Synaptic Dynamics Convey Differential Sensitivity to Input Pattern Changes in Two Muscles Innervated by the Same Motor Neurons

Muscle responses to spontaneous rhythmic input differed substantially between cpv2a and cpv2b

In an initial set of experiments, we kept most of the STNS intact and connected to the PD innervated muscles. We simultaneously recorded from a PD soma and a muscle fiber, either cpv2a (n = 7) or cpv2b (n = 6), during ongoing rhythmic pyloric activity (Fig. 1C,D). In H. americanus, pyloric rhythm frequencies range from 0.4 to 1 Hz (Bucher et al., 2005, 2006). PD neurons are parabolic bursters, producing ∼10–25 spikes per burst, yielding intra-burst mean spike frequencies of 10–35 Hz, and peak instantaneous spike frequencies of 50–100 Hz (Ballo and Bucher, 2009). Soma recordings show waveforms consisting of substantially attenuated spikes on top of only minimally attenuated slow wave depolarizations, as is typical for STG neurons (Mulloney and Selverston, 1972; Golowasch and Marder, 1992).

Stomach muscle fibers are multiterminally innervated along their length, which ensures spatial spread of synaptic potentials (excitatory junction potentials; EJPs) because they usually do not produce all-or-none overshooting action potentials. They generate slow and graded contractions in response to EJPs that summate during bursting input (Morris and Hooper, 1998), and have fairly homogeneous properties within a given muscle (Govind and Lingle, 1987). Both cpv2a and cpv2b showed summated depolarizations of a few millivolts, albeit with very different dynamics. In cpv2a, responses to bursting input comprised easily discernible individual EJPs (Fig. 1D). The responses were fast in the sense that they included a rapid depolarization at the onset. Fibers of stomach muscles innervated by more than one neuron are often polyneural, meaning that individual fibers receive input from more than one motor neuron (Govind and Lingle, 1987; Daur et al., 2012). Individual fibers of cpv2a appeared to receive input from both PD neurons. PD neurons are strongly electrically coupled in the STG, but while this causes highly coherent slow wave oscillations, spike initiation occurs independently in both neurons (unpublished results). Therefore, spikes are not synchronous and arrive at the muscle with some timing offset. This caused a higher number of distinguishable EJPs than could be accounted for by a single PD neuron’s spike pattern, and the varying timing offset led to varying patterns of summation (Fig. 1D, black arrow).

In cpv2b, initial depolarization was much slower than in cpv2a, and occurred with substantial delay from the onset of the PD burst. Peak depolarization was only reached toward the end of burst input, or even after. Individual EJP responses were not easily discernible, and often completely undetectable. Single burst responses could have a relatively smooth appearance in some phases (Fig. 1D, white arrow) and could show more distinct local peaks in others (Fig. 1D, gray arrow), possibly also because of changing offsets between the arrival times of spikes from both PD neurons.

In four experiments, we sequentially recorded from both cpv2a and cpv2b and could therefore directly compare the delay between PD spikes in the STG and the onset of individual muscle fiber responses (Fig. 1D, dashed lines and double-sided arrows). Despite recording sites at similar distance to the proximal muscle insertion sites (Fig. 1B), delays were significantly different (cpv2a: 48.8 ± 2.0 ms SEM; cpv2b: 75.2 ± 6.6 ms SEM; paired t test: t₍₃₎ = −3.482, p = 0.04). As conduction delay between STG and the proximal pdn is between 40 and 50 ms (Bucher et al., 2005), the delay to cpv2a activation is consistent with a direct path of the axon branches to the proximal part of the muscle fibers. However, the ∼25-ms longer delay for cpv2b may indicate a more circuitous path, possibly projecting to a more distal part of the fibers first and then returning to more proximal sites.

Postsynaptic nonlinear muscle fiber membrane properties differed between cpv2a and cpv2b

For the remainder of the study, the muscles were disconnected from centrally generated input by cutting the nerves, and synaptic potentials were evoked by electrically stimulating the pdn. In all cases, stimulus voltage was set to be substantially above threshold to ensure that both PD axons were stimulated synchronously at all frequencies. This differs from the slight offsets in spike timing between the two PD axons during spontaneous pyloric activity (Fig. 1D). However, given the small amplitudes of total responses to even full bursting input, the difference this could make for summation and local voltage values is likely in the submillivolt range.

