Short-term depression, temporal summation, and onset inhibition shape interval tuning in midbrain neurons

Abstract

A variety of synaptic mechanisms can contribute to single-neuron selectivity for temporal intervals in sensory stimuli. However, it remains unknown how these mechanisms interact to establish single-neuron sensitivity to temporal patterns of sensory stimulation in vivo. Here we address this question in a circuit that allows us to control the precise temporal patterns of synaptic input to interval-tuned neurons in behaviorally relevant ways. We obtained in vivo intracellular recordings under multiple levels of current clamp from midbrain neurons in the mormyrid weakly electric fish Brienomyrus brachyistius during stimulation with electrosensory pulse trains. To reveal the excitatory and inhibitory inputs onto interval-tuned neurons, we then estimated the synaptic conductances underlying responses. We found short-term depression in excitatory and inhibitory pathways onto all interval-tuned neurons. Short-interval selectivity was associated with excitation that depressed less than inhibition at short intervals, as well as temporally summating excitation. Long-interval selectivity was associated with long-lasting onset inhibition. We investigated tuning after separately nullifying the contributions of temporal summation and depression, and found the greatest diversity of interval selectivity among neurons when both mechanisms were at play. Furthermore, eliminating the effects of depression decreased sensitivity to directional changes in interval. These findings demonstrate that variation in depression and summation of excitation and inhibition helps to establish tuning to behaviorally relevant intervals in communication signals, and that depression contributes to neural coding of interval sequences. This work reveals for the first time how the interplay between short-term plasticity and temporal summation mediates the decoding of temporal sequences in awake, behaving animals.

Keywords: electrosensory system; short-term synaptic plasticity; temporal coding; weakly electric fish.

Figure 1.

ELp neurons vary in their tuning to stimulus interval. A–D, Recorded V_m values in response to a scan of decreasing then increasing IPIs (left), and tuning curve (right) for a high-pass (A), low-pass (B), bandpass (C), and bandstop (D) neuron. Tick marks below the recording traces indicate stimulus times. Tuning curves were generated by averaging PSP amplitudes in response to the same IPI during a decreasing–increasing train and an increasing–decreasing train, then normalizing by the maximum average response. These curves were then fit with both a Gaussian and a sigmoidal function. Neurons were classified as high-pass or low-pass if the r_sigmoid²/r_Gaussian² ratio was ≥0.85, and as bandpass or bandstop if this ratio was <0.85 (see Materials and Methods). The sigmoidal (high-pass and low-pass) or Gaussian (bandpass and bandstop) fit is shown for each neuron.

Figure 2.

Excitatory and inhibitory conductances decrease at short intervals in response to IPI scans. A, The V_m values recorded from a high-pass neuron during a decreasing–increasing IPI scan under three levels of current clamp. B, C, The excitatory (gE; B) and inhibitory (gI; C) synaptic conductances estimated from the potentials recorded in A. Notice that the peak amplitudes decrease at short IPIs. D, E, Average peak excitatory (D) and inhibitory conductances (E) normalized to single-pulse responses for high-pass and low-pass neurons. Error bars represent SEM. *p < 0.000001, repeated-measures ANOVA, interaction between tuning and IPI.

Figure 3.

Interval-tuned neurons receive excitatory and inhibitory inputs that decrease to varying degrees during 10 ms IPIs. A, The V_m values recorded from a low-pass ELp neuron in response to a 10 ms IPI train under multiple levels of current clamp. B, Estimated excitatory (gE) and inhibitory (gI) conductances underlying the responses in A. C, Estimated synaptic conductances of the same neuron in A and B in response to a 100 ms IPI train. D–F, Plots of normalized PSP (D), inhibitory conductance (E), and excitatory conductance (F) amplitudes evoked by a 10 ms IPI train versus stimulus time. Plots for each individual neuron (n = 42 neurons) are shown in gray, and the averages ± SEM are shown in black (PSPs), magenta (gI), and green (gE). G–I, Same as in D–F for the responses of 34 ELp neurons to 100 ms IPI trains.

Figure 4.

Excitation depresses less than inhibition at short intervals in high-pass neurons. A, The V_m values recorded from a representative high-pass neuron in response to a 10 ms IPI train. B, The excitatory (gE) and inhibitory (gI) synaptic conductances underlying the responses shown in A. C, Normalized synaptic conductances during a 10 ms IPI train in high-pass neurons (n = 13 neurons). *p < 0.0001, repeated-measures ANOVA, interaction between excitation/inhibition and pulse time. D, Normalized synaptic conductances during the 10 ms IPI train after removing the effects of temporal summation (see Materials and Methods) for high-pass neurons. *p < 0.01, repeated-measures ANOVA, interaction between excitation/inhibition and pulse time. E, F, Bar graphs of average time constants (E) and amplitudes (F) of exponential fits to normalized observed and summation-removed (depression only) conductances during 10 ms IPI trains in high-pass neurons. Error bars represent SEM.

