The ability to determine the location of the source of a sound is critical for all animals. They can more easily find prey, escape from predators and survive other dangers in nature thanks to their sound localization skills. Humans, as well, benefit from this ability to assess their safety and to distinguish speech when competing sounds are present. Unlike visual and somatosensory systems, the auditory system does not map the spatial origin of stimuli onto the sensory epithelium. Instead, the brain uses temporal, spectral, and intensity cues to determine the location of the source of sounds in three-dimensional space (Middlebrooks, 2015). Locating a sound in the horizontal plane requires precise temporal and intensity information coming from both ears. Integration of binaural information in humans takes place in the superior olivary complex (SOC) located in the brainstem, specifically in the medial superior olive (MSO), where azimuthal sound localization occurs. MSO cells receive binaural excitatory inputs from spherical bushy cells (SBCs) and binaural inhibitory inputs driven by globular bushy cells (GBCs), which act via relay nuclei, the medial and lateral nuclei of the trapezoid body (MNTB and LNTB) (Scott et al., 2005). SBCs and GBCs are located in the cochlear nucleus, the first relay point for signals from the periphery to the central auditory system. Multiple spiral ganglion neurons (SGNs) project from the cochlea to SBCs and GBCs and anatomical studies show that SBCs typically receive input from 2 to 4 SGNs while GBCs receive input from 9 to 69 SGNs (Sento and Ryugo, 1989; Liberman, 1991; Ryugo and Sento, 1991; Spirou et al., 2005). Integration of input from multiple SGNs, along with specializations in synaptic and intrinsic physiology, enable SBCs and GBCs to respond to sound with more precise phase-locking than the SGN fibers, therefore transmitting precise timing information to MSO cells (Joris et al., 1994). A reduced representation of this circuitry is shown in Figure 1.

Humans can resolve interaural time differences (ITDs), the difference in the arrival time of a sound to each ear, as short as 10 μs, and can locate sound sources as precisely as a few degrees of azimuth (Kandel et al., 2000). MSO cells participate in sound localization by acting as coincidence detectors with their firing activity showing sensitivity to ITD levels (Yin and Chan, 1990). Specifically, MSO cells, on one side of the brain, do not fire unless they are excited by contra- and ipsilateral SBCs within a short time window. For binaural excitatory inputs to coincide at an MSO on one side of the brain, the sound needs to arrive to the contralateral ear first. In this way, the internal delay caused by the signal traveling from the contralateral ear is compensated for. As a result, the ITDs inducing the highest activity in the MSO on one side of the brain, also called the best ITDs, correspond to slightly contralateral-leading sound source locations. This gives rise to different MSO responses in each side to the same sound, and the horizontal location of the sound is encoded in the brain by the difference in firing rates between the MSOs in each side (Harper and McAlpine, 2004).

The precise timing of binaural signals is essential to detect the horizontal direction of the sound source. Therefore, the disruption of signaling along peripheral auditory circuits would significantly impair sound localization ability in humans. Many behavioral and electrophysiological studies suggest that humans with normal audiometric thresholds can have problems with encoding and processing binaural cues, giving rise to speech intelligibility and ITD sensitivity deficits. These deficits occur as a result of noise exposure (Bharadwaj et al., 2015; Bernstein and Trahiotis, 2016; Prendergast et al., 2017), aging (Eddins et al., 2018) or demyelinating diseases (Rance et al., 2012; Furst and Levine, 2015; Choi et al., 2018), and lead to a condition known as hidden hearing loss (HHL). In this study, we hypothesize that these perceptual deficits stem from the lack of coincidence of inputs from SBCs to MSO cells, leading to decreased activity levels of MSO cells and deficits in ITD discrimination. To test this hypothesis, we constructed a network model of binaural auditory processing from the periphery to the MSO. We employed the computational model from Budak et al. (2021) to simulate the response of SGN fibers to sound stimuli under conditions simulating either myelin defects at SGN heminodes or synapse loss at inner hair cell (IHC)-SGN synapses, since animal studies suggested that myelinopathy in the SGN heminodes (Wan and Corfas, 2017) and synaptopathy at IHC-SGN synapses (Kujawa and Liberman, 2009; Furman et al., 2013; Sergeyenko et al., 2013; Viana et al., 2015; Gleich et al., 2016; Valero et al., 2017) result in HHL. We additionally simulated the activity of SBC and GBC populations, and their projections to MSO populations. Model results show decreased firing rates of MSO cells for varying ITDs with increasing degrees of myelinopathy and synaptopathy, indicating decreased MSO activity and ITD sensitivity. This effect on MSO activity is less pronounced in response to sounds waves at resonant frequencies of MSO cells, i.e., the sound frequencies at which MSO cells exhibit the highest activity. These results provide evidence that HHL-associated peripheral neuropathies might lead to lower MSO ITD sensitivity, especially at non-resonant sound frequencies, which potentially causes sound localization problems and speech intelligibility deficits in HHL patients.

