Subjects were 23 male CBA/Ca mice. Mice were 7–19 weeks old at the time of noise exposure. Control animals were age-matched littermates. ABRs were recorded 1–14 days prior to, 1 day after, and 4 weeks after noise exposure. IC recordings took place 4 weeks after noise exposure. At the end of the final experiment, mice were overdosed with an intra-peritoneal (i.p.) injection of sodium pentobarbital. All experiments were performed in accordance with the United Kingdom Animal (Scientific Procedures) Act of 1986.

Mice were anesthetized with ketamine and medetomidine (i.p.) and positioned in a custom-made sound-proof booth on a heated pad directly underneath the center of a speaker (Stage Line PA Horn Tweeter MHD-220N/RD) positioned 45 cm above. The speaker was calibrated prior to each use to ensure that the frequency response was flat (±2 dB) over the 8–16 kHz range. Noise exposure was performed with an octave-band noise (8–16 kHz) at 100 or 105 dB SPL for 2 h. Noise stimuli were generated using an RX6 processor (Tucker-Davis Technologies, TDT), attenuated as required (TDT PA5) and amplified (TDT SA2). During the noise exposure, pedal reflex and breathing rate were checked every 30 min. Control animals were not exposed to any additional sound beyond the normal background noise in the animal unit.

For ABR recordings, animals were anesthetized with an i.p. injection of ketamine and medetomidine. ABR recordings were obtained using subdermal needle electrodes (Rochester Medical), one inserted at the vertex, and one each behind the ipsilateral and contralateral pinnae. Electrode signals were low-pass filtered (7.5 kHz cut-off frequency, 12 dB per octave) and recorded at 24 kHz sampling rate (TDT RA4LI, RA4PA and RX5). For analysis, ABR data were filtered using a bandpass filter (100–3000 Hz, 5th-order Butterworth filter). Stimuli were either tone pips (5 ms total duration with 1.5 ms rise/fall time; frequencies 6, 8, 11, 16, 24, 32, and 48 kHz; intensities 0–80 dB SPL in 5 dB steps) or clicks (50 μs duration, 0–80 dB SPL in 5 dB steps), both delivered at a rate of 20/s. Stimuli were generated using a TDT RX6 processor, attenuated as needed (TDT PA5), amplified (TDT SA2), and presented in free-field condition with the speaker (TDT FF1) positioned at a 45° to the animal’s axis at a distance of approximately 15 cm. The ear contralateral to the speaker was blocked using a foam earplug. Before the start of each experiment, the transfer function of the speaker was measured with a microphone (4939, Brüel and Kjaer) placed at the location of the animal’s ear with the animal in place. This function was used to calibrate individual tones so that the overall output of the speaker was flat across frequency to ±3 dB. ABR thresholds were determined visually by estimating the lowest sound level at which deflections in the ABR waveform were judged to be greater than the background variability in the waveforms. Measurements of wave amplitudes were performed using custom Matlab software: a time window containing the wave of interest was selected by the user, and the software then detected maxima and minima of the ABR traces within that window. ABR wave amplitudes were measured from the peak to the following trough.

Animals were anesthetized with an i.p. injection of ketamine and medetomidine, followed by administration of dexamethasone and atropine sulfate. Lactated Ringers solution was given every 2 h to maintain hydration. The animal’s temperature was maintained at 37.5°C using a homeothermic blanket connected to a rectal thermistor. Breathing rate was monitored throughout the surgery, and then at 45-min intervals throughout the recording. Once the pedal reflex had been abolished, the mouse was placed in a nose clamp to stabilize the head while leaving the ears free. To access the IC, a large craniotomy (≈4.5–6.5 mm posterior to Bregma, 0.5–3.5 mm lateral to midline) was performed on the right-hand side, revealing the full surface of the right IC. Extracellular, multi-unit recordings were made using single-shank silicon multi-electrodes with 16 recording sites (1 × 16 linear array with 100 μm spacing; NeuroNexus). This arrangement of electrode sites enabled sampling across the full extent of the central nucleus of the IC. The probe was advanced manually until the tip just touched the collicular surface. Using a remote hydraulic microdrive (Neurocraft, FHC Inc.), the electrode array was then advanced rapidly by 2000 μm, to minimize the duration of tissue compression during the initial penetration, and then retracted by 500 μm. Electrode signals were recorded at 24 kHz sampling rate and bandpass-filtered between 300 and 9000 Hz (TDT RX5).

