Abstract
Abnormal levels of acoustic activity can result in hearing problems such as tinnitus and language processing disorders, but the underlying cellular and synaptic changes triggered by abnormal activity are not well understood. To address this issue, we studied the time course of activity-dependent changes that occur at auditory nerve synapses in mice of both sexes after noise exposure and conductive hearing loss. We found that EPSC amplitude and synaptic depression decreased within 2 d of noise exposure through a decrease in the probability of vesicle release (Pr). This was followed by a gradual increase in EPSC amplitude through a larger pool of releasable vesicles (N). Occlusion of the ear canal led to a rapid decrease in EPSC amplitude through a decrease in N, which was followed by an increase in EPSC amplitude and synaptic depression through an increase in Pr. After returning to normal sound levels, synaptic depression recovered to control levels within 1–2 d. However, repeated exposure to noise for as little as 8 h/d caused synaptic changes after 7 d, suggesting recovery did not fully offset changes. Thus, there appear to be three activity-dependent mechanisms in auditory nerve synapses—bidirectional changes in Pr in 1–2 d, slower bidirectional changes in N through synaptic growth or retraction, and rapid downregulation of N with low activity. The dynamic changes indicate that multiple mechanisms are present to fine-tune synaptic fidelity across different acoustic conditions in a simple relay.
SIGNIFICANCE STATEMENT Hearing impairments can arise from exposure to noise or conductive hearing loss. This appears to result from changes in the brain, but the mechanisms are not well understood. We study this issue by studying the synapses made by auditory nerve fibers called endbulbs of Held. These synapses undergo bidirectional changes in size and release probability of neurotransmitter in response to increased or decreased activity. Here, we made a close examination of how quickly these synaptic characteristics change, which indicates there are at least three cellular mechanisms underlying changes. Furthermore, repeated exposure to brief periods of noise can produce cumulative effects. These changes could significantly affect hearing, especially because they occur at the start of the central auditory pathway.
Introduction
Acoustic experience can influence the transmission of information throughout the auditory pathway (Walmsley et al., 2006; Rubio, 2020). Increased activity, such as resulting from exposure to loud noise, can lead to tinnitus (Shore and Wu, 2019). Decreased activity, such as during otitis media, can result in language processing disorders (Holm and Kunze, 1969; Whitton and Polley, 2011). These hearing deficits are caused by changes in the central auditory pathway (Sanes and Bao, 2009). It is important to identify the cellular processes involved in activity-dependent synaptic changes to develop prevention and treatment strategies. It is also important to understand the time course of the effects so that therapeutic interventions can be made before hearing is permanently affected.
Synaptic changes can come about through changes in the size of the readily releasable pool of vesicles (N), the probability of vesicle release (Pr), or the quantal size (Q). There is extensive evidence in multiple systems that N, Pr, and Q can change in response to activity in vitro (Lüscher et al., 2000; Davis, 2006; Castillo, 2012; Turrigiano, 2012). These synaptic properties have also been shown to be modulated in vivo (Knott et al., 2006; Chen et al., 2011; Hengen et al., 2013; Keck et al., 2013). In the auditory system, noise exposure and conductive hearing loss can affect N, Pr, or Q (Grande et al., 2014; Mendoza Schulz et al., 2014; Mowery et al., 2019), but how these different synaptic properties change and how quickly changes take place is not well understood. By studying the time course, it may provide information about how many cellular mechanisms are involved.
A useful synapse to study the effects of acoustic experience is the endbulb of Held, which is formed by auditory nerve fibers onto bushy cells (BCs) in the cochlear nucleus (Ryugo and Fekete, 1982; Ryugo and Sento, 1991; Spirou et al., 2005). BCs relay precise timing information to the superior olive (Joris et al., 1998; Oertel, 1999; Grothe et al., 2010), so changes in endbulb function may interfere with sound localization. Endbulbs are sensitive to levels of sound-driven activity as exposure to nontraumatic levels of noise for a week results in a decrease in Pr and an increase in N (Ngodup et al., 2015). The opposite effects, increased Pr and decreased N, occur in genetic models of deafness (Oleskevich et al., 2004; Mendoza Schulz et al., 2014) or 1 week after a bilateral occlusion of the ear canal (Zhuang et al., 2017). Monaural deprivation leads to larger postsynaptic densities, increased AMPA receptor expression, and reduced VGluT1 expression (Clarkson et al., 2016); and the overall effect on Q is unclear. Changes in Pr appear to result from changes in presynaptic calcium influx (Zhuang et al., 2020). A better understanding of the time course of changes in synaptic properties could provide insight into the number and diversity of activity-dependent mechanisms at endbulbs.
We addressed this issue by assessing N, Pr, and Q at multiple time points following noise exposure and ear occlusion. We found bidirectional changes in Pr in response to increased or decreased activity with similar time courses, probably reflecting a single process. By contrast, ear occlusion seemed to result in a rapid downregulation in N, whereas noise exposure led to a slow increase in N, suggesting they are initially mediated by different cellular mechanisms. We also found that these mechanisms could be triggered by brief, repeated noise exposure, suggesting they could have a significant impact on hearing.
Materials and Methods
All experiments were performed with the approval of the University at Buffalo Institutional Animal Care and Use Committee. Electrophysiology experiments used CBA/CaJ mice (stock #654, The Jackson Laboratory). Immunohistochemistry experiments were performed on mice expressing YFP in a subset of auditory nerve fibers (see below, Endbulb structure). All experiments used mice of either sex ranging in age from postnatal day (P)20 to P31.
Noise exposure or ear occlusion
Mice were primarily housed in facilities with ambient sound levels measuring 21–38 dB SPL (average of 27 dB) over a frequency range of 1–20 kHz as measured by a Larson Davis 824 sound meter at one-third octave intervals. For noise exposure, mice were housed in a separate room, and a speaker (Fostex FT28D) was placed above the cage and driven by a noise generator (ACO Pacific 3025). Noise intensities in the cage measured 76–85 dB SPL (average of 81 dB SPL). Noise exposure was started at P21.
For mice undergoing occlusion, at P21 both ear canals were either surgically ligated or plugged with a silicone elastomer (Kwik-Cast, World Precision Instruments). Mice undergoing ligation were anesthetized with 200 mg/kg ketamine plus 10 mg/kg xylazine. The skin was depilated with Nair, and treated with betadine. An incision was made ventral to the pinna to expose the ear canal, which was ligated with surgical silk (Harvard Apparatus). The incision was closed using suturing and Vetbond. Recovering mice were given carprofen (5 mg/kg) the following day and were housed in normal acoustic conditions. Before ear-plugged mice were used for brain slice electrophysiology or immunohistochemistry, the efficacy of ear plugs was confirmed using auditory brainstem responses (ABRs). Mice with a <15 dB shift in ABR threshold were excluded from further study.