In this study, we aimed to bridge the gap between observed peripheral auditory deficits in animal models of HHL and mechanisms underlying perceptual deficits in patients with HHL. For that purpose, we modeled a mammalian SOC circuit that includes cochlear sound processing and SGN, SBC, GBC, and MSO cell populations (Figure 1), focusing on the crucial role that MSO cells play in sound localization. We simulated circuit responses to binaural sound stimuli at different azimuthal locations under multiple peripheral auditory deficit conditions that have been shown to cause HHL in animal models, i.e., myelinopathy at the SGN axons (Wan and Corfas, 2017) and synaptopathy at IHC-SGN synapses (Kujawa and Liberman, 2009; Furman et al., 2013; Sergeyenko et al., 2013; Viana et al., 2015; Gleich et al., 2016; Valero et al., 2017). Specifically, we analyzed the population firing rates and phase-locking to sound stimuli while simulating varying degrees of myelinopathy at the SGN axons (Wan and Corfas, 2017) and synaptopathy at IHC-SGN synapses (Kujawa and Liberman, 2009; Furman et al., 2013; Sergeyenko et al., 2013; Viana et al., 2015; Gleich et al., 2016; Valero et al., 2017).

We prescribed SGN myelinopathy levels (see also Budak et al., 2021) by varying the length of the initial unmyelinated segment L_u, such that 0% variation represents a homogeneous population of SGN fibers whose L_u is 10 μm (putative control condition), whereas 100% variation stands for a heterogeneous SGN population where L_u’s vary between 10 and 20 μm.

Experimental results show that the synaptopathy driven by noise-exposure selectively targets IHC-HT SGN synapses (Furman et al., 2013). Here, for generality, we simulated two types of synaptopathies, high threshold (HT) and random synaptopathies, to compare their differential effects on downstream circuit activity. In HT synaptopathy, we removed an increasing fraction of IHC-HT SGN synapses, leaving all low- (LT) and medium-threshold (MT) synapses intact, such that all HT synapses were intact in 0% synaptopathy (putative control condition) and all HT synapses were removed in 100% synaptopathy. In random synaptopathy, the same number of synapses as the corresponding level of HT synaptopathy was removed across all three types of SGN fibers. All synapses were present at 0% synaptopathy (putative control condition) and 1/3rd of the synapses were randomly removed at 100% synaptopathy. In this way, random synaptopathy acts as a control simulation to understand the specific effect of the loss of IHC-HT SGN synapses on downstream processing.

