The effects of the activation of the inner-hair-cell basolateral K+ channels on auditory nerve responses

MYH1 deficiency disrupts outer hair cell electromotility, resulting in hearing loss

Myh1 is a mouse deafness gene with an unknown function in the auditory system. Hearing loss in Myh1-knockout mice is characterized by an elevated threshold for the auditory brainstem response and the absence of a threshold for distortion product otoacoustic emission. Here, we investigated the role of MYH1 in outer hair cells (OHCs), crucial structures in the organ of Corti responsible for regulating cochlear amplification. Direct whole-cell voltage-clamp recordings of OHCs revealed that prestin activity was lower in Myh1-knockout mice than in wild-type mice, indicating abnormal OHC electromotility. We analyzed whole-exome sequencing data from 437 patients with hearing loss of unknown genetic causes and identified biallelic missense variants of MYH1 in five unrelated families. Hearing loss in individuals harboring biallelic MYH1 variants was non-progressive, with an onset ranging from congenital to childhood. Three of five individuals with MYH1 variants displayed osteopenia. Structural prediction by AlphaFold2 followed by molecular dynamic simulations revealed that the identified variants presented structural abnormalities compared with wild-type MYH1. In a heterogeneous overexpression system, MYH1 variants, particularly those in the head domain, abolished MYH1 functions, such as by increasing prestin activity and modulating the membrane traction force. Overall, our findings suggest an essential function of MYH1 in OHCs, as observed in Myh1-deficient mice, and provide genetic evidence linking biallelic MYH1 variants to autosomal recessive hearing loss in humans.

From the outer ear to the nerve: A complete computer model of the peripheral auditory system

Computer models of the individual components of the peripheral auditory system - the outer, middle, and inner ears and the auditory nerve - have been developed in the past, with varying level of detail, breadth, and faithfulness of the underlying parameters. Building on previous work, we advance the modeling of the ear by presenting a complete, physiologically justified, bottom-up computer model based on up-to-date experimental data that integrates all of these parts together seamlessly. The detailed bottom-up design of the present model allows for the investigation of partial hearing mechanisms and their defects, including genetic, molecular, and microscopic factors. Also, thanks to the completeness of the model, one can study microscopic effects in the context of their implications on hearing as a whole, enabling the correlation with neural recordings and non-invasive psychoacoustic methods. Such a model is instrumental for advancing quantitative understanding of the mechanism of hearing, for investigating various forms of hearing impairment, as well as for devising next generation hearing aids and cochlear implants.

Characterization of the decline in auditory nerve phase locking at high frequencies

The frequency dependence of phase locking in the auditory nerve influences various auditory coding mechanisms. The decline of phase locking with increasing frequency is commonly described by a low-pass filter. This study compares fitted low-pass filter parameters with the actual rate of phase locking decline. The decline is similar across studies and only 40 dB per decade, corresponding to the asymptotic decline of a second order filter.

Inner-hair-cell induced hearing loss: A biophysical modeling perspective

In recent years, experimental studies have demonstrated that malfunction of the inner-hair cells and their synapse to the auditory nerve is a significant hearing loss (HL) contributor. This study presents a detailed biophysical model of the inner-hair cells embedded in an end-to-end computational model of the auditory pathway with an acoustic signal as an input and prediction of human audiometric thresholds as an output. The contribution of the outer hair cells is included in the mechanical model of the cochlea. Different types of HL were simulated by changing mechanical and biochemical parameters of the inner and outer hair cells. The predicted thresholds yielded common audiograms of hearing impairment. Outer hair cell damage could only introduce threshold shifts at mid-high frequencies up to 40 dB. Inner hair cell damage affects low and high frequencies differently. All types of inner hair cell deficits yielded a maximum of 40 dB HL at low frequencies. Only a significant reduction in the number of cilia of the inner-hair cells yielded HL of up to 120 dB HL at high frequencies. Sloping audiograms can be explained by a combination of gradual change in the number of cilia of inner and outer hair cells along the cochlear partition from apex to base.