To record frequency-response areas (FRAs), tone pips were played in sequential order from 4 to 70 kHz in one-eighth octave steps, with sound level ranging from 0 to 80 dB SPL in 5 dB steps. Tone pip duration was 100 ms, with a rise/fall time of 5 ms, and the inter-stimulus-interval was 400 ms. The speaker was positioned at a 45° to the animal’s axis and at a distance of approximately 15 cm from the animal’s left ear. The right ear was plugged with a sound-attenuating plug. The equipment for sound generation and delivery was the same as for the ABR measurements. The FRA measurement was repeated three times.

To obtain a measure of the spontaneous firing rates, we recorded 100 epochs of 500 ms duration without sound presentation. The speaker was unplugged during the recording of spontaneous activity.

To obtain multiunit activity, the electrode signals were first stripped of the local field potential by applying an additional high-pass filter with cut-off at 600 Hz, and action potentials were then classified using a latent variable spike-sorting algorithm (45) to separate multi-unit clusters from background noise. Characteristic frequencies (CFs) and thresholds of the multiunits were determined visually from the FRAs. Multi-unit recordings were considered to originate from the central nucleus of the IC (ICc) when there was a clear progression of CFs along the length of the linear electrode array. Recordings from electrodes that deviated from this CF progression were excluded from further analysis. Rate-level functions at CF were then derived from the FRA data. Spontaneous firing rates were determined by calculating the average firing rate over the 100 repetitions of the silent epoch of 500 ms duration.

After the end of an IC recording, the cochleae were harvested and fixed in 4% paraformaldehyde. For immunohistochemistry, the organ of Corti was left in the temporal bone in position with no decalcification in order to identify the precise location of the cells in each cochlea. The tissue was accessed by removing the overlying apical bony covering and the tectorial membrane removed using micropipette aspiration or fine forceps. The procedure therefore differs from more conventional histological procedures and is a novel approach. To identify the synaptic structures after tissue permeabilization, we employed mouse anti-CtBP2 (#612044, BD Transduction Laboratories), used at 1:200, or simultaneously with rabbit anti-GluR2/3 (#AB1506, Millipore Bioscience), used at 1:50, incubated at 4°C overnight with a standard lysine block. The ribbon protein CtBP2 was then labeled by secondary antibodies conjugated to ATTO425 (TEFLabs); the postsynaptic terminals were labeled using biotinylated goat anti-rabbit IgG (#BA-1000, Vector) and subsequent incubation with either fluorescein or Alexa 488 conjugated to streptavidin (#SA-5001 Vector). The temporal bone was mounted for viewing hair cells from scala media and images were acquired as z-stacks with step sizes of 0.2–0.5 μm with a 63 × 1.0 NA objective. For such in situ identifications, multiphoton imaging was used in an upright LSM 510 confocal microscope (Zeiss). Ribbons were identified from z-projections and only those with both labels positively identified and were manually counted. Ribbons per cell were typically determined as averages from the groups of 8–12 IHCs from the 10–30 kHz region of the cochleae. No account was taken individual variations in the cochlear frequency place map between animals. The differences between the resulting data and reported figures from decalcified and dissected tissue [e.g., Ref. (17)] may reflect differences in the sampling processes.

We have set up a computational model of the early auditory system, as described below, to study the effects of different patterns of ANF deafferentation on spontaneous activity in the central auditory system. The model is based on previous models of the effects of loss of inner and outer hair cells and damage to hair cell stereocilia (46, 47) as well as selective deafferentation of high-threshold ANFs (21).