In this study, we built a computational model of mammalian brainstem auditory circuits to understand the impact of peripheral neural deficits, such as SGN myelin defects or loss of IHC-SGN synapses, on binaural auditory processing. Specifically, we explored how the activity of SGNs, cochlear nucleus cells (SBCs and GBCs) and MSO cells are affected by varying degrees of demyelination and synaptopathy of auditory nerve and IHC-SGN synapses, respectively. Motivated by experimental results in animal models, we modeled the degree of demyelination by increasing the range of L_u, the length of the initial unmyelinated segment in SGN axons (Wan and Corfas, 2017), and the degree of synaptopathy by removing IHC-SGN synapses (Kujawa and Liberman, 2009; Furman et al., 2013; Sergeyenko et al., 2013). Model results provided evidence that the activity of an SGN population and the level of phase-locking to the sound stimulus drops with larger ranges of L_u values and higher degrees of synaptopathy, resulting in decreased firing rates and relative vector strength (VS) of cells downstream of SGNs, i.e., SBCs, GBCs, and MSOs (Figure 2). In synaptopathy conditions, these disrupted spiking patterns of cochlear nucleus and MSO cells stemmed purely from loss of SGN firing activity. However, myelinopathy was found to have two effects on SGN activity patterns: it decreased both the rates and the degree of synchrony of SGN spikes (Budak et al., 2021). To explore solely the effect of synchronous activity of SGN fibers, we artificially added jitter to SGN spikes without decreasing the amount of activity. Model results showed that higher levels of SGN jitter affected the activity and relative VS of downstream cells significantly (Figure 3). This confirms the hypothesis that synchronous activity of SGN fibers is essential for proper cochlear nucleus and MSO activity patterns. Specifically, multiple SGN inputs need to arrive at SBCs within a short time window to generate SBC activity, therefore desynchronized SGN activity reduces the probability of SBC firing. Likewise, lower SBC activity decreases the chance of coincident binaural excitatory input to the MSO, leading to lower MSO firing rates.

Since the difference in MSO firing rates between the left and right MSO is critical for the detection of the horizontal angle of sound sources, lower activity levels in both MSOs, as we observed in all peripheral auditory deficit scenarios we studied, decreases this difference (Figure 4), presumably causing binaural processing and sound localization deficits. These results are in line with behavioral human studies, which provided evidence that myelin defects affecting the auditory nerve or auditory brainstem generate problems in locating sound (Rance et al., 2012; Furst and Levine, 2015; Choi et al., 2018). In addition, synapse loss in the cochlea has been associated with degraded temporal coding in the auditory nerve and brainstem (Bharadwaj et al., 2015) and poorer performance in sound localization tasks (Bharadwaj et al., 2015; Bernstein and Trahiotis, 2016; Prendergast et al., 2017; Eddins et al., 2018).

As MSO cells are known to have resonance properties due to their phasic firing patterns (Svirskis et al., 2002; Gai et al., 2010; Meng et al., 2012), we investigated how effects of peripheral neuropathy may differ at resonant compared to non-resonant frequency sound stimuli. While all neuropathy conditions decreased measures of MSO activity and ITD sensitivity (ΔR amplitude), the deficits were less severe at resonant frequencies. Furthermore, results showed that the disruptive effect of all peripheral auditory neuropathy scenarios could be compensated for by the resonance effect, as the activities of MSO cells were still reasonably high in case of higher levels of synaptopathy or myelinopathy conditions in response to sound stimuli at resonant frequencies (Figures 5C–K, 6). In contrast, the MSO activities in response to sound stimuli with frequencies higher or lower than the resonant frequency were already low in the control case, therefore, peripheral auditory deficits led to significant degradation of MSO activity.

In addition, a counterintuitive effect arises in response to higher frequency sounds at higher levels (80 dB SPL, 800 and 1,000 Hz sound stimuli) where the amplitude of ΔR seemed to increase for increasing levels of neuropathies (Figures 5I–K), even though the MSO spike rates did not show the same effect (Figures 6G–I). This counterintuitive outcome may stem from the fact that MSO cells were overly stimulated at higher sound levels, resulting in smaller differences between left and right MSO spike rates as a function of varying ITDs. However, introducing peripheral neuropathies resulted in a decrease in the amount of input MSO cells received, causing a more significant difference between both MSO spike rates for varying ITDs, even though the absolute rate of MSO activity decreased for all ITD levels.