A Modelling Study on the Comparison of Predicted Auditory Nerve Firing Rates for the Personalized Indication of Cochlear Implantation

The decision of whether to perform cochlear implantation is crucial because implantation cannot be reversed without harm. The aim of the study was to compare model-predicted time–place representations of auditory nerve (AN) firing rates for normal hearing and impaired hearing with a view towards personalized indication of cochlear implantation. AN firing rates of 1024 virtual subjects with a wide variety of different types and degrees of hearing impairment were predicted. A normal hearing reference was compared to four hearing prosthesis options, which were unaided hearing, sole acoustic amplification, sole electrical stimulation, and a combination of the latter two. The comparisons and the fitting of the prostheses were based on a ‘loss of action potentials’ (LAP) score. Single-parameter threshold analysis suggested that cochlear implantation is indicated when more than approximately two-thirds of the inner hair cells (IHCs) are damaged. Second, cochlear implantation is also indicated when more than an average of approximately 12 synapses per IHC are damaged due to cochlear synaptopathy (CS). Cochlear gain loss (CGL) appeared to shift these thresholds only slightly. Finally, a support vector machine predicted the indication of a cochlear implantation from hearing loss parameters with a 10-fold cross-validated accuracy of 99.2%.

Kv4.2-Positive Domains on Dendrites in the Mouse Medial Geniculate Body Receive Ascending Excitatory and Inhibitory Inputs Preferentially From the Inferior Colliculus

The medial geniculate body (MGB) is the thalamic center of the auditory lemniscal pathway. The ventral division of MGB (MGV) receives excitatory and inhibitory inputs from the inferior colliculus (IC). MGV is involved in auditory attention by processing descending excitatory and inhibitory inputs from the auditory cortex (AC) and reticular thalamic nucleus (RTN), respectively. However, detailed mechanisms of the integration of different inputs in a single MGV neuron remain unclear. Kv4.2 is one of the isoforms of the Shal-related subfamily of potassium voltage-gated channels that are expressed in MGB. Since potassium channel is important for shaping synaptic current and spike waveforms, subcellular distribution of Kv4.2 is likely important for integration of various inputs. Here, we aimed to examine the detailed distribution of Kv4.2, in MGV neurons to understand its specific role in auditory attention. We found that Kv4.2 mRNA was expressed in most MGV neurons. At the protein level, Kv4.2-immunopositive patches were sparsely distributed in both the dendrites and the soma of neurons. The postsynaptic distribution of Kv4.2 protein was confirmed using electron microscopy (EM). The frequency of contact with Kv4.2-immunopositive puncta was higher in vesicular glutamate transporter 2 (VGluT2)-positive excitatory axon terminals, which are supposed to be extending from the IC, than in VGluT1-immunopositive terminals, which are expected to be originating from the AC. VGluT2-immunopositive terminals were significantly larger than VGluT1-immunopositive terminals. Furthermore, EM showed that the terminals forming asymmetric synapses with Kv4.2-immunopositive MGV dendritic domains were significantly larger than those forming synapses with Kv4.2-negative MGV dendritic domains. In inhibitory axons either from the IC or from the RTN, the frequency of terminals that were in contact with Kv4.2-positive puncta was higher in IC than in RTN. In summary, our study demonstrated that the Kv4.2-immunopositive domains of the MGV dendrites received excitatory and inhibitory ascending auditory inputs preferentially from the IC, and not from the RTN or cortex. Our findings imply that time course of synaptic current and spike waveforms elicited by IC inputs is modified in the Kv4.2 domains.