In some of the experiments, we observed graded action potentials (GAPs; Fig. 2A) when the pdn was stimulated with a burst pattern of parabolic interval structure (see Materials and Methods). GAPs are amplifying potentials of varying amplitudes that are common in some arthropod skeletal muscles (Araque and Buño, 1995; Araque et al., 1998; Weiss et al., 2001). They were straightforward to distinguish from regular EJPs not just by their larger amplitudes, but also by their steep voltage slopes to peak (Fig. 2B). GAPs were seen in only a few experiments in cpv2a (12/202 animals = 6%) but were more common in cpv2b (119/216 animals = 55%). In those experiments, they only occurred episodically and did not show a consistent dependence on presynaptic spike rates, as even during constant repetitive bursting input their occurrence waxed and waned (Fig. 2A). It was therefore straightforward to exclude them from analysis of synaptic responses shown in the remainder of this study. However, they were a clear indication that both muscles exhibited nonlinear voltage responses to synaptic currents.

• Download figure
• Open in new tab
• Download powerpoint

Figure 2.

GAPs in cpv2a and cpv2b. A, Episodes of GAPs in recordings from different experiments. Synaptic responses are from pdn stimulation with a regular parabolic burst pattern at F_burst = 1 Hz. B, Overlay of all burst responses marked by teal arrowheads in A, showing different depolarization slopes.

To gauge the degree of postsynaptic membrane nonlinearities, we performed dual impalements and current injections into single fibers. We did not precisely determine the fiber size distribution, but cursory estimates suggested that diameters exceeded 50 μm in both muscles. Correspondingly, fiber input resistances were very low. Voltage responses to 5-nA current injections yielded apparent input resistance values of 0.53 MΩ (±0.06 SEM, n = 14) in cpv2a, and 0.62 MΩ (±0.10 SEM, n = 15) in cpv2b. These values were not statistically different from each other (t test: t₍₂₇₎ = −0.797, p = 0.216). Because of the large currents needed to change the membrane potential, and the substantial space constants, we could not achieve voltage clamp of sufficient quality to measure voltage-gated currents reliably. However, step currents of increasing amplitudes revealed clear transients in the voltage responses. These nonlinearities were variable across recordings. Figure 3A shows different examples from each muscle. In cpv2a, initial voltage transients in response to larger current amplitudes always decayed monotonically to steady state, albeit at varying rates (Fig. 3A, upper traces). In cpv2b, 7 of 15 experiments showed transients that decayed monotonically, similar to cpv2a (Fig. 3A, middle traces). In the remaining 8 experiments, the initial transients were larger and decayed non-monotonically, either just producing a trough before reaching steady state (Fig. 3A, lower left), or eliciting moderate membrane oscillations (Fig. 3A, lower right).

• Download figure
• Open in new tab
• Download powerpoint

Figure 3.

Step current injections into cpv2a and cpv2b fibers in two-electrode current clamp. A, Example responses to 2-s steps of depolarizing current injections, in increments of 5 nA, from 5 to 45 nA. All responses are shown scaled to the same height of the smallest voltage response (5-nA current injection). Dashed lines indicate integer multiples of that first response. The two examples of cpv2a responses show different rates of monotonic decay from an initial peak in the voltage responses to larger current amplitudes. Two of the four cpv2b examples (lighter blue) show similar monotonic decay at different rates. The other two (darker blue) show amplified initial peak responses followed by non-monotonic trajectories. B, Normalized V-I curves from individual experiments (cpv2a: n = 14; cpv2b: n = 15, 7 with monotonic and 8 with non-monotonic trajectories following the peak). In some experiments, a more limited range of current steps was used. Curves were obtained from the amplitudes of the initial voltage peaks and the mean voltage of the last ∼200 ms of each step (“steady state”). In each experiment, voltage amplitude was scaled to the smallest responses (5-nA current injection) and plotted as a function of current. Therefore, values below the identity line indicate that the voltage response was smaller than the corresponding integer multiple of the smallest response, and values above indicate that the response was larger. C, Pharmacological manipulation of response properties in an example cpv2 recording; 5 nm TEA and 100 nm TTX were added sequentially. In the last step, Ca²⁺ in the saline was reduced to 10% of the normal value, the rest replaced with Mn²⁺.

Figure 3A also shows that voltage responses did not increase linearly with current. In all cpv2a recordings, both peak and steady-state responses to larger currents were smaller than the linear extrapolation of responses to the smallest current injection (Fig. 3A, dashed lines). In cpv2b, peak responses could be either smaller or larger than the linear extrapolation of responses to the smallest current injection, but steady-state responses were smaller in most cases. We plotted the data from all individual experiments as normalized V-I curves for peak and steady-state responses, in which the identity line indicates linear increase from the smallest response. For cpv2a, all V-I curves fall below the identity line, slightly at the initial peak and more substantially at steady state. This suggests that the responses were dominated by outward currents, and that at least parts of the outward currents were activated slowly. In cpv2b, V-I curves differed between experiments with monotonically or non-monotonically decaying transients. The former also fell mostly below the identity line, both at the peak and at steady state, whereas all the latter examples were above the identity line at peak. This suggests that in those experiments, the peaks were amplified by inward currents.