Auditory brainstem responses
Mice were anesthetized with 200 mg/kg ketamine plus 10 mg/kg xylazine and placed on a 37°C heating pad (Gaymar) in a sound booth (Med Associates) lined with Sonex sound-attenuating foam (Acoustical Solutions). ABRs were recorded with a vertex electrode, an electrode inserted behind the pinna ipsilateral to the stimulated ear, and a ground electrode inserted contralateral to the stimulated ear. Clicks (100 µs) were presented through a speaker (MF1, Tucker-Davis Technologies) placed 10 cm from the stimulated ear canal driven by an ABR rig powered by a WS4 computer with an R26 processor (Tucker-Davis Technologies). ABR threshold was obtained by reducing the stimulus intensity from 90 to 20 dB SPL in steps of 10 dB, with 5 dB steps near threshold. ABR recordings were made and analyzed using BioSig software (Tucker-Davis Technologies).
Electrophysiology
To prepare brain slices for electrophysiology, mice were anesthetized with 200 mg/kg ketamine plus 10 mg/kg xylazine, then perfused transcardially with ice-cold sucrose solution containing the following (in mm): 76 NaCl, 75 sucrose, 25 NaHCO3, 25 glucose, 2.5 KCl, 1.25 NaH2PO4, 7 MgCl2, 0.5 CaCl2. Then the brain was removed, and sagittal slices were cut using a Campden Integraslice 7550 MM or a Leica VT1200 (142 μm), and incubated in standard recording solution containing the following (in mm): 125 NaCl, 26 NaHCO3, 20 glucose, 2.5 KCl, 1.25 NaH2PO4, 1 MgCl2, 1.5 CaCl2, 4 Na l-lactate, 2 Na-pyruvate, 0.4 Na l-ascorbate, bubbled with 95% O2–5% CO2) at 34°C for 20 min. Afterward, slices were kept at room temperature until recordings. During recordings, 1 μm strychnine was added to block spontaneous glycinergic IPSCs. Whole-cell voltage-clamp recordings were made from BCs in the anteroventral cochlear nucleus using borosilicate patch pipettes of resistance 1.3–2.3 MΩ. Pipettes were filled with internal solution containing the following (in mm): 35 CsF, 100 CsCl, 10 EGTA, 10 HEPES, and 1 QX-314, pH 7.3, 300 mOsm. BCs were patched under an Olympus BX51WI microscope with a MultiClamp 700B (Molecular Devices) controlled by an ITC-18 interface (InstruTECH), driven by custom-written software (mafPC) running in Igor (WaveMetrics). The bath was perfused at 3–4 ml/min using a pump (403U/VM2, Watson-Marlow), with standard recording solution running through an inline heater (SH-27B, Warner Instruments) to maintain the temperature at 34°C (controller, TC-324B, Warner Instruments). BCs were held at –70 mV with access resistance 5–15 MΩ compensated to 70%. Cells were identified as BCs by having EPSCs with fast decay kinetics (τ < 0.2 ms) and half-widths (<0.5 ms). Single auditory nerve fibers were stimulated using a glass microelectrode placed 30–50 µm away from the soma with currents of 4–20 µA through a stimulus isolator (A360, World Precision Instruments). Single or paired pulses were applied every 8 s. For mean-variance analysis (see Fig. 3), the concentration of CaCl2 to MgCl2 was modified to the following (in mm): 1:2.5, 1.5:1, 3:0.1, or 4.5:0.05.
Endbulb structure
Endbulb structure was assessed in transgenic mice expressing YFP in auditory nerve fibers. These mice were generated by crossing mice expressing Cre off a promotor for advillin (AVIL-Cre; Zhou et al., 2010), with mice derived from Ai32 mice from The Jackson Laboratory (strain 024109) that have a floxxed construct of channelrhodopsin-EYFP. Both strains were individually backcrossed into the CBA/CaJ line for over 10 generations before crossing for experiments. In these mice (AVIL-YFP), expression of EYFP is in a subset of auditory nerve fibers, despite widespread expression of advillin in auditory nerve fibers (Hasegawa et al., 2007; Zhang-Hooks et al., 2016). AVIL-YFP mice were anesthetized with 200 mg/kg ketamine and 10 mg/kg xylazine, then perfused transcardially with 0.9% saline followed by 4% buffered paraformaldehyde. Brains were removed and postfixed (room temperature, 1 h) before cryoprotecting in 20% sucrose (4°C). Sagittal sections were cut frozen at 25–50 µm thickness on a sliding microtome (American Optical) and washed in phosphate-buffered saline (0.9% NaCl, 0.2 m phosphate; PBS, pH 7.4). Slices were permeabilized with 0.5% Triton X-100 in PBS (PBST) for 10 min, washed in PBS three times, blocked in 1% normal goat serum in PBST for 1 h at room temperature, and incubated overnight at 4°C in primary antibody solution containing anti-VGluT1 (polyclonal guinea pig, 1:500; catalog #135304, Synaptic Systems), and anti-GFP (polyclonal rabbit, 1:1000; catalog #A-6455, Invitrogen) in PBST. Specificity of the anti-VGluT1 antibody was validated by Synaptic Systems using Western blot in VGluT1-knock-out animals (Synaptic Systems, https://www.sysy.com/product/135304#list). Specificity of the anti-GFP antibody was verified by the absence of auditory nerve labeling in animals that lacked the transgene in auditory nerve fibers (data not shown). The sections were then washed three times in PBS and incubated for 2 h with secondary antibodies Alexa Fluor 488 goat anti-rabbit (1:250; catalog #A-11008, Invitrogen,) and Alexa Fluor 594 goat anti-guinea pig (1:250; catalog #A-11076, Invitrogen).
Immunostained sections were imaged on a Leica TCS SP8 confocal microscope system installed on a Leica DMi8 inverted stand. Stacks of images were obtained at 0.3 µm intervals and imported into Igor (WaveMetrics). Structures were traced with a custom-written program based on Reconstruct (Fiala, 2005). Tracing was done blind to the acoustic experience of the animal.