The compensation for peripheral auditory deficits by MSO cells’ resonance properties would only be significant if these deficits occurred at the SGN fibers having CFs corresponding to resonant frequencies of MSOs. There is no study to our knowledge that investigates the CFs of SGN fibers with myelin defects. However, several animal studies provided evidence that hidden hearing loss occurs as a result of synaptopathy at IHC’s with high CF [>10 kHz in mice (Kujawa and Liberman, 2009), >2 kHz in guinea pigs (Furman et al., 2013), and rhesus monkeys (Valero et al., 2017)]. As MSO cells are not responsive to sound frequencies >1.5 kHz, synaptopathy scenarios at IHC-SGN synapses with high CFs may be more effective on circuits that respond more to high frequency sounds. For instance, like MSO cells, lateral superior olive (LSO) cells are located in SOC, but unlike MSO cells, they are responsible for localizing high frequency sounds using interaural level difference (ILD) cues (Park et al., 2004). Therefore, as a future direction, modeling LSO circuits and assessing ILD sensitivity of LSO cells in synaptopathy scenarios may also give us insight into the mechanisms of binaural deficits caused by synaptopathies.

Changes in the phases of firing, relative to the sound wave, of cells upstream of MSO may also contribute to auditory processing deficits. Model results supported this effect as shown by the significant degradation of MSO activity when SGN spike times were jittered (Figure 3). While those results analyzed variations in the phase-locking to the sound wave, as measured by the VS, the possibility remains that the actual phase angle of spikes relative to the sound wave may be disrupted by SGN myelinopathy and synaptopathy. To investigate this, we further computed average phase angles of spikes, relative to sound waves, of all cell types in our SOC circuit model in response to 50 dB SPL sound stimuli with frequencies of 200 Hz (Supplementary Figure 3), 400 Hz (Supplementary Figure 4), and 600 Hz (Supplementary Figure 5) for both myelinopathy (Supplementary Figures 3A–5A) and HT synaptopathy (Supplementary Figures 3B–5B) scenarios. In the SGN, SBC, and GBC populations, we didn’t observe any significant changes in average phase angles for either neuropathy scenario in response to any frequency sound stimuli. Interestingly, the phase of firing of MSO cells increased significantly for higher myelinopathy levels in response to 400 Hz 50 dB sound stimuli, the frequency closest to the resonant frequency (Supplementary Figure 4A). This result may arise from the resonance properties of MSO cells at 400 Hz, where the absolute decrease in spike rates is the highest for higher levels of myelinopathy (Figure 6A), significantly affecting the average firing phases of MSO cells. In myelinopathy, MSO cells only fire in the first few sound cycles (Supplementary Figure 4M) and therefore lose the subsequent spikes that fire at earlier phases relative to sound due to the gradual phase shift over time that is apparent in the putative control (Supplementary Figure 4L). The loss of only low-phase spikes results in an increase in the average phase angle of firing in MSO cells. Further investigation on circuits downstream of MSO cells (e.g., inferior colliculus, medial geniculate body, etc.) would be useful to better understand the effect of myelinopathy-induced phase angle increases on auditory perceptual deficits. This analysis showing minimal effects of peripheral neuropathy on spike phase angle, relative to the sound wave, suggests that the primary mechanism underlying binaural deficits obtained in the model is the loss of excitatory signaling from SGN fibers, that results in lower coincident signals downstream of SGNs, thus decreasing activity levels in cochlear nucleus and MSO cells.