Auditory nerve responses are modeled with a rate-level function that represents the average response of a small population of ANFs, comprising low-, medium-, and high-threshold fibers, with similar CFs (46). The effects of different types of cochlear damage on AN responses are then captured by adjusting the shape of the ANF population rate–intensity function. Selective loss of high-threshold ANFs is captured by scaling down responses to high sound intensities and reducing the maximum firing rate of the ANF population. The resulting rate–intensity function f*(I) is then f*(I)=f(I)−dh[f(I)−fh]+ where []₊ denotes positive rectification, 0 ≤ d_h < 1 represents the fraction of missing high-threshold fibers, and f_h = 100 spikes/s is the firing rate where deafferentation starts to influence the AN population response. In addition to selective deafferentation of high-threshold ANFs, we also consider cases where all fiber types get deafferented: f*(I)=(f(I)−dh[f(I)−fh]+)da

The parameter d_a scales the whole AN population rate-level function, and thus (for d_h = 1) models equal deafferentation of all fiber types when it is set to a value between 0 and 1. When both d_h and d_a are set to values < 1, deafferentation with a bias toward high-threshold fibers is created. Examples of the resulting AN population rate-level functions are shown in Figure 4A. To model hearing threshold increase, we increase the response threshold without changing spontaneous and maximum firing rate, based on the model for outer hair cell loss presented in Ref. (46, 47). Examples of rate–intensity functions with threshold increase and ANF deafferentation can be seen in Figure 4B.

The central auditory system stage comprises a neuronal circuit where projection neurons (PNs) receive inhibition from two different types of inhibitory interneurons, one of them providing wide- and the other narrow-band inhibition. This circuit architecture is based on the circuitry of the dorsal cochlear nucleus (DCN) [reviewed in Ref. (48)], as this circuit is probably the best-characterized circuit in the auditory brainstem. However, by adjusting the strength of inhibition (governed by the two parameters g_w and g_n), a variety of different response types can be generated [see Ref. (47), for more details]. In this study, we used g_w = 0.5 and g_n = 0.6, which yields model PNs with monotonous rate-level functions, as typically observed in the inferior colliculus. Moreover, for the application of the model to data from the IC, we have now also included a response threshold for the PN as an additional parameter to account for the fact that spontaneous firing rates in the IC are generally quite low, and especially lower than in the cochlear nucleus (36, 48, 49). The firing rate response r of the PN to excitatory input at rate f (provided here through the activity of ANFs) and input from the inhibitory interneurons at rates w and n is then given by r=R(f,w,n)=rmaxtanh([f−gww−gnn−th]+​/rmax) where r_max = 300 spikes/s is the maximum firing rate of the PN, and th = 40 spikes/s is the response threshold.

In the model, we assume that the mean firing rate of the PNs is stabilized at a certain target level (i.e., the mean activity obtained for input from an undamaged cochlea) through homeostatic plasticity, which scales the strength of excitatory and inhibitory synapses onto the PN in opposite directions. When the mean activity of the PN is permanently below the target, homeostatic plasticity increases excitation and decreases inhibition to bring activity back up to the target level. Prolonged increases in activity lead to changes in the opposite direction. Synaptic scaling is implemented through the homeostasis factor h (limited to values between 1/3 and 3 to account for physiological constraints on synaptic strength): r=R(f,w,n,h)=rmaxtanh([hf−gwhw−gnhn−th]+​/rmax)

The exact value of h required to reach the desired target mean activity for a certain pattern of cochlear damage is determined numerically.

All data analysis as well as implementation and evaluation of the model were done using MATLAB (The MathWorks Inc., Natick, MA, USA). To test for significant differences, t tests were used unless otherwise stated.