Figure 5.

Excitation and inhibition depress similarly at short intervals in low-pass neurons. A, The V_m values recorded from a representative low-pass neuron in response to a 10 ms IPI train. B, The excitatory (gE) and inhibitory (gI) synaptic conductances underlying the responses shown in A. C, Normalized synaptic conductances during a 10 ms IPI train in low-pass neurons (n = 22 neurons). D, Normalized synaptic conductances during the 10 ms IPI train after removing the effects of temporal summation (see Materials and Methods) in low-pass neurons. E, F, Bar graphs of average time constants (E) and amplitudes (F) of exponential fits to normalized observed and summation-removed (depression only) conductances during 10 ms IPI trains in low-pass neurons. Error bars represent SEM.

Figure 6.

Temporal summation of excitation contributes to high-pass responses, whereas long onset inhibition contributes to low-pass responses. A, V_m recordings in response to a 10 ms IPI train (top) and a single stimulus pulse (middle), and excitatory (gE) and inhibitory (gI) synaptic conductances (bottom) underlying the single-pulse PSPs for a representative high-pass neuron. B, Same as in A for a low-pass neuron whose 10 ms IPI conductances fit a depression model for low-pass tuning. C, Same as in A for a low-pass neuron whose 10 ms IPI conductances do not fit a depression model for low-pass tuning. D, E, Bar graphs of the average durations (D) and amplitudes (E) of excitatory and inhibitory conductances elicited by single pulses in high- and low-pass neurons. Error bars represent SEM. The p values are shown for significant differences between excitation and inhibition resulting from paired t tests.

Figure 7.

Convolutions of single-pulse conductances reveal that, without depression, excitation would summate more than inhibition in high-pass neurons, whereas inhibition would summate more than excitation in low-pass neurons. A, The recorded membrane potential (“V_m recorded”) and the membrane potential resulting from conductance convolutions (“V_m from convolutions”) of a high-pass neuron in response to a 10 ms IPI stimulus train. B, The estimated (“gI estimated”) and convolved (“gI convolved”) inhibitory conductances of the same neuron in A in response to a 10 ms IPI train. C, D, Normalized convolved synaptic conductances during a 10 ms IPI train for high-pass (C) and low-pass (D) neurons. *p < 0.01, repeated-measures ANOVA, interaction between excitation/inhibition and pulse time. E, F, Bar graphs of the average time constants (E) and amplitudes (F) of single exponential fits to normalized convolved excitatory and inhibitory conductances. Error bars represent SEM.

Figure 8.

With temporal summation alone or depression alone, tuning among the population of ELp neurons would shift toward low-pass. A, B, Tuning curves of observed PSPs, PSPs after summation removal (“depression only”), and PSPs estimated from conductance convolutions (“summation only”) in response to IPI stimuli from high-pass (A) and low-pass (B) neurons. Error bars represent SEM. C, The percentage of neurons (n = 36 neurons) classified as each tuning type using the observed PSPs, the PSPs estimated from conductance convolutions, and the PSPs after summation removal. Reported p values are the results of χ² observed versus expected frequency tests.

Figure 9.

Depression increases selectivity for direction of interval change. A, The V_m values recorded from a low-pass neuron in response to a decreasing then an increasing IPI scan stimulus. B, Close-up of the responses to short intervals of the recording trace in A. Numbers below the stimulus tick marks indicate the IPI in milliseconds. C, A plot of the PSP amplitudes of the neuron in A versus IPI for the decreasing (black) and increasing (gray) portions of the scan stimulus. The scan DSI for this neuron was 0.33. D, Bar graph of the average scan DSI for observed PSPs, PSPs estimated from conductance convolutions (“summation only”), and PSPs after summation removal (“depression only”). Because there were no differences in DSI among high-pass, low-pass, bandpass, and bandstop neurons, neurons from all tuning groups were combined. The reported p value is the result of a Tukey's post hoc test following a repeated-measures ANOVA.

Figure 10.

Schematic of ELp circuitry and synaptic mechanisms contributing to interval tuning. A, An ELp neuron (black) receives excitatory (green) inputs from ELa and from other ELp neurons, as well as inhibitory (magenta) inputs from other ELp neurons. B, High-pass tuning is associated with excitation that depresses less than inhibition, leading to more temporal summation of excitation than inhibition. Excitation and inhibition elicited by the first stimulus pulse are indicated by thin lines. The summed response is the result of adding excitatory and inhibitory traces. C, The majority of low-pass neurons fit a depression model in which excitation depresses more than inhibition. Onset inhibition that lasts longer than onset excitation also contributes to low-pass responses. D, A subset of low-pass neurons does not fit a depression model for low-pass tuning; instead, excitation depresses less than inhibition. Onset inhibition that lasts longer than onset excitation contributes to these neurons' low-pass responses.