B, magnification of the events shown in A are aligned by presynaptic stimulation artefact for the Δt in A (as marked). C, pooled data plotting EPSC area, as a percentage of the initial EPSC area, against Δt. Points were fitted with a biphasic exponential (continuous line). D, pooled data plotting delays, as a percentage of the initial delay, against Δt. Points were fitted with a biphasic exponential (solid lines) in all cases except for response delay, which was fitted with a single exponential. E, correlation plots of EPSC recovery versus recovery of synaptic delay (left) and transmission delay (right) as a percentage of the initial events. Continuous black lines represent linear regression to scattered data points shown.

Figure 2. Quantitative comparison of different analytical methods for determining dynamic changes in the onset of EPSCs evoked by high-frequency stimuli

A, example of paired presynaptic cell-attached (top) and postsynaptic whole-cell voltage-clamp recordings (bottom). Thirty current traces, in response to high-frequency afferent stimulation trains (200 Hz, 150 ms), are superimposed to illustrate activity-dependent changes in synaptic responses. Stimulation artefacts preceding presynaptic and postsynaptic currents have been removed for clarity. B, magnified view of first (left) and final (right) stimuli from the traces shown in A. Note the increase in both synaptic delay and variance in events towards the end of trains. C, an example contrasting two EPSCs with fast (black line) and slow rise phases (grey line), for which the linear intersection method (left) and threshold method (right) both bias the temporal onset of EPSCs. D, summary data showing the bias inherent in each of the methods shown in C as compared with the maximal curvature method for the determination of the EPSC onset.

Figure 10. Quantitative assessment of three analytical methods for determination of the onset of EPSCs

A, example EPSC (grey line, left trace), with fitted the Boltzmann equation (black line), and dotted lines highlighting the region used for the curve fitting process. The fitted function (grey line) and the 4th derivative (black line), aligned in time, are shown (right trace) with solutions to the 4th derivative given as vertical dotted lines (t₁, t₂ and t₃). B, same trace as in A analysed with the linear intersection method. The EPSC onset is determined by the intersection point of the two black lines, with the upper and lower error limits shown by dotted lines (left trace). The boxed region is magnified (right traces) to show the shift in the calculated EPSC onset time, with and without the inclusion of error in the horizontal baseline. The nomenclature refers to the appendix. C, same trace as in A analysed with the threshold method. The black line in the left trace indicates 10% of the EPSC peak. Magnification of the boxed region is shown (right traces) to illustrate the error inherent due to digitization. D, cumulative histograms of the error distributions in the determination of the EPSC onset from the first (grey line) and last (black line) EPSCs in response to train stimuli (200 Hz, 150 ms) using the linear intersection (left) and maximal curvature methods (right).

Figure 3. Frequency-dependence of increases in neurotransmission delay and variance during repetitive stimulation

A, first (black lines) and 30th (grey lines) pairs of presynaptic current deflections and postsynaptic EPSCs, from 30 repeated stimulation trains at 20 (left), 50 (middle) and 100 Hz (right), are aligned and superimposed to illustrate the frequency dependence of delay in pre- and postsynaptic responses (P15, 2 mm[Ca²⁺]_o). B, average change in synaptic (top), response rise (middle) and transmission (bottom) delays, as a function of stimulus number, for 20 (green diamonds), 50 (blue triangles), 100 (red squares) and 200 Hz (black circles) stimulation frequencies shown in A. Data shown for 200 Hz are taken from the example shown in Fig. 2A. Dashed lines are least-squares regressions through data shown. C, summary data showing the progression of delay (μs event⁻¹, top) or variance (μs² event⁻¹, bottom) for each delay component at each frequency shown in B. D, summary data showing the percentage change in delay and variance, compared between the first and final three events in a train, for each delay component at each frequency shown in B. *P < 0.05 (Students t test) vs 200 Hz group (black bars).

Figure 8. Comparison of activity-dependent changes in temporal delays and their variance

A and B, pooled data showing the progression rate of delay (A) for all temporal components, and their variance (B) for various experimental conditions. C and D, pooled data showing the relative extent of the prolongation in various delay components (C) and their variance (D), as in A and B. *P < 0.05 (Student's t test) against the 2 mm[Ca²⁺]_o data set. Comparisons between other data sets are shown in Supplemental Table 1.

Figure 6. Temporal plasticity of synaptic transmission is mediated by mechanisms downstream of AP-evoked Ca²⁺ influx

A, voltage-clamp template of an AP train (200 Hz, 200 ms) used for evoking Ca²⁺ currents from calyces. Note that these real APs were previously recorded in whole-cell current-clamp configuration from a nerve terminal (P15), in response to afferent stimulation, and digitally converted into a voltage-clamp command file (see Methods). B, Ca²⁺ currents evoked by the AP train template in 2 mm[Ca²⁺]_o (left), 1 mm[Ca²⁺]_o (middle) and 2 mm[Ca²⁺]_o w/50 μm baclofen (right) solutions are shown. In each case, 10 repeated sweeps of Ca²⁺ currents are overlaid to demonstrate their temporal fidelity. Insets (B, bottom) contrast the first and last two Ca²⁺ currents magnified from those shown in the top traces.