Auditory brainstem responses were measured before, 1 day after, and 4 weeks following noise exposure. At 1 day postexposure, both exposure groups exhibited a shift in response thresholds for tone pips of around 20–40 dB at frequencies above 11 (105-dB-SPL exposure, Figure 1C) or 16 kHz (100-dB-SPL exposure, Figure 1A). Four weeks after noise exposure, ABR thresholds had recovered in the 100-dB-SPL exposure group, such that they were no longer significantly different from the pre-exposure values at all test frequencies (all p-values > 0.1). In the 105-dB-SPL group, thresholds remained significantly elevated by around 20–25 dB at 11 and 16 kHz (p < 0.01 at both frequencies), but recovered, and were no longer significantly different from pre-exposure levels, at 32 and 48 kHz (p > 0.1 at both frequencies, Figure 1C).

The effects of noise exposure on the ABR were further investigated by analyzing the amplitudes of ABR waves I and IV in response to broadband clicks. Four weeks after noise exposure, both exposure groups displayed significantly lower amplitudes of click-evoked ABR wave I compared to control mice (p < 0.01, repeated measures ANOVA). The strongest reduction in ABR amplitude, in conjunction with an increase of the response threshold, was observed in the group exposed to 105-dB-SPL noise (Figure 1D). These changes in the magnitude of ABR wave I are indicative of deafferentation of ANFs (17, 18, 50).

In contrast to the effects of noise exposure on wave I of the ABR, amplitudes of wave IV in the 100-dB-SPL exposure group were virtually identical to those in control animals for click intensities up to 45 dB SPL, and then showed a slightly shallower growth at higher intensities (Figure 1B, right panel). In contrast, in the 105-dB-SPL group, the average amplitudes of ABR wave IV were reduced at low and medium sound intensities, but reached those of control animals at high sound intensities, even though the threshold was shifted by about 15 dB, similar to the elevation in wave I thresholds for this group. Moreover, the slope of the amplitude growth function above threshold was very similar to that of the control group (Figure 1D, right panel).

To confirm that the observed reduction of ABR wave I amplitude was related to deafferentation of AN fibers, cochleae were extracted from representative animals from the control (n = 6), the 100-dB-SPL (n = 3) and the 105-dB-SPL (n = 4) groups, and loss of synaptic ribbons was quantified using immunohistochemistry (see Materials and Methods). Representative examples from a control mouse and a mouse exposed at 105 dB SPL are shown in Figure 1E. Ribbon counting was carried out in up to three regions of the cochlea for each animal, and the counts were averaged across these regions. Compared to control animals, both the 100- and 105-dB-SPL group showed a reduced number of synaptic ribbons per IHC (Figure 1F). There was a significant effect of noise exposure on the ribbon count (p = 0.03, ANOVA).

In addition to measuring wave IV of the ABR, we also assessed the effects of noise exposure on central auditory function by making multi-unit recordings in the central nucleus of the right IC (ICc) of (anesthetized) noise-exposed and control mice using 16-channel single-shank electrode arrays (see Materials and Methods). A total of 66 multi-unit recordings were obtained from control animals, 54 recordings from animals exposed at 100 dB SPL, and 111 recordings from animals exposed at 105 dB SPL. In control animals, the largest fraction of multi-unit recordings had CFs in the range of 16–24 kHz, commensurate with the most sensitive region of the mouse audiogram. However, in both noise exposure groups, CFs in the range of 8–12 kHz, i.e., near the low-frequency end of the octave-band noise used for the acoustic over-exposure, were most frequently encountered (Figure 2A). Similar results were obtained for best frequencies, i.e., the tone frequencies evoking maximal firing rates (not shown).

In control animals, CF-tone evoked thresholds of ICc recordings ranged from 0 to 45 dB SPL, with a mean of 15.7 ± 1.3 dB SPL. The range of thresholds recorded from the ICc of noise-exposed mice was similar (0–60 dB SPL for 100-dB-SPL exposure and 0–65 dB SPL for 105-dB-SPL exposure); however, the mean threshold of 31.6 ± 1.4 dB SPL in the 105 dB SPL group was significantly higher than in the control group (p < 0.01, Figure 2D), corresponding to the threshold shift that was also observed in the ABR recordings. The mean threshold for recordings from the 100 dB SPL exposure group was 17.4 ± 1.7 dB SPL, which did not differ significantly from control.