Experimental design and statistical analysis
Average results are reported throughout as mean ± SEM, and the number of cells per group is indicated in the text. Because of the variability in endbulb properties, 15–20 cells were needed for most measurements. Before statistical comparison, normality was evaluated for each dataset using Shapiro–Wilks tests. Most experiments assessed synaptic features at multiple time points. We first used ANOVA (parametric) or Kruskal–Wallis tests (nonparametric) to test for significant changes across all groups, and if significant, we tested the significance of individual time points with post hoc tests. We did not detect changes with age in control animals, so control data were pooled for greater statistical power. For post hoc tests comparing multiple experimental groups to a single control, we used the Tamhane–Dunnett (parametric) or Anderson–Darling many-to-one (nonparametric) tests as implemented in R (adManyOneTest and tamhaneDunnettTest in the PMCMRplus package). When experimental groups were compared with each other, we used the Anderson–Darling all-pairs test (adAllPairsTest). Post hoc tests used Holm's correction method for multiple comparisons. The significance level was set at α = 0.05. Exact p values are shown in the corresponding text.
Results
Synaptic changes after noise exposure and occlusion
We wanted to determine how quickly noise-exposure or ear-occlusion-induced changes in synaptic function. EPSCs were recorded from BCs in whole-cell voltage-clamp following electrical stimulation of single presynaptic auditory nerve synapses. To ensure the stimulation of a single synaptic input, we verified that EPSCs were all-or-none near threshold. We first evaluated the stability of synaptic properties between P20 and P31 (Fig. 1B). At these ages, mice are not yet sexually mature, but the properties of endbulbs appear largely stable (Pliss et al., 2009). We confirmed EPSC1 stability first by performing linear regression, which yielded a slope of 10 ± 202 pA/d (mean ± SEM, 146 cells, 39 mice), which was not significantly different from zero (p > 0.5, t test), indicating no change in EPSC1 over these ages (Fig. 1B). Second, we assigned EPSCs to five age groups (P20–21: 7.7 ± 1.6 nA, 22 cells, 5 mice; P22: 6.7 ± 1.5 nA, 16 cells, 6 mice; P23: 9.4 ± 1.9 nA, 10 cells, three mice; P24–26: 9.0 ± 1.3 nA, 45 cells, 13 mice; P27–31: 7.4 ± 0.9 nA, 53 cells, 12 mice). We detected no significant difference among these groups (Kruskal–Wallis, p = 0.8). Therefore, we pooled control EPSC1 data for subsequent comparisons (8.0 ± 0.6 nA; 146 cells).
Speed of activity-dependent changes in EPSC1 amplitude and PPR at auditory nerve synapses. A, Representative traces showing EPSC1 and PPR for 3 ms interval in control, after noise exposure and after ear ligation. Manipulations were started at P21. B, EPSC1 amplitude for control endbulbs over the ages studied. Small dots are EPSC1 amplitude from 146 cells from 39 mice, and open circles are averages for the age or exposure ranges demarcated by different shading. There were no significant differences between groups (p = 0.8, Kruskal–Wallis test). Line is regression of individual data. C, Effects of noise exposure (195 cells, 50 mice, red) and ear ligation (124 cells, 33 mice, blue) on EPSC1 amplitude. Lines are fits to individual data using segmented regression (see Equation 1). A Kruskal–Wallis test indicated significant differences between exposure groups (p > 0.001), and asterisks mark points that were significantly different from control (p < 0.05, Anderson–Darling many-to-one post hoc test). D, PPR for control endbulbs over the ages studied. There were no significant differences among age groups (p = 0.13, ANOVA). Line is regression of individual data. E, Effects of noise exposure (red) or ear ligation (blue) on PPR. Lines are fits of individual data to the exponential decay function (see Results). ANOVA indicated significant differences between groups (p < 0.001), and asterisks mark points that differed significantly from control (p < 0.05, Tamhane–Dunnett's test). Markers throughout are mean ± SEM.
We then manipulated auditory nerve activity by exposing mice to nontraumatic, broadband noise, or by bilaterally ligating the ear canal beginning at P21, and tracked changes in EPSC1 amplitude. Following noise exposure, EPSC1 appeared to decrease between 0.75 and 4 d compared with control (0.25 d: 7.8 ± 1.7 nA, 16 cells, 7 mice; 0.5 d: 7.1 ± 0.8 nA, 45 cells, 6 mice; 0.75 d: 4.7 ± 0.7 nA, 13 cells, 3 mice; 1 d: 6.0 ± 0.6 nA, 42 cells, 6 mice; 2 d: 4.7 ± 0.6 nA, 19 cells, 4 mice; 3–5 d: 5.5 ± 1.1 nA, 23 cells, 9 mice; 6–10 d: 9.4 ± 1.1 nA, 37 cells, 15 mice; Fig. 1C, red symbols). EPSC1 amplitude also appeared to decrease below control between 2 and 5 d following ear ligation (1 d: 6.8 ± 0.8 nA, 36 cells, 7 mice; 2 d: 5.9 ± 0.8 nA, 23 cells, 9 mice; 3–5 d: 4.3 ± 0.6 nA, 30 cells, 8 mice; 6–10 d: 8.8 ± 1.1 nA, 35 cells, 9 mice; Fig. 1C, blue circles).
We compared the noise-exposed and ear-ligated groups against control and found there was a significant difference (Kruskal–Wallis, p < 0.001). Post hoc comparisons indicated only one condition that differed significantly from control at 3–5 d following ligation (p = 0.01 Anderson–Darling many-to-one test). We were concerned that the highly conservative corrections for multiple comparisons coupled with the large variance in EPSC1 amplitude might obscure real changes following noise exposure or ear ligation. We had found previously that N increases and Pr decreases following noise exposure, while N decreases and Pr increases following ear ligation, with no detectable changes in Q (Ngodup et al., 2015; Zhuang et al., 2017). We were interested to determine whether N and Pr might change with different time courses, so we analyzed the noise-exposure and ear-ligated data using regression with two linear segments as follows:
To understand the cellular mechanisms underlying these processes, we wanted to specifically characterize changes in N, Pr, and Q. We assessed Pr by eliciting pairs of EPSCs with an interval of 3 ms and calculating the ratio of the EPSC amplitudes [paired-pulse ratio (PPR) = EPSC2/EPSC1; Fig. 1A]. PPR is sensitive to changes in Pr, where an increase in Pr is reflected as a lower PPR, and a decrease in Pr is reflected as a higher PPR. We first examined the stability of PPR in control mice. Linear regression of PPR from P20 to P31 had a slope of –0.0026 ± 0.0044/d, which was not significantly different from zero (p = 0.56, 146 cells, 39 mice), indicating no change in PPR over these ages (Fig. 1D). Furthermore, there were no significant changes in average PPR across the age groups (P20–21: 0.56 ± 0.04, 22 cells, 5 mice; P22: 0.53 ± 0.04, 16 cells, 6 mice; P23: 0.58 ± 0.04, 10 cells, 3 mice; P24–26: 0.48 ± 0.02, 45 cells, 13 mice; P27–31: 0.54 ± 0.02, 53 cells, 12 mice; ANOVA, p = 0.13; Fig. 1D). Therefore, control PPR was pooled across all age groups in subsequent analyses (0.53 ± 0.01, 146 cells).