To gain further insight into potential ionic mechanisms, we performed pharmacological manipulations. In the example cpv2b recording shown in Figure 3C, application of a relatively low dose of TEA (5 mm), which blocks many voltage-gated and some Ca²⁺-gated K⁺ channels (Lang and Ritchie, 1990; Golowasch and Marder, 1992), amplified the initial transient response and the following membrane oscillations. Adding TTX did not change the responses, indicating that inward currents likely responsible for the enhanced peaks were not carried by TTX-sensitive voltage-gated Na⁺ channels. Replacing 90% of the Ca²⁺ with Mn²⁺ (in the continued presence of TEA and TTX) eliminated the amplification of the initial peaks and the membrane oscillations. Initial transients were still present and steady state responses were larger than in control saline. We only performed a qualitative assessment of the effects, for two reasons. First, the magnitude of the effects was variable across experiments and appeared to largely depend on how much nonlinearity was expressed in control saline. In recordings that displayed a monotonic decay of the initial transient (all cpv2a recordings and a subset of cpv2b recordings), TEA generally caused a more subtle increase in voltage amplitude and no obvious increases in non-linearities. Second, TEA amplification of peaks in some experiments was associated with fiber contractions resulting in movement artifacts that prevented assessment of the responses to the full range of current amplitudes. This was particularly apparent when TEA led to large repetitive GAP-like oscillations. However, qualitatively, responses were similar across experiments (cpv2a, n = 9; cpv2b, n = 6).

We interpret the findings described in Figure 3 as an indication that both muscles express multiple voltage-gated and possibly Ca²⁺-gated currents. In cpv2a, intrinsic properties predominantly dampen responses, while membrane properties in cpv2b fibers can either dampen or amplify responses. Therefore, all synaptic dynamics explored in the remainder of this study likely resulted both from short-term synaptic plasticity and substantial nonlinear muscle fiber membrane properties.

Magnitude and frequency dependence of short-term facilitation differed between cpv2a and cpv2b

Crustacean stomach NMJs show substantial short-term synaptic plasticity, in most cases facilitation (Govind and Lingle, 1987; Sen et al., 1996; Jorge-Rivera et al., 1998; Stein et al., 2006; Daur et al., 2012; Blitz et al., 2017). To explore the dynamics of EJP responses, we used electrical stimulation of the pdn to activate PD axons in different patterns. Figure 4A shows responses to a single stimulus and a stimulus train. Two examples are shown for cpv2b, one with discernible individual responses, and one without. EJP responses to single stimuli in cpv2a had a median amplitude of 1.16 mV (0.50 CI, n = 15) but were absent or very small in cpv2b (n = 10).

• Download figure
• Open in new tab
• Download powerpoint

Figure 4.

Short-term facilitation in response to stimulation of the pdn. A, Responses to single and train stimulations (16 stimuli at 30 Hz) in a cpv2a fiber and two cpv2b fibers. B, Paired-pulse facilitation in cpv2a. Multiple sweep traces show raw responses. For amplitude measurements, traces were corrected for summation (inset). The plot shows all individual data points across experiments (light red) as the amplitude ratio between response to test and conditioning pulse, as a function of stimulus interval (n = 15). Facilitation recovered as a single exponential decay (R₍₁₂₀₎ = 0.648, p < 0.0001, τ = 244 ms). Mean values ± SEM (dark red) are shown for clarity. C, Responses to conditioning trains (16 stimuli at 30 Hz) and test pulses in cpv2a. Multiple sweeps of raw traces are shown in light red. Responses to test stimuli (dark red) were reconstructed by subtracting a scaled template of the response to the conditioning train. The plot shows all individual data points across experiments (light red) as the amplitude ratio of the responses to the test pulse and the first peak in the train response (arrow in the traces) as a function of stimulus interval (n = 11). Reponses at the shortest interval (10 ms, open circles) on average were smaller than at the second smallest interval (17 ms), as more easily discernible on a log scale (inset). At intervals >10 ms, facilitation recovered as a single exponential decay (R₍₉₉₎ = 0.569, p < 0.0001, τ = 176 ms). Mean values ± SEM (dark red) are shown for clarity. Decay undershot the initial response amplitude. At 1-s interval, the mean (not normalized) amplitudes of responses to the test pulse were significantly smaller than to the conditioning pulse (asterisk, paired t test, t₍₁₀₎ = 2.324, p < 0.05). D, Responses to conditioning trains and test pulses in in cpv2b. Multiple sweeps of raw traces are shown in light blue, reconstructed responses to test stimuli in dark blue. The inset shows a single reconstructed response (blue) compared with the response of a cpv2a fiber (red, scaled to the same amplitude). As cpv2b usually did not exhibit discernible responses to the first conditioning stimulus (arrow), the plot shows all individual data points across experiments (light blue) as raw amplitudes (n = 10). Responses at the shortest intervals (10 and 17 ms, open circles) were smaller than at the next shortest (28 ms), as more easily discernible at on a log scale (inset). At intervals >17 ms, facilitation recovered as a double exponential (R₍₈₀₎ = 0.789, p < 0.0001, τ₁ = 36 ms, τ₂ = 440 ms). Mean values ± SEM (dark blue) are shown for clarity.