A convolutional neural-network framework for modelling auditory sensory cells and synapses

In classical computational neuroscience, analytical model descriptions are derived from neuronal recordings to mimic the underlying biological system. These neuronal models are typically slow to compute and cannot be integrated within large-scale neuronal simulation frameworks. We present a hybrid, machine-learning and computational-neuroscience approach that transforms analytical models of sensory neurons and synapses into deep-neural-network (DNN) neuronal units with the same biophysical properties. Our DNN-model architecture comprises parallel and differentiable equations that can be used for backpropagation in neuro-engineering applications, and offers a simulation run-time improvement factor of 70 and 280 on CPU or GPU systems respectively. We focussed our development on auditory neurons and synapses, and show that our DNN-model architecture can be extended to a variety of existing analytical models. We describe how our approach for auditory models can be applied to other neuron and synapse types to help accelerate the development of large-scale brain networks and DNN-based treatments of the pathological system.

Drakopoulos et al developed a machine-learning and computational-neuroscience approach that transforms analytical models of sensory neurons and synapses into deep-neural-network (DNN) neuronal units with the same biophysical properties. Focusing on auditory neurons and synapses, they showed that their DNN-model architecture could be extended to a variety of existing analytical models and to other neuron and synapse types, thus potentially assisting the development of large-scale brain networks and DNN-based treatments.

A simplified physiological model of rate-level functions of auditory-nerve fibers

Several approaches have been used to describe the rate-level functions of auditory-nerve fibers (ANFs). One approach uses descriptive models that can be fitted easily to data. Another derives rate-level functions from comprehensive physiological models of auditory peripheral processing. Here, we seek to identify the minimal set of components needed to provide a physiologically plausible account of rate-level functions. Our model consists of a first-order Boltzmann mechanoelectrical transducer function relating the instantaneous stimulus pressure to an instantaneous output, followed by a lowpass filter that eliminates the AC component, followed by an exponential synaptic transfer function relating the DC component to the mean spike rate. This is perhaps the simplest physiologically plausible model capable of accounting for rate-level functions under the assumption that the model parameters for a given ANF and stimulus frequency are level-independent. We find that the model typically accounts well for rate-level functions from cat ANFs for all stimulus frequencies. More complicated model variants having saturating synaptic transfer functions do not perform significantly better, implying the system operates far away from synaptic saturation. Rate saturation in the model is caused by saturation of the DC component of the filter output (e.g., the receptor potential), which in turn is due to the saturation of the transducer function. The maximum mean spike rate is approximately constant across ANFs, such that the slope parameter of the exponential synaptic transfer function decreases with increasing spontaneous rate. If the synaptic parameters for a given ANF are assumed to be constant across stimulus frequencies, then frequency- and level-dependent input nonlinearities are derived that are qualitatively similar to those reported in the literature. Contrary to assumptions in the literature, such nonlinearities are obtained even for ANFs having high spontaneous rates. Finally, spike-rate adaptation is examined and found to be accounted for by a decrease in the slope parameter of the synaptic transfer function over time following stimulus onset.

Optimized Tuning of Auditory Inner Hair Cells to Encode Complex Sound through Synergistic Activity of Six Independent K+ Current Entities

Auditory inner hair cells (IHCs) convert sound vibrations into receptor potentials that drive synaptic transmission. For the precise encoding of sound qualities, receptor potentials are shaped by K⁺ conductances tuning the properties of the IHC membrane. Using patch-clamp and computational modeling, we unravel this membrane specialization showing that IHCs express an exclusive repertoire of six voltage-dependent K⁺ conductances mediated by K_v1.8, K_v7.4, K_v11.1, K_v12.1, and BK_Ca channels. All channels are active at rest but are triggered differentially during sound stimulation. This enables non-saturating tuning over a far larger potential range than in IHCs expressing fewer current entities. Each conductance contributes to optimizing responses, but the combined activity of all channels synergistically improves phase locking and the dynamic range of intensities that IHCs can encode. Conversely, hypothetical simpler IHCs appear limited to encode only certain aspects (frequency or intensity). The exclusive channel repertoire of IHCs thus constitutes an evolutionary adaptation to encode complex sound through multifaceted receptor potentials.