Next, we recorded PPR from mice exposed to noise or with ear ligation for up to 13 d (Fig. 1A,E, red and blue markers). We fit each set of data to the following exponential function: f(t) = ystart + (yend − ystart)(1 − e−t/τ), where ystart is the PPR before manipulation (i.e., 0.53), yend is the ending PPR, and τ is the time constant. Following noise exposure, the PPR increased with τ = 1.07 ± 0.58 d and yend = 0.68 ± 0.03 (160 cells; Fig. 1E, red line), and following ear ligation, PPR decreased with τ = 1.97 ± 1.12 d and yend = 0.40 ± 0.03 (124 cells; Fig. 1E, blue line). Analysis with ANOVA indicated that PPR differed significantly following noise exposure and ear ligation (p < 0.001). Post hoc analysis identified the specific days showing significant changes. Following noise exposure, PPR increased significantly beginning at 1 d and reached a plateau thereafter (1 d: 0.65 ± 0.03, 33 cells, 7 mice; 2 d: 0.63 ± 0.03, 19 cells, 3 mice; 3–5 d: 0.68 ± 0.05, 23 cells, 8 mice; 6–13 d: 0.70 ± 0.05, 22 cells, 9 mice; p < 0.05 each group, Tamhane–Dunnett's test). By contrast, following ear ligation, PPR decreased significantly after 2 d and reached a plateau thereafter (2 d: 0.45 ± 0.02, 23 cells, 4 mice; 3–5 d: 0.38 ± 0.02, 30 cells, 7 mice; 6–10 d: 0.42 ± 0.02, 35 cells, 5 mice; p < 0.03 each group, Tamhane–Dunnett test).
Thus, noise exposure leads to a decrease in Pr within 1 d, consistent with the initial decrease in EPSC1. Because Pr remains low, it does not appear likely to explain the subsequent return of EPSC1 to control levels, indicating that other synaptic changes must be taking place, such as increases in Q or N. Even more strikingly, ear ligation leads to an increase in Pr within 2 d, but EPSC1 decreases at that time, suggesting the increase in Pr is more than offset by other synaptic changes, such as decreases in Q or N. The increase in Pr could contribute to the slower increase in EPSC1 observed 4 d after ligation.
Quantal size and frequency
We next assessed changes in Q by recording spontaneous mEPSC amplitude and frequency (Fig. 2A). Previous studies had found no significant changes in mEPSC amplitude or frequency after 1 week of noise exposure or ear ligation (Ngodup et al., 2015; Zhuang et al., 2017), and we wanted to evaluate whether changes take place on a faster time scale, which could contribute to the changes in EPSC1 we observed. We first examined mEPSC frequency and amplitude between P20 to P30 in control endbulbs, and both appeared stable over this age range. Linear regression of mEPSC amplitude had slope of −1.2 ± 1.6 pA/d, and mEPSC frequency had slope of −0.09 ± 0.28 s−1/d, neither of which differed significantly from zero (64 cells, 13 mice, both p values > 0.4, t test; Fig. 2B,C). In addition, we grouped mEPSC amplitudes and frequencies according to age ranges P20–22, P24–26, and P28–30, and no significant differences were detected among the groups (P20–22: amplitude 134 ± 7 pA, frequency 6.1 ± 1.7 s−1, 19 cells, 4 mice; P24–26: 125 ± 8 pA, 7.1 ± 1.5 s−1, 27 cells, 5 mice; P28–30: 132 ± 9 pA, 5.3 ± 0.8 s−1, 18 cells, 4 mice; Kruskal–Wallis test, p = 0.58 for both mEPSC amplitude and frequency; Fig. 2B,C). Therefore, we pooled control measurements across all ages (amplitude 130 ± 5 pA; frequency 6.3 ± 0.8 s−1).
Changes in quantal size and frequency after noise exposure or ear ligation. A, Representative traces of spontaneous synaptic activity for auditory nerve synapses from control (left, black), noise-exposed (center, red), and ear-ligated (right, blue) mice. B, C, Amplitude (B) and frequency (C) of mEPSCs in control mice. Small markers are individual experiments, and open circles are averages for age groups demarcated by shading. Kruskal–Wallis tests showed no significant differences between groups in mEPSC amplitude or frequency (both p values > 0.5). Lines are regressions to individual data. D, E, Amplitude (D) and frequency (E) of mEPSCs after noise exposure (red) or ear ligation (blue). Small dots are individual experiments, and open circles are averages for the exposure durations demarcated by shading. Lines in E are fits to individual data using segmented regression (see Equation 1). There were no significant effects of noise exposure or ear ligation on mEPSC amplitude (both p values > 0.15, Kruskal–Wallis), nor mEPSC frequency after noise exposure (p = 0.53), but mEPSC frequency decreased significantly following ear ligation (p = 0.02); asterisks mark points that differed significantly from control (p < 0.05, Anderson–Darling many-to-one test). Black line and gray shaded area represent pooled average ± SEM from control cells.
We next examined mEPSCs in bushy cells of mice following noise exposure or ear ligation. There were no significant changes in mEPSC amplitude at any time point following the onset of noise or after ear ligation (Fig. 2D, red and blue markers; both p values > 0.15, Kruskal–Wallis test). Thus, the effects of noise exposure or ear ligation on Q are minor and seem unlikely to contribute to the changes in PPR or EPSC1 observed in Figure 1.
We also investigated changes in mEPSC frequency, which may be influenced by changes in N and Pr (Prange and Murphy, 1999; Burrone et al., 2002), which might change with different time courses. There were no significant changes in mEPSC frequency after noise exposure for any of the age groups (p = 0.53, Kruskal–Wallis). We also fit mEPSC frequency data using segmented regression (see Equation 1), constraining A to the average rate of controls (6.3 s−1). For noise exposure, the fit yielded t0 = 0.49 ± 0.77 d, and B1 = –3.0 ± 4.6 s−1/d and B2 = 0.05 ± 0.15 s−1/d. Neither slope was significantly different from zero (p > 0.5, both slopes, t test, 141 cells, 16 mice, Fig. 2E, red line), indicating negligible effects of noise exposure on mEPSC frequency.