Because cpv2b did not reliably respond to single stimuli but showed substantial responses to train input, it was evident that the NMJ undergoes substantial facilitation at this timescale. In contrast, cpv2a responded to single stimuli, but summation during train stimulation prohibited reliable assessment of short-term synaptic plasticity. We therefore performed a standard paired-pulse characterization on cpv2a, consisting of a single conditioning pulse and a test pulse delivered at varying intervals (Fig. 4B). We corrected for summation (Fig. 4B, inset; see Materials and Methods) and determined the paired-pulse ratio as a function of stimulus interval. The NMJ showed moderate facilitation, lasting for ∼1 s, and recovering as a single exponential decay function (τ = 244 ms).

To test whether more repetitive activity yields quantitatively different dynamics in cpv2a than with paired pulses, and to assess the time course of recovery in both cpv2a and cpv2b, we also used conditioning trains followed by a test pulse at varying intervals. We corrected for summation and determined the amplitudes of responses to the test pulses.

In cpv2a (Fig. 4C), we calculated the ratio between the test pulse and initial responses (Fig. 4C, arrow). Facilitation showed a more complex time course compared with the paired-pulse paradigm. Recovery was non-monotonic, as facilitation on average peaked only at the second smallest interval (28 ms). However, the remaining intervals showed recovery with a single exponential, albeit faster than with paired pulses (τ = 176 ms). In addition, recovery undershot the conditioning response (Fig. 4C, asterisk).

In cpv2b (Fig. 4D), we used raw EJP amplitudes in response to the test pulses because initial responses were mostly absent (Fig. 4D, arrow). The time course of facilitation was also non-monotonic. On average, facilitation peaked only at the third smallest interval (47 ms) and then recovered with a double exponential (τ₁ = 36 ms, τ₂ = 440 ms). We interpret the non-monotonic recovery from facilitation in both muscles, the undershoot in cpv2a, and the two recovery time constants present in cpv2b as an indication that more than one process contributed to the dynamics of the responses.

The reconstruction of unitary responses to test pulses in cpv2b also allowed comparison with cpv2a responses (Fig. 4D, inset). We confirmed the larger delay in cpv2b (as shown in Fig. 1D) and determined that the mean halfwidth was about twice as large (cpv2a: 52.6 ± 4.3 ms SEM, n = 14; cpv2b: 109.0 ± 4.2 ms SEM, n = 10; t test: t₍₂₂₎ = −9.041, p < 0.001). Therefore, more substantial summation likely explains the smoother appearance of cpv2b responses to bursts or trains.

While the data presented in Figure 4 assessed facilitation as the dependence of unitary responses on prior activity, it did not address the dependence of compound responses on the rate of repetitive activity. Therefore, we also tested the responses to stimulus trains at varying frequencies (Fig. 5A). We stimulated the pdn with 10 pulses every 30 s, varying the stimulation frequency within trains (F_stim) between 1 and 50.2 Hz. Figure 5A shows example traces from cpv2a and cpv2b recordings for some of the values of F_stim. As a parameter that is independent of summation, we measured the voltage integral of each response to the whole train. Figure 5B shows that responses of the two muscles differed substantially in their frequency dependence, as cpv2a responses increased logarithmically with frequency, whereas cpv2b responses increased sigmoidally.

• Download figure
• Open in new tab
• Download powerpoint

Figure 5.

Facilitation across different stimulus frequencies. A, Example traces of responses to trains of 10 stimuli delivered at different frequencies (F_stim, 4 of 8 frequencies shown). B, Responses quantified as the total voltage integral of each train response, showing all individual data points across experiments (lighter color) over the log of F_stim (cpv2a: n = 13; cpv2b: n = 10). Mean values ± SEM (darker colors) are shown for clarity. In both muscles, responses increased monotonically with F_stim. In cpv2a, response increase with F_stim was fit with a logarithmic function (R₍₈₈₎ = 0.575, p < 0.0001). In cpv2b, response increase with F_stim was fit with a sigmoidal function (R₍₇₂₎ = 0.892, p < 0.0001). C, Plots of the binned and normalized upper voltage envelopes from the same data shown in B. For each train stimulus, voltage maxima were determined in bins set to the size of the stimulus interval, extending three bins before the first stimulus and 12 bins after the last. All responses within each experiment were normalized to the maximum depolarization at 50.2 Hz.