Spontaneous firing rates were generally low in the control animals at 7.0 ± 1.3 spikes/s. In both exposure groups, the average spontaneous firing rates were significantly increased compared to control animals (p < 0.01 in both cases). The average spontaneous firing rate was 26.3 ± 4.2 spikes/s in the 100-dB-SPL exposure group and 11.7 ± 3.1 spikes/s in the 105-dB-SPL exposure group. The difference in spontaneous firing rate between the two noise exposure groups was also significant (p < 0.01). To test for significant differences in spontaneous firing rates in different frequency regions, recordings were grouped according to their CFs (8–12 kHz, 12–16 kHz, 16–24 kHz, 24–32 kHz). For CFs <8 kHz and >32 kHz, there were too few recordings in the control data to allow for meaningful statistical analysis. In the control group, average spontaneous rates were around 6–8 spikes/s across frequencies. Spontaneous firing rates in the 100-dB-SPL group were significantly increased in recordings with CFs from 8 to 12 kHz, 12 to 16 kHz, and 16 to 24 kHz (p < 0.01 in all cases). In the 105-dB-SPL group, a significant increase in spontaneous firing rates was seen in the 12–16 kHz range (p < 0.01). Spontaneous firing rates were also higher than in control mice in the 8–12, 16–24, and 24–32 kHz frequency ranges, but the increases did not achieve significance.

To further characterize the effects of noise exposure on the response properties of ICc recordings, we also analyzed rate-vs.-intensity functions for responses to CF tones. For this purpose, the multi-unit recordings were grouped according to their CFs, using the same frequency ranges as for the analysis of spontaneous firing rates. The average rate-vs.-intensity functions for the control group showed a monotonic response growth with increasing stimulus intensity, reaching discharge rates of 150–200 spikes/s at 80 dB SPL (Figure 3). In both exposure groups, on the other hand, the slopes of the rate-vs.-intensity functions were shallower on average, and the maximum responses were reduced compared to those in control animals (Figure 3). However, recordings from the 100-dB-SPL group showed elevated spike rates at sound intensities close to threshold, consistent with greater spontaneous activity.

Perhaps the most surprising outcome of the ICc recording experiments was that noise exposure at 100 dB SPL resulted in a greater increase in spontaneous firing rates than did the 105-dB-SPL exposure. This was despite the fact that 100 dB SPL exposure generated less hearing loss (Figure 1A) and had less effect on the magnitude of ABR wave I (Figure 1B). Our expectation had been that animals in the 105-dB-SPL exposure group would show the greatest increase in spontaneous firing rates, since earlier studies had reported a proportionality between the degree of cochlear damage or threshold increase and the magnitude of spontaneous neuronal hyperactivity [e.g., Ref. (33, 36)], which we had also observed in our earlier modeling results (21, 46, 47, 51).

However, our most recent modeling study has suggested that whereas deafferentation of high-threshold ANFs (which show little or no spontaneous activity) leads to neuronal hyperactivity in the central auditory system, deafferentation of low-threshold fibers (with high spontaneous activity) could even reduce spontaneous firing rates (52). Moreover, while high-threshold ANFs appear to be most susceptible to noise-induced deafferentation (18), reductions in the amplitude of ABR wave I might arise when only low-threshold ANFs are deafferented; recent data suggest that the contribution of high-threshold fibers to the amplitude of ABR wave I is negligible (50). Since mice from the 105-dB-SPL group showed a greater reduction in ABR wave I amplitude with a shallower slope of the amplitude growth function than the mice exposed to noise at 100 dB SPL (Figure 1B), we hypothesized that the 105-dB-SPL-exposed mice might have a higher degree of deafferentation of low-threshold fibers than the 100-dB-SPL mice. We therefore employed the model to explore whether this hypothesis might account for the observed non-monotonic relationship between cochlear damage and IC hyperactivity.