By contrast, mEPSC frequency changed significantly following ear ligation (p = 0.02, Kruskal–Wallis). The mEPSC frequency appeared to decrease between 1 and 4 d following ligation, and post hoc analysis revealed a significant decrease at 2 d (1 d: 4.3 ± 0.4 s−1, 42 cells, 7 mice, p = 0.79; 2 d: 3.4 ± 0.4 s−1, 35 cells, 9 mice, p = 0.04; 4 d: 3.3 ± 0.4 s−1, 31 cells, 11 mice, p = 0.06; 8 d: 5.6 ± 1.1 s−1, 33 cells, 10 mice, p = 0.79; Anderson–Darling many-to-one test; Fig. 2E). Segmented regression yielded t0 = 1.7 ± 0.5 d, B1 = –2.0 ± 0.6 s−1/d, and B2 = 0.4 ± 0.2 s−1/d, and both slopes differed significantly from zero (both p values < 0.01; Fig. 2E, blue line). This suggests that after ligation, one process drives a rapid decrease in mEPSC frequency, followed by a slower process by which mEPSC frequency increases beginning ∼2 d. Pr increases slowly during this period (i.e., Fig. 1E, PPR decreases), so the initial decrease in mEPSC frequency most likely reflects a rapid decrease in the number of functional release sites, consistent with the decrease in EPSC1 observed shortly after ear ligation.
Mean-variance analysis
To explicitly quantify the effects of sound exposure on N, Pr, and Q, we used mean-variance analysis. The relationship between the mean (μ) and variance (σ2) of EPSC1 amplitude can be described by the equation σ2 = Qμ – (μ2/N), when the extracellular calcium concentration (Cae) is varied to influence Pr (Meyer et al., 2001; Silver, 2003; Foster and Regehr, 2004). Recording durations permitted three Cae during each experiment, either 1, 1.5, and 3 mm or 1.5, 3, and 4 mm. Assessing N and Pr in the context of individual vesicles would require application of a low-affinity antagonist, to prevent receptor saturation and desensitization (Xu-Friedman and Regehr, 2004). However, in preliminary experiments with 2 mm kynurenate, we could not raise Pr high enough to constrain the fit. Therefore, we did not use a low-affinity antagonist in the experiments presented here, so the values of N, Pr, and Q do not simply reflect vesicle properties. Figure 3A shows an example recording of a BC from a control animal. Fitting to the equation above yielded N = 63.6 and Q = 185 pA. Using the values of Q and N, we calculated release probability (Pr = EPSC1/QN). For the example in Figure 3A, Pr in 1.5 Cae was 0.22. On average, control synapses had N of 73 ± 9, Q of 182 ± 18 pA, and Pr of 0.48 ± 0.03 in 1.5 Cae (33 cells, 13 mice).
Activity-dependent changes assessed using mean-variance analysis. A, Representative experiment recording from a BC of a control animal. Markers are EPSC1 amplitudes measured over the course of an experiment in three different Ca(e) (1, 1.5, or 3 mM). B, C, Representative experiments with BCs from animals noise exposed for 1 d (B) or 7 d (C). D, Mean and variance from control experiment in A (closed black circles), noise exposed for 1 d in B (open red circles), and noise exposed for 7 d in C (closed red circles). Lines are fits to the mean-variance relationship (see Mean-variance analysis above) to estimate N, Pr, and Q. E, F, Representative recordings made from BCs in animals ear ligated for 2 d (E) or 7 d (F). G, Mean and variance from control experiment in A (closed black circles), ear ligated 2 d in E (open blue circles), and ear ligated 7 d in F (closed blue circles). Lines are fits to the mean-variance relationship (see Mean-variance analysis above). H–J, Histograms for N (H), Q (I), and Pr (J) for control, noise exposed 1 or 7 d, and ear ligated 2 or 7 d. Dots are individual data. Bars indicate mean ± SEM. Asterisks denote significant difference from control (p < 0.05, Kruskal–Wallis followed by Anderson–Darling many-to-one test).
We next examined the effects of noise exposure (Fig. 3B–D) and ear ligation (Fig. 3E–G) on N, Pr, and Q. Comparing all groups simultaneously showed there was a significant change in N (p < 0.001, Kruskal–Wallis test). Post hoc analysis indicated there was no significant change in N after noise exposure for 1 d (75 ± 12, 13 cells, 3 mice, p = 0.68, Anderson–Darling many-to-one test; Fig. 3H), but there was a significant increase at 7 d (153 ± 28, 16 cells, 7 mice, p = 0.02, Anderson–Darling many-to-one test; Fig. 3H). The effects at 7 d are similar to findings in a previous study (Ngodup et al., 2015). Thus, noise exposure leads to an increase in N between day 1 and 7, which may contribute to the increase in EPSC1 over this period (Fig. 1C).
We next considered the effects of ear ligation after 2 and 7 d with post hoc analyses. We saw a significant decrease in N at both 2 and 7 d (2 d: 29 ± 7, 16 cells, 4 mice, p = 0.003; 7 d: 43 ± 5, 20 cells, 7 mice, p = 0.04; Anderson–Darling many-to-one test, Fig. 3H). The results at 7 d are similar to the findings of a previous study (Zhuang et al., 2017). Thus, N decreased by 2 d after ear ligation, which likely contributed to the initial decrease in EPSC1 (Fig. 1C) and mEPSC frequency (Fig. 2E).
No significant changes were detected in either Pr or Q following noise exposure or ear ligation (p > 0.50, Kruskal–Wallis test). The lack of change in Q is consistent with previous studies (Ngodup et al., 2015; Zhuang et al., 2017) and the present measurements of mEPSC amplitude (Fig. 2D). However, the lack of change in Pr is unexpected, especially considering the robust changes in PPR in Figure 1E. One possible reason for this difference is that the value of Pr in mean-variance analysis is derived from EPSC1 at a single Cae, so quantifying Pr may be subject to more error than Q and N, which are produced by fitting over multiple data points. Overall, it seems most likely that after noise exposure, Pr decreases followed by a slower increase in N, whereas after ear ligation N initially decreases followed by an increase in Pr, with neither manipulation causing a change in Q.