We also used these data to show that the time courses of depolarization in response to repetitive input were consistently different between cpv2a and cpv2b. Because individual peaks could not reliably be detected in cpv2b at all frequencies, and in cpv2a at higher frequencies, we measured the upper voltage envelopes by finding the voltage maxima in time bins that matched the stimulus interval at each frequency. Figure 5C shows the mean normalized upper voltage envelopes for all stimulus frequencies, plotted over the bin numbers. In cpv2a, envelopes showed an immediate and steep rise at stimulus onset and started to saturate before the end of the stimulus. In cpv2b, onset was delayed and gradual, and envelopes did not display any sign of saturation before the end of the stimulus and mostly peaked thereafter.

Dynamics across bursts differed between cpv2a and cpv2b

Slower forms of synaptic plasticity like augmentation, post-tetanic potentiation, and long-lasting depression are only apparent with longer lasting and highly repetitive synaptic activation and can depend on a range of cellular phenomena (Regehr and Stevens, 2001; Zucker and Regehr, 2002). Pyloric neuron activity is highly repetitive, and the time constants of recovery from facilitation shown in Figure 4 suggested that dynamics could extend over multiple burst inputs, as has been shown for other stomach muscles (Stein et al., 2006; Blitz et al., 2017). We did not attempt to distinguish between cellular mechanisms that may be involved in dynamics apparent at different timescales, either presynaptically or postsynaptically. For simplicity, we therefore refer to any enhancement of synaptic responses as facilitation, and any decline as depression. We stimulated the pdn with a realistic parabolic burst pattern and recorded the responses to episodes of 20 consecutive bursts (Fig. 6A). We used the burst pattern described in Materials and Methods and varied the burst frequency (F_burst) across episodes from 0.2 to 2 Hz. We did so while keeping the number of pulses per burst and the DC constant and scaling the inter-pulse intervals proportionally to the burst period (Fig. 6A, inset). In the example shown, response amplitudes increased with F_burst to some point but decreased again at higher values. This indicates bandpass filtering properties with lower best frequencies in cpv2b than in cpv2a. Amplitudes within each episode also changed. Therefore, differences in responses across different values of F_burst were clearly not simply caused by differences in summation. Summation across bursts even at higher values of F_burst was generally small, as seen in the only slight baseline depolarization during those episodes.

• Download figure
• Open in new tab
• Download powerpoint

Figure 6.

Dynamics across repeated bursting input. A, Example responses to 20 consecutive bursts at different burst frequencies (F_burst). The inset shows that single bursts consisted of 19 stimuli delivered in a parabolic interval structure (see Materials and Methods). Burst DC was kept constant at 0.35 across F_burst values. Maximum instantaneous frequency (F_inst) scaled linearly as 63.4 * F_burst. B, Expanded view of the traces at F_burst = 0.63 Hz. Dashed lines indicate the amplitude of the first burst response. C, Mean voltage integrals (normalized to the first burst response) as a function of burst index, for all values of F_burst (cpv2a: n = 17; cpv2b: n = 15). D, Same normalized voltage integrals as in C, as means of means across all burst frequencies, not individual data. The initial large changes in both muscles diminished to steady state as single exponential functions (cpv2a: R₍₁₉₎ = 0.99, p < 0.0001, rise constant = 3.7 bursts; cpv2b: cpv2a: R₍₁₉₎ = 0.99, p < 0.0001, decay constant = 6.7 bursts). E, Magnitude of initial change as a function of F_burst. Values are the average responses to the second and third bursts, normalized to the response to the first burst. Plots show all individual data points across experiments (small circles) over the log of F_stim. Mean values ± SEM (large circles) are shown for clarity. Linear regression showed change with frequency at both NMJs (cpv2a: R₍₁₅₃₎ = 0.43, p < 0.0001; cpv2b: R₍₁₃₅₎ = 0.44, p < 0.0001).

First, we assessed the dynamics across bursts within each episode. The expanded traces of the example recording at F_burst = 0.63 Hz (Fig. 6B) show that responses in cpv2a expressed initial depression across bursts, followed by partial recovery. In contrast, cpv2b expressed initial facilitation, followed by partial recovery. We measured the voltage integral of each burst response and normalized to the first response. Figure 6C shows the mean trajectory of normalized integrals over successive bursts for all values of F_burst. Recovery was relatively consistent across values of F_burst, apparently depending more on number of bursts than on time or frequency. We therefore pooled the data from all values of F_burst and fit the means with single exponentials (Fig. 6D). Responses in cpv2b took more bursts to recover (decay constant = 6.7 bursts) than responses in cpv2a (rise constant = 3.7 bursts). Although recovery appeared to be mostly dependent on burst number, the initial magnitude of depression or facilitation across burst responses was dependent on F_burst. Figure 6E shows the ratios of the average response to the second and third bursts over the first burst. Both depression in cpv2a and facilitation in cpv2b increased significantly with F_burst (linear regression; cpv2a: R² = 0.18, p < 0.0001; cpv2b: R² = 0.19, p < 0.0001).