In our SOC circuit, we included binaural inhibitory inputs that MSO cells receive from GBCs via relays through the medial and lateral nuclei of the trapezoid body (MNTB and LNTB). However, the function of these inhibitory signals has remained controversial over the years. In particular, some studies suggest that they play a role in shifting the best ITD of MSO cells toward more contralateral ITD values, contributing to the ITD sensitivity of MSO cells (Myoga et al., 2014), whereas other studies claim that inhibition does not shift the window for detecting binaural coincidence, but only reduces the levels of excitation to refine ITD sensitivity or to preserve ITD sensitivity at higher sound intensities (Roberts et al., 2013). Our simulations of the SOC circuit with GBC cells removed addressed these competing hypotheses (Supplementary Figure 1). In putative control conditions (either 0% L_u variation or 0% synaptopathy) in response to sound stimuli at various sound levels and frequencies, model results showed that best ITDs did not significantly shift (Supplementary Figure 1B), but that ITD sensitivity, measured by the amplitude ΔR, was modulated (Supplementary Figure 1C), as hypothesized in Roberts et al. (2013).

In conclusion, our model results showed that mechanisms underlying HHL in animal models, such as myelin defects at SGN fibers or synapse loss at IHC-SGN synapses, may have significant effects on downstream auditory cell responses, such as MSO cell activity, which plays a crucial role in sound localization. Results indicate that loss of SGN spiking activity as well as potentially asynchronous spike timing contribute to a degradation of ITD sensitivity and coding in the MSO. Model results predict that the primary mechanism inducing binaural auditory processing deficits in myelinopathy and synaptopathy conditions is a decrease in SGN firing activity.

These results may provide a reasonable explanation for human auditory deficits where audiometric thresholds are normal but encoding and processing of binaural cues are degraded. In addition, this study may give us insight into possible treatments for HHL scenarios to overcome these binaural processing deficits. To better elucidate the mechanisms of perceptual deficits resulting from peripheral auditory neuropathies, effects on LSO activity patterns should also be investigated, as LSO cells are responsible for localizing high frequency sounds (Park et al., 2004). Our model results additionally provided evidence that peripheral synaptopathy and myelinopathy cause decreased neuronal activity throughout brainstem auditory circuitry, namely all the way from SGN fibers to MSO cells. Such chronic decreases in neuronal activity may result in homeostatic plasticity downstream of the circuit, as sensory deprivation is already known to cause homeostatic plasticity to compensate for decreased neuronal activity in the brain (Turrigiano et al., 1998; Turrigiano, 2008; Bishop and Zito, 2013; Whitt et al., 2014), including in the auditory system (Teichert et al., 2017). Therefore, studying the impact of these peripheral deficits on downstream auditory circuits from midbrain to auditory cortex may shed light into homeostatic plasticity mechanisms and its consequences such as the perception of tinnitus (Yang et al., 2011).

Some people have difficulty understanding speech in crowded social settings, also known as the “cocktail party problem,” despite having normal hearing thresholds for all sound frequencies. One potential cause of this condition is “hidden hearing loss” (HHL), an auditory disorder resulting from noise exposure, aging or peripheral neuropathy. In this study, we hypothesized that the perceptual deficits caused by HHL arise from sound localization problems due to disrupted inputs to the medial superior olive (MSO), a nucleus in the brainstem that integrates binaural signals to determine the relative timing of sound arrival to both ears and to detect the horizontal angle of the sound source. To explore the impacts HHL has on MSO activity, we simulated MSO circuits that receive signals from both ears affected by two peripheral neuropathies which have been previously shown to cause HHL in animal models: (1) loss of synapses between inner hair cells and auditory nerve fibers, and (2) disruption of auditory-nerve myelin. We provide evidence that both scenarios disrupt the activity of MSO cells correlated with sound localization that may, in turn, result in speech intelligibility deficits. This model may be used to elucidate downstream effects of peripheral neuropathies and to propose possible clinical treatments for HHL.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

MB performed the research and analyzed the data. MB, MR, KG, GC, VB, and MZ designed the research, wrote the manuscript, contributed to the article, and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.