Changes in endbulb structure
The changes in N following noise exposure or ear ligation likely result from changes in the number of release sites. We wanted to see whether there were corresponding structural changes in endbulbs. Our strategy was to label endbulbs using an antibody against VGluT1 (Lauer et al., 2013), which reveals puncta surrounding BC somata (Fig. 4A, yellow). VGluT1 labels synaptic vesicles in endbulbs, so we considered VGluT1-positive puncta as likely functional synaptic regions of the endbulb. BCs in mice receive 2–5 endbulbs (Nicol and Walmsley, 2002; Wang and Manis, 2008; Cao and Oertel, 2010; Chanda and Xu-Friedman, 2010b). To aid reconstruction of individual endbulbs, we used a strain of mice expressing YFP in a subset of auditory nerve fibers (AVIL-YFP) such that one or two endbulbs were labeled per BC (Fig. 4A, cyan). To ensure that the expression of YFP did not affect the size of the synapse, we compared the areas of YFP-positive and YFP-negative fibers, and found they were not significantly different (YFP positive: 47.47 ± 7.09 µm3, 23 endbulbs; YFP negative: 39.78 ± 5.60 µm3, 22 endbulbs; 3 mice; p = 0.40, t test). The expression of YFP did not appear to correlate with calretinin immunolabelling (data not shown), so it is probably unrelated to auditory nerve fiber subtype. We used the YFP labeling to aid in identifying puncta from the same endbulb. VGluT1-positive structures were traced and linked between optical sections (Fig. 4B). The areas of traces were used to calculate the volumes of synaptic regions of each endbulb.
Structural changes in endbulbs after noise exposure and ear ligation. A, Optical section from the cochlear nucleus of an AVIL-YFP mouse immunostained for VGluT1. YFP labeling is shown in cyan and VGluT1 in yellow. B, Traces of four different endbulbs (red, magenta, blue, black) around the BC in A. Optical sections were sampled every 0.3 µm, with every third section shown here. Tracings marked with the asterisk (left, third row) correspond to the images in A. C, Synaptic volumes from P24 animals in control conditions, noise exposed for 3 d, ear ligated for 3 d, P27 control animals, noise exposed for 7 d and ear ligated for 7 d. Dots are individual synaptic volumes, and bars indicate averages ± SEM. Asterisks denote significant difference from age-matched controls (p < 0.05, Kruskal–Wallis followed by Anderson–Darling all-pairs test).
We performed reconstructions of endbulbs from age-matched control, noise-exposed, and ear-ligated mice. Tracing was done blind to the manipulation. A Kruskal–Wallis test found there was a significant difference among the groups (p < 0.001). Post hoc analysis revealed that there was no significant change in VGlut1+ regions of endbulbs after 3 d of noise exposure compared with P24 controls (control: 38.4 ± 5.2 µm3, 32 endbulbs, 3 mice; noise exposed: 40.9 ± 4.2 µm3, 48 endbulbs, 3 mice; p > 0.50, Anderson–Darling all-pairs test; Fig. 4C). However, VGlut1+ regions were significantly larger in mice exposed to noise for 7 d compared with P28 controls (control: 43.0 ± 4.4 µm3, 50 endbulbs, 3 mice; noise exposed: 63.5 ± 8.1 µm3, 54 endbulbs, 3 mice; p = 0.02, Anderson–Darling all-pairs test; Fig. 4C). For ear ligation, VGlut1+ regions of endbulbs were not significantly different after 2 d (35.5 ± 4.9 µm3, 24 endbulbs, 3 mice, p > 0.50, Anderson–Darling all-pairs test) but were significantly smaller after 7 d of ear ligation (21.5 ± 1.7 µm3, 59 endbulbs, 3 mice, p < 0.001, Anderson–Darling all-pairs test; Fig. 4C). These data suggest that elevated or decreased acoustic activity causes morphologic changes in the extent of the vesicle pool in the endbulb, not immediately, but after several days.
The slow increase in the extent of the vesicle pool following noise exposure could correspond to the gradual increase in EPSC1 amplitude (Fig. 1C) and the increase in N in mean-variance analysis (Fig. 3H). However, the slow decrease in vesicle pool area following ear ligation does not directly match the faster time course of the decrease in EPSC1 (Fig. 1C), mEPSC frequency (Fig. 2E), or N in mean-variance analysis (Fig. 3H). Thus, ear ligation appears to trigger another mechanism that drives a decrease in N, distinct from large-scale changes in morphology.
Occluding with ear plugs
We wanted to study the rate of recovery of Pr after returning to normal sound conditions. We were concerned that repeated surgery and anesthesia associated with ligating and unligating the ear might obscure changes in Pr. Therefore, we evaluated the effectiveness of occlusion by plugging the ear canals with a fast-setting silicone, which could be applied and removed without anesthesia or surgery. We compared the effectiveness of plugging versus ligating by comparing ABRs to click stimuli. A Kruskal–Wallis test showed that there was a significant difference in ABR threshold between groups (p < 0.001). Subsequent post hoc tests indicated that ABR thresholds increased significantly from 35.5 ± 1.1 dB SPL (11 ears, 6 mice) to 57.5 ± 2.5 dB SPL after ear plugging (8 ears, 4 mice, p < 0.001, Anderson–Darling all-pairs test) and to 69.5 ± 2.9 dB SPL after ear ligating (21 ears, 11 mice, p < 0.001, Anderson–Darling all-pairs test; Fig. 5A,B). Furthermore, although ear plugs were effective, they were significantly less effective at increasing ABR threshold than ligating (p < 0.001, Anderson–Darling all-pairs test).
Efficacy of ear plugging versus ear ligation. A, Representative ABRs from control, plugged, and ligated ears. Arrowheads mark threshold. B, ABR threshold for control, plugged, and ligated ears. C, PPR recorded from BCs in ear-plugged animals. Small triangles are PPRs from individual cells, and open red triangles are averages. Average PPRs for ear-ligated cells are duplicated from Figure 1 for comparison (open blue circles). The black line and dark gray bar indicate control mean ± SEM. PPR after ear plugging did not differ significantly from ear ligating at any time point (p > 0.5, each comparison).
We verified whether ear plugging could induce synaptic changes by quantifying changes in PPR. Ear ligation and ear plugging had broadly similar effects on PPR, and they were not significantly different at any of the comparable time points (ear plugging 1 d: 0.53 ± 0.02, 15 cells, 3 mice; 2 d: 0.43 ± 0.03, 13 cells, 3 mice; 4 d: 0.41 ± 0.03, 21 cells, 3 mice; 8 d: 0.42 ± 0.04, 8 cells, 3 mice; all p > 0.50, t tests comparing corresponding ear-ligation time points; Fig. 5C). Thus, the effects of ear plugging and ligation seem similar and may be useful for studying recovery from occlusion.