Next, we assessed the steady-state responses across frequencies from the average responses of the last five bursts (Fig. 7). As depicted in Figure 6A, inset, we had kept DC and number of spikes constant while changing F_burst. Consequently, burst duration (Dur) changed inversely to F_burst, while the mean spike frequency (F_spk) changed proportionally. Any dynamics could therefore have resulted from the changes in F_burst, F_spk, or Dur. This paradigm was chosen because it reflects the PD neuron behavior across varying cycle frequencies (Bucher et al., 2005), and we refer to it from here on as paradigm 1. To distinguish between sensitivity of responses to F_burst versus F_spk or Dur, we applied two additional stimulus paradigms, which are shown alongside paradigm 1 in Figure 7A. Paradigm 2 was designed to keep F_spk and Dur constant while changing F_burst. We fixed Dur at 0.32 s and F_spk at 55.6 Hz, corresponding to the value at F_burst = 1.1 Hz in paradigm 1. Paradigm 3 was designed to keep F_burst constant while changing F_spk and Dur. We fixed F_burst at 0.2 Hz but changed F_spk and Dur over the same range as in paradigm 1. We restricted the analysis to the F_burst range of 0.2−1.5 Hz, because in some experiments, F_burst = 2.0 Hz produced summation across bursts.

• Download figure
• Open in new tab
• Download powerpoint

Figure 7.

Sensitivity of responses to different burst parameters. A, Three different stimulus paradigms used to distinguish between sensitivity to burst frequency (F_burst) versus burst duration (Dur) and mean spike frequency within bursts (F_spk). The number of spikes per burst was constant (19) in all cases. In paradigm 1, DC was constant while F_burst was varied between 0.2 and 1.5 Hz. Consequently, F_spk changed between 10.1 and 75.4 Hz, and Dur changed between 1.79 and 0.24 s. In paradigm 2, F_spk and Dur were constant at 55.6 Hz and 0.32 s, respectively, while F_burst was varied as in paradigm 1. In paradigm 3, F_burst was constant at 0.2 Hz, while F_spk and Dur changed as in paradigm 1. B, C, Steady-stated responses to the different stimulus paradigms (cpv2a: n = 13; cpv2b: n = 11). In each experiment, values were divided by the average response over all frequencies, and the results plotted as percent deviation from the overall mean. Asterisks indicate results from Friedman ANOVAs on ranks for each paradigm. Integrals changed significantly with F_burst and F_spk (cpv2a: χ²₍₇₎ = 62.08, p < 0.001; cpv2b: χ²₍₇₎ = 60.87, p < 0.001), F_spk (cpv2a: χ²₍₇₎ = 72.43, p < 0.001; cpv2b: χ²₍₇₎ = 27.79, p < 0.001) and Dur (cpv2a: χ²₍₇₎ = 54.95, p < 0.001; cpv2b: χ²₍₇₎ = 55.24, p < 0.001).

Figure 7B shows the change of mean voltage integrals in cpv2a under each stimulus paradigm. Under paradigm 1, voltage integrals increased with F_burst and F_spk over most of the range but decreased again at the highest frequency. This bandpass filtering property was absent under paradigm 2, but otherwise the magnitude of changes was similar. Under paradigm 3, the sensitivity to F_spk and Dur appeared less pronounced, but there was a decrease of integrals at the highest frequency similar to the responses to paradigm 1. We therefore conclude that the change in responses seen when burst parameters were changed in a realistic manner (paradigm 1) was because of changes in F_burst and either F_spk or Dur.

Figure 7C shows the change of mean voltage integrals in cpv2b under each stimulus paradigm. Under paradigm 1, voltage integrals showed pronounced bandpass filtering, with the largest responses at F_burst = 0.6 Hz and F_spk = 31.8 Hz. The magnitude of changes was substantially smaller under paradigm 2, and responses were smallest in the midrange of F_burst values. Under paradigm 3, changes were not as pronounced but qualitatively similar to the ones seen under paradigm 1, showing the same bandpass filtering. We therefore conclude that the change in responses seen when burst parameters were changed in a realistic manner (paradigm 1) was dominated by the changes in F_spk or Dur, and relatively insensitive to changes in F_burst.