In the model, we first created different patterns of ANF deafferentation, ranging from selective deafferentation of high-threshold ANFs to a pattern where all fiber types are affected to a similar degree (see Materials and Methods and Figure 4A for an example), and combined these patterns of deafferentation with different degrees of hearing loss (i.e., increased thresholds; see Materials and Methods and Figure 4B). By this means, we explored a three-dimensional parameter space of damage parameters spanning (i) the degree of deafferentation, (ii) the pattern of deafferentation (i.e., low, medium and high spontaneous ANFs), and (iii) the degree of hearing loss (threshold increase). The model is based on the assumption that in attempting to stabilize neuronal activity following hearing loss, homeostatic plasticity elevates neuronal response gain in the central auditory system, thereby generating increased spontaneous firing rates through over-amplification of spontaneous activity (21, 46, 47, 53, 54). Hyperactivity thus depends first on how much the gain is increased by homeostatic plasticity and, second, on how much spontaneous activity in the AN is reduced through cochlear damage. If the increase in response gain is greater than the reduction of the spontaneous excitatory input from the ANFs, spontaneous hyperactivity develops (46, 47).

Figure 4C shows model results for four different degrees of overall ANF deafferentation from 10 to 40% of the total number of ANFs. For the case where deafferentation affects only high-threshold ANFs (“Ht only”), and thus does not reduce the amount of spontaneous excitatory input provided to the central auditory system by the ANFs, the greater the number of deafferented fibers the higher the spontaneous rate in the central auditory system following homeostasis. However, when low-threshold (and high spontaneous) fibers are also deafferented (i.e., moving from the bottom to the top, “Ht only” to “Equal” in each plot in Figure 4C), the resulting spontaneous firing rates are always lower than when only high-threshold fibers are deafferented. In the “balanced case” where deafferentation affects all fiber types equally (i.e., at the top of each plot in Figure 4C), there is even the suggestion of hypo-activity with spontaneous firing rates lower than before cochlear damage (the normal, healthy spontaneous rate is indicated by the dashed line in all plots). Finally, in the model, additional increases of peripheral thresholds always increase spontaneous firing rates in the central auditory system. Therefore, the model demonstrates that the same degree of elevation of spontaneous firing rates can be generated by different types of cochlear damage, and that trajectories exist through the “cochlear damage space” where more damage can even lead to a reduction in spontaneous firing rates in the central auditory nervous system, despite the presence of homeostatic plasticity mechanisms.

The ABR results from the 100-dB exposed mice with HHL resembled our findings from an earlier study in which we compared human tinnitus subjects with clinically normal hearing thresholds to age-, gender-, and hearing-matched control subjects, showing that the tinnitus group had significantly smaller amplitudes of ABR wave I (21). A direct comparison between humans and mice is hampered by the fact that ABR wave I amplitudes in mice are more than a magnitude larger than in humans, due to differences in head size and data acquisition methods. We therefore performed a qualitative comparison of the cumulative distributions of ABR wave I amplitudes. Figure 5A shows the cumulative distribution of the amplitudes of ABR wave I elicited by 50 μs clicks at 100 dB SPL for human tinnitus (gray line, n = 15 ears) and control participants (black line, n = 18 ears). Despite the significant difference in average amplitude, there is a considerable overlap in the distributions. Figure 5B shows cumulative distributions of ABR wave I amplitudes (50 μs clicks at 80 dB SPL) for mice before (black line) and 4 weeks after (gray line, 25 ears from 13 mice in both cases) exposure to octave-band noise at 100 dB SPL (note that this data set includes additional mice that did not undergo IC recordings). On a qualitative level, there is a great degree of similarity between mice before and after noise-induced HHL and normal-hearing humans with and without tinnitus, suggesting that mice with noise-induced HHL approximate the ABR-phenotype of human tinnitus subjects with normal hearing thresholds and could therefore, if tinnitus is verified through behavioral tests, potentially serve as an animal model for the condition.