Enhancing the sensitivity of the envelope-following response for cochlear synaptopathy screening in humans: The role of stimulus envelope

Auditory de-afferentation, a permanent reduction in the number of inner-hair-cells and auditory-nerve synapses due to cochlear damage or synaptopathy, can reliably be quantified using temporal bone histology and immunostaining. However, there is an urgent need for non-invasive markers of synaptopathy to study its perceptual consequences in live humans and to develop effective therapeutic interventions. While animal studies have identified candidate auditory-evoked-potential (AEP) markers for synaptopathy, their interpretation in humans has suffered from translational issues related to neural generator differences, unknown hearing-damage histopathologies or lack of measurement sensitivity. To render AEP-based markers of synaptopathy more sensitive and differential to the synaptopathy aspect of sensorineural hearing loss, we followed a combined computational and experimental approach. Starting from the known characteristics of auditory-nerve physiology, we optimized the stimulus envelope to stimulate the available auditory-nerve population optimally and synchronously to generate strong envelope-following-responses (EFRs). We further used model simulations to explore which stimuli evoked a response that was sensitive to synaptopathy, while being maximally insensitive to possible co-existing outer-hair-cell pathologies. We compared the model-predicted trends to AEPs recorded in younger and older listeners (N=44, 24f) who had normal or impaired audiograms with suspected age-related synaptopathy in the older cohort. We conclude that optimal stimulation paradigms for EFR-based quantification of synaptopathy should have sharply rising envelope shapes, a minimal plateau duration of 1.7-2.1 ms for a 120-Hz modulation rate, and inter-peak intervals which contain near-zero amplitudes. From our recordings, the optimal EFR-evoking stimulus had a rectangular envelope shape with a 25% duty cycle and a 95% modulation depth. Older listeners with normal or impaired audiometric thresholds showed significantly reduced EFRs, which were consistent with how (age-induced) synaptopathy affected these responses in the model.

Phase Locking of Auditory Nerve Fibers: The Role of Lowpass Filtering by Hair Cells

Phase locking of auditory-nerve-fiber (ANF) responses to the temporal fine structure of acoustic stimuli, a hallmark of the auditory system's temporal precision, is important for many aspects of hearing. Previous work has shown that phase-locked period histograms are often well described by exponential transfer functions relating instantaneous stimulus pressure to instantaneous spike rate, with no observed clipping of the histograms. The operating points and slopes of these functions change with stimulus level. The mechanism underlying this apparent gain control is unclear but is distinct from mechanical compression, is independent of refractoriness and spike-rate adaptation, and is apparently instantaneous. Here we show that these findings can be accounted for by a model consisting of a static Boltzmann transducer function yielding a clipped output, followed by a lowpass filter and a static exponential transfer function. Using responses to tones of ANFs from cats of both sexes, we show that, for a given ANF, the period histograms obtained at all stimulus levels for a given stimulus frequency can be described using one set of level-independent model parameters. The model also accounts for changes in the maximum and minimum instantaneous spike rates with changes in stimulus level. Notably, the estimated cutoff frequency is lower for low- than for high-spontaneous-rate ANFs, implying a synapse-specific contribution to lowpass filtering. These findings advance our understanding of ANF phase locking by highlighting the role of peripheral filtering mechanisms in shaping responses of individual ANFs.SIGNIFICANCE STATEMENT Phase locking of auditory-nerve-fiber responses to the temporal fine structure of acoustic stimuli is important for many aspects of hearing. Period histograms typically retain an approximately sinusoidal shape across stimulus levels, with the peripheral auditory system operating as though its overall transfer function is an exponential function whose slope decreases with increasing stimulus level. This apparent gain control can be accounted for by a static saturating transducer function followed by a lowpass filter. In addition to attenuating the AC component, the filter approximately recovers the sinusoidal waveform of the stimulus. The estimated cutoff frequency varies with spontaneous rate, revealing a synaptic contribution to lowpass filtering. These findings highlight the significant impact of peripheral filtering mechanisms on phase locking.

Phase Locking of