The three paradigms used to change burst parameters did not allow us to distinguish between effects of F_spk and Dur. We therefore tested those effects in a different set of experiments. For simplicity, we used bursts of 19 pulses with constant (regularized) instantaneous frequency (F_inst) at F_burst = 1 Hz and Dur = 0.35 s. We stimulated for 20 s to reach steady state and then changed the pattern by reducing the number of pulses to 17. This drop in number of pulses was achieved in two ways, either by keeping F_spk constant and therefore decreasing Dur from 0.35 s to 0.31 s, or by keeping Dur constant and therefore decreasing F_spk from 51 to 46 Hz (Fig. 8A). We measured the mean voltage integral of the responses to the last five bursts before the change and the first five after and compared the results across conditions (Fig. 8B). In cpv2a, the decrease in number of pulses was accompanied by a significant decrease in voltage integral in both cases, and the effects of Dur and F_spk were statistically indistinguishable. In both cases, the decrease was close to the calculated linear decrease with pulse number (17/19 of the original response; Fig. 8B, teal arrowheads). In cpv2b, voltage integrals significantly decreased when Dur was decreased, but not when F_spk was decreased. The decrease in integrals with Dur was larger than the calculated linear decrease with pulse number (teal arrowheads). We conclude that responses in cpv2a depended on number of pulses in a burst, while responses in cpv2b only depended on Dur.

• Download figure
• Open in new tab
• Download powerpoint

Figure 8.

The effects of changing the number of pulses per burst. A, Regularized burst patterns were changed from 19 pulses/burst (middle red or middle blue) to 17 pulses/burst (teal), first by decreasing Dur to keep F_spk constant (light red or light blue), and then by decreasing F_spk to keep Dur constant (dark red or dark blue). B, Mean voltage integrals of the five responses before and five responses after the pattern changes. Teal arrowheads indicate the calculated mean linear decrease to 17/19 of the responses to 19 pulses/burst. In cpv2a (n = 16), responses differed between 19 and 17 pulses (one-way RM-ANOVA, F_(3,63) = 16.941, p < 0.001). Responses decreased both when Dur and when F_spk changed, and the magnitude of decrease did not differ (Holm–Sidak post hoc comparisons). In cpv2b (n = 16), responses differed across stimulus regimes (one-way RM-ANOVA, F_(3,63) = 19.504, p < 0.001), but only decreased significantly when Dur was decreased (Holm–Sidak post hoc comparisons).

Sensitivity to spike interval patterns within bursts differed between cpv2a and cpv2b

The results presented in Figures 7, 8 addressed the sensitivity of both NMJs to different burst parameters, but not to the precise temporal pattern within each burst. Pyloric neurons produce cell type-specific characteristic intraburst spike patterns that are malleable to neuromodulation (Szücs et al., 2003, 2005; Ballo and Bucher, 2009; Ballo et al., 2012; Zhang et al., 2017). To which degree muscle responses may be sensitive to those patterns, and changes thereof, is not known. During ongoing pyloric activity, the PD neuron shows a parabolic burst pattern (Szücs et al., 2003; Ballo and Bucher, 2009) We therefore tested whether the parabolic trajectory of F_inst within each burst was important in determining synaptic responses. We stimulated the pdn with a bursting pattern (19 pulses, Dur = 0.35 s, F_burst = 1 Hz), alternating 1 min episodes of a regularized (constant F_inst) intraburst pattern with the parabolic pattern. Figure 9A shows three examples for each muscle, indicating that the responses to changing the pattern were inconsistent across experiments. In some cases, responses increased when the pattern switched from regularized to parabolic (upper traces), in some cases there was no clear effect (middle traces), and in other cases responses decreased (lower traces). Figure 9B shows that in cpv2a, although there was no significant change in mean responses across experiments, 3 of 11 experiments showed an increase within the experiment, 4 showed a decrease, and another 4 showed no change. In cpv2b, mean responses across experiments also did not show a significant change, but 7 of 11 experiments showed an increase within the experiment, 3 showed a decrease, and one showed no change. We also wanted to test whether cycle-to-cycle variability was dependent on the pattern. To this end, we determined the coefficient of variation (CV) across cycles for each pattern in each individual experiment. Figure 9C shows that in cpv2a, mean cycle-to-cycle variability did not change, but in cpv2b, variability was smaller with parabolic stimulation.

• Download figure
• Open in new tab
• Download powerpoint

Figure 9.

The effect of regularized versus parabolic intraburst stimulus patterns. A, Examples of cpv2a and cpv2b recordings showing increasing (upper traces), stable (middle traces), and decreasing (lower traces) responses during a switch from regularized (constant instantaneous frequency, F_inst) to parabolic patterns. B, Mean integrals across experiments (cpv2a: n = 11; cpv2b: n = 11) did not significantly change between regularized and parabolic stimulation in either muscle (cpv2a: paired t test, t₍₁₀₎ = 0.90, p = 0.900; cpv2b: Wilcoxon signed-rank test, Z₍₁₁₎ = 1.245, p = 0.240). However, t tests or Mann–Whitney rank-sum tests of mean integrals from 50 to 60 cycles for each stimulus pattern in individual experiments (details not reported here) showed either increases (dark color lines), no change (middle color lines), or decreases (light color lines). C, Cycle-to-cycle variability (CV) of response integrals. Lines show changes in individual experiments, and open circles (±SEM) mean CVs across experiments. Means were not significantly different in cpv2a (Wilcoxon signed-rank test, Z₍₁₁₎= 1.600, p = 0.123) but were significantly smaller for parabolic stimulation in cpv2b (paired t test, t₍₁₀₎ = 3.273, p < 0.01).