Recovery of Pr
We explored the recovery of PPR following a return to normal sound conditions after 3 or 10 d of noise exposure. A Kruskal–Wallis test indicated significant differences in PPR between the different exposure groups (p = 0.001). We then conducted post hoc comparisons using the Anderson–Darling many-to-one test to identify specific differences. For 3 d of noise exposure, PPR remained significantly elevated by 6 h in quiet conditions (0.76 ± 0.03, 9 cells, 3 mice, p < 0.001) and was indistinguishable from control levels beginning at 12 h (12 h: 0.57 ± 0.04, 7 cells, 2 mice; 24 h: 0.54 ± 0.06, 12 cells, 3 mice; 36 h: 0.57 ± 0.05, 15 cells, 4 mice; p > 0.50 each test; Fig. 6A, red circles). For mice exposed to noise for 10 d, a Kruskal–Wallis test also indicated significant differences between groups (p = 0.001). Post hoc analysis using Anderson–Darling many-to-one tests showed that PPR remained significantly elevated after 12 h in quiet conditions (0.78 ± 0.04, 19 cells, 2 mice, p < 0.001), slightly elevated above control over the following 24 h (1 d: 0.64 ± 0.06, 14 cells, 2 mice, p = 0.049), and was indistinguishable from control after 1.5 d (0.61 ± 0.04, 16 cells, 4 mice; p = 0.13; Fig. 6A, purple circles). This suggests that Pr recovers quickly, with the rate depending on the duration of noise exposure.
Recovery of PPR after noise exposure and ear plugging. A, PPR after 0, 0.25, 0.5, 1, or 1.5 d recovery in quiet conditions, following noise exposure for 3 d (red) or 10 d (purple). Dots are individual data, and open circles are averages. B, PPR after 3 d of ear plugging. Black line and gray bar in A and B represent the control mean ± SEM. Asterisks denote points significantly different from control (p < 0.05, Kruskal–Wallis followed by Anderson–Darling many-to-one test).
We also studied the recovery of PPR after ear plugging for 3 d. The Kruskal–Wallis test indicated that there were significant differences between the treatment groups (p = 0.009). Post hoc analysis using the Anderson–Darling many-to-one test indicated that PPR was significantly more depressed than control 6 h and 12 h after unplugging (6 h: 0.40 ± 0.04, 10 cells, 2 mice, p = 0.04; 12 h: 0.36 ± 0.07, 8 cells, 2 mice, p = 0.04) and was indistinguishable from control by 1 d (0.50 ± 0.03, 9 cells, 2 mice, p = 0.45; Fig. 6B). Thus, Pr appears to recover on a similar time scale following occlusion or noise exposure.
Repeated exposure
We examined how periods of recovery between repeated bouts of noise exposure might affect auditory nerve synapses by exposing mice to noise for a number of hours per day for 7 d before slices were cut to assess synaptic properties (Fig. 7A). The 0 h/d condition (i.e., no noise exposure) had relatively depressed PPR after 7 d (0.53 ± 0.02, 19 cells, 5 mice), very similar to the control value used throughout, whereas 24 h/d is the same as constant noise for 7 d or more in Figure 1A. A Kruskal–Wallis test indicated significant differences between groups (p < 0.001). Subsequent post hoc analysis using the Anderson–Darling many-to-one test indicated a significant increase in PPR after 7 d of noise exposure for 8 h/d (0.65 ± 0.03, 19 cells, 2 mice, p = 0.02), and 12 h/d (0.71 ± 0.03, 27 cells, 3 mice, p < 0.001) compared with 0 h/d (Fig. 7B), but no increase in PPR after 4 h/d (0.47 ± 0.04, 15 cells, 2 mice). By contrast, EPSC1 showed no significant changes for any duration of noise exposure (4 h/d: 4.9 ± 0.9 nA; 8 h/d: 7.1 ± 0.8 nA; 12 h/d: 7.4 ± 0.9 nA; p = 0.23, Kruskal–Wallis). These results suggest that the effects of even brief noise exposure can accumulate, resulting in changes in Pr within a few days.
Effects of periodic noise exposure. A, Treatment paradigm. Gray bars represent the times the noise was on each day for a week. On day 7, slices were prepared for electrophysiology immediately after ending noise exposure. B, C, PPR (B) and EPSC1 amplitude (C) following 7 d of noise exposure for 0, 4, 8, 12, 24 h/d (15–27 cells per point). Small dots indicate individual data, and open circles are averages. Asterisks denote PPRs significantly >0 h/d (p < 0.05, Kruskal–Wallis followed by Anderson–Darling many-to-one test). EPSC1 did not change significantly (p = 0.23, Kruskal–Wallis).
Discussion
We tracked how quickly changes in acoustic environment lead to physiological and structural changes in auditory nerve synapses, which revealed multiple activity-dependent processes (Fig. 8). PPR changes after 1 or 2 d of noise exposure or occlusion, suggesting activity levels act on a single mechanism to bidirectionally regulate release probability (Pr). Occlusion causes a decrease in EPSC amplitude and mEPSC frequency, most likely through a decrease in N, with changes in endbulb structure occurring after several days. This suggests that the rapid mechanism acts by disabling release sites, followed by slower structural remodeling. Noise exposure leads to a slow increase in N, with physiological and structural features changing together, presumably because adding release sites is more complex.
Graphical summary of synaptic changes. Diagram shows an auditory nerve fiber (blue) contacting a bushy cell (black outline). Release sites are indicated by orange dots. Noise exposure leads to decreased Pr (yellow), followed by structural changes and addition of release sites. Conductive hearing loss (CHL) induces rapid inactivation of release sites (gray), followed by an increase in Pr (red) and then by structural changes.
Recovery from noise or occlusion appeared to be very fast. That might suggest that noise exposure followed by equal time for recovery would produce little effect on synaptic function. However, repeated exposure to noise for as little as 8 h/d induced changes in PPR. This may have implications for people who are exposed daily to loud environments, despite having time for recovery. Furthermore, it suggests that the cellular mechanisms involved in detecting the activity levels retain some residual activation from one bout of noise exposure to the next.
Changes in N and Pr, but not Q
This study shows that for manipulations of both noise exposure and occlusion, endbulbs respond by changing the presynaptic properties of N and Pr. PPR results show most clearly that Pr is bidirectionally sensitive to activity, with changes becoming evident in 1 or 2 d. It is notable that the changes take longer to develop than presynaptic forms of long-term potentiation (LTP) and long-term depression (LTD) in vitro (Malenka and Bear, 2004), which appear otherwise similar. It is possible the cellular mechanisms are actually the same but that acoustically driven activity is less effective at triggering changes. Protocols for inducing LTP/LTD in vitro are very refined and may be more powerful at recruiting induction mechanisms than acoustic stimuli in vivo. This may also explain the somewhat faster rate of change in Pr with noise exposure compared with occlusion (1.1 vs 2.0 d), because the increase in activity with noise is likely to be substantial, whereas the drop-in activity with occlusion is likely to be smaller.