In the PD neurons, activity-dependent changes in axonal excitability and conduction velocity affect the interval structure within bursts during propagation from the STG to the muscle (Ballo and Bucher, 2009). These changes are dependent on axonal hyperpolarization-activated inward current (I_h), which is increased in the presence of dopamine (DA; Ballo et al., 2010). Blocking I_h exacerbates pattern changes because conduction velocity becomes more variable within each burst, while DA-mediated increase in I_h reduces pattern changes because conduction velocity becomes more consistent (Ballo et al., 2012; Zhang et al., 2017). We wanted to know whether such changes in interval structure affected muscle responses, particularly because they are more subtle than the difference between parabolic and regularized patterns. Figure 10A shows stimulus patterns that mimicked the burst patterns as they would arrive at the muscle in control saline (“control”), when I_h is blocked (“-I_h”), and when I_h is increased by DA (“DA”; Ballo et al., 2012). The most prominent differences between the patterns are in the F_inst value at the beginning of the bursts, corresponding to the first interval (Fig. 10A, teal). In the -I_h pattern, the first interval is decreased, while in the DA pattern it is increased. First, we alternated the three stimulation patterns cycle by cycle (Fig. 10B). Both muscles were sensitive to the pattern changes, with generally smallest responses to the -I_h patterns, and largest responses to the DA pattern. However, in cpv2a only the responses to the -I_h pattern were significantly different from the others, and the difference was in the range of <5%. In contrast, responses to all patterns differed significantly from each other in cpv2b, and the differences could exceed 20%. To ensure that these differences were not just caused by transient changes because of the switching of patterns, we used two additional stimulus regimes. First, we still alternated the patterns cycle by cycle, but changed the sequence, which yielded similar results (data not shown). Second, we switched patterns only every five bursts and quantified responses from the average voltage integrals of the last three in each episode (Fig. 10C). Again, both muscles were sensitive to the differences in patterns, showing the smallest responses to the -I_h pattern, and the largest responses to the DA pattern. In this case, the differences were significant in all cases, and similar in magnitude to the cycle-by-cycle results. We conclude that the changes in F_inst within each burst that arise from activity-dependent changes in axonal spike propagation and are sensitive to axonal DA modulation are substantial enough to affect the magnitude of postsynaptic responses, particularly in cpv2b.

• Download figure
• Open in new tab
• Download powerpoint

Figure 10.

The effect of intraburst stimulus patterns mimicking pattern changes because of spike propagation. A, Stimulus patterns corresponding to how the parabolic pattern used in the prior experiments changes during propagation from the STG to the muscle in control saline (control), when the hyperpolarization-activated inward current I_h is blocked (-I_h), and when I_h is increased by DA. The most substantial difference between pattern at the beginning of the bursts is highlighted in teal. B, Responses to cycle-by-cycle change of intraburst patterns, color coded as indicated in A. Plots show mean normalized voltage integrals (cpv2a: n = 17; cpv2b: n = 19). In each experiment, at least 20 responses to each stimulus pattern were averaged. Each average value was then divided by the average across all stimulus patterns, and the results plotted as percent deviation from the overall mean. In cpv2a, the overall effect of stimulation pattern was significant (Friedman RM-ANOVA on ranks, χ²₍₂₎ = 25.53, p < 0.001), but control and DA were not significantly different (Tukey’s test). In cpv2b, the overall effect of stimulation pattern was also significant (one-way RM-ANOVA, F_(2,56) = 31.198, p < 0.001), and responses differed between all patterns (Holm–Sidak post hoc comparisons). C, Responses to episodes of five consecutive bursts for each pattern. Plots show normalized values from the averages of the last three of the five cycles in at least 10 episodes. Normalization was done and plots generated as described in B (cpv2a: n = 18; cpv2b: n = 22). In cpv2a, the overall effect of stimulation pattern was significant (Friedman RM-ANOVA on ranks, χ²₍₂₎ = 32.11, p < 0.001), and responses differed between all patterns (Tukey’s test). In cpv2b, the overall effect of stimulation pattern was also significant (one-way RM-ANOVA, F_(2,65) = 28.022, p < 0.001), and responses differed between all patterns (Holm–Sidak post hoc comparisons).