It is more difficult to evaluate changes in N than in Pr, so we used multiple lines of evidence. For noise exposure, both mean-variance analysis and VGluT1 immunohistochemistry suggested that noise does not drive an increase in N within 1 d, but does after 7 d. Noise-driven changes in EPSC1 amplitude are more complex. Shortly after the start of noise exposure, EPSC1 amplitude decreases, most likely because of a decrease in Pr. Then, after ∼1.5 d, EPSC1 amplitude begins to increase, most likely from an increase in N (because Q does not change measurably).
The changes in N with occlusion are more complex. Mean-variance analysis and mEPSC frequency suggest N decreases within 2–4 d after occlusion, but structural changes in VGluT1 immunohistochemistry are not visible until 7 d. Remarkably, the overall effect is an initial decrease in EPSC1, despite Pr increasing. Together, these results suggest that occlusion triggers a rapid downregulation of N, with slower increase in Pr, followed by structural rearrangements that maintain a low N.
It is striking that the changes in N and Pr compensate almost perfectly for each other, yielding the same average EPSC1 after 7 d. During noise exposure, first, Pr decreases and then N increases, whereas after occlusion, N appears to decrease first followed by increasing Pr. This is surprising because EPSC1 in vitro represents release from a fully rested and recovered synapse, which auditory nerve synapses are unlikely to be in vivo, especially in the presence of noise. Even so, recruiting additional release sites would also increase the amplitude of chronically depressed EPSCs, thereby preserving the fidelity of the synapse. In addition, EPSC amplitude would also be expected to affect the timing of postsynaptic spikes, because postsynaptic latency and jitter are sensitive to EPSP amplitude (Xu-Friedman and Regehr, 2004; Yang and Xu-Friedman, 2009; Chanda and Xu-Friedman, 2010a). This is important, because the timing of BC spikes is used for sound localization (Oertel, 1999), so shifts in EPSC amplitude resulting from changes in activity levels during noise exposure or occlusion could disrupt interaural comparisons of sound level or timing. Adjusting N and Pr together may minimize such disruption.
Our methods of noise exposure and occlusion did not perturb Q. This is striking because changes in activity do affect Q in other systems both in vitro (Turrigiano et al., 1998; Wierenga et al., 2006) and in vivo (Hengen et al., 2013; Torrado Pacheco et al., 2021; Wu et al., 2021). Furthermore, changes in Q have been observed in the auditory cortex following occlusion in vivo (Mowery et al., 2019). Endbulbs from knock-outs of the synaptic protein Bassoon have deeper depression and show increased Q (Mendoza Schulz et al., 2014). In addition, monaural occlusion leads to lower VGluT1 density on endbulb vesicles and more AMPA receptors at BC postsynaptic densities (Clarkson et al., 2016), which could affect Q. An increase in Q would be consistent with the homeostatic effect of synaptic scaling. It is not clear why noise exposure or binaural occlusion do not also cause a change in Q. Insight into this issue may arise with better understanding of the induction mechanisms driving changes in Q at endbulbs.
Cellular mechanisms of changes in Pr and N
Our results suggest that during noise exposure, Pr decreases before N increases, whereas during occlusion, N decreases before Pr increases. The changes in Pr appear to occur at roughly the same time following a change in acoustic conditions, suggesting increases and decreases share a common activity-dependent mechanism. Imaging experiments suggest that changes in Pr at the endbulb and calyx of Held result from modulation of presynaptic calcium influx (Fekete et al., 2019; Zhuang et al., 2020). The time course for changes in Pr was more than a day, which does not put strong constraints on the possible cellular mechanisms. Calcium influx could be modulated through phosphorylation of channels (Catterall and Few, 2008), which can occur much faster than 1 d. It is possible that in vivo, the signaling pathway is weakly activated, so phosphorylation could occur more slowly. Alternatively, the cellular mechanism may be intrinsically slow, such as requiring gene expression. Indeed, occlusion leads to a shift in calcium channel subtypes driving release at endbulbs (Zhuang et al., 2020), which could require changes in gene expression, although it is possible that different subtypes are already available in a reserve pool of channels.
Our results suggest two different mechanisms regulating N, one following occlusion that rapidly downregulates release sites and one following noise exposure that slowly upregulates release sites. The slow increase appears to parallel structural changes following noise exposure. It seems reasonable that structural changes and the addition of new release sites could take a significant amount of time, for example if vesicles and proteins associated with neurotransmitter release must be generated de novo (Ataman et al., 2008). By contrast, the rapid decrease in N following occlusion could use fast mechanisms such as removing receptors from the postsynaptic density, as occurs in postsynaptic forms of LTD (Lüscher et al., 2000), producing a rapid decrease in EPSC1 amplitude. It would be interesting to determine whether the same release sites that are rapidly disabled after occlusion are then gradually removed by structural changes, or if there are larger reworkings of the synapse taking place.
Implications for hearing
Our findings represent a major change in our understanding of the function of auditory nerve synapses. Until recently, endbulbs were thought to be relatively stable synapses, simply relaying precise temporal information about sounds from the cochlea to the superior olive for sound localization. Now we understand there are multiple processes regulating N and Pr based on activity. We have shown that these forms of long-term synaptic plasticity can be triggered through realistic exposure. Exposure to noise for 8 h/d is sufficient to cause changes in synaptic function, despite even longer periods of recovery. Because endbulbs are a major conduit for auditory activity into the brain, changes in these synapses may have a significant effect on hearing.
Footnotes
This work was supported by funding from the National Institute of Deafness and Other Communication Disorders of the National Institutes of Health (Grant RO1 DC015508). We thank Sydney Brongo, Connor Cook, Alex Gennaro, Kim Nguyen, Tenzin Ngodup, Gabriel Si, John Puskas, and Xiaowen Zhuang for comments and support throughout this project; Victoria Gellatly and James Engel for maintaining the mouse colony; Fan Wang at Duke University for the gift of the AVIL-CRE mice; Wade Sigurdson for confocal assistance; Micheal Dent for the use of the ABR apparatus; and Yan Li for statistical advice.
The authors declare no competing financial interests.
- Correspondence should be addressed to Matthew A. Xu-Friedman at mx{at}buffalo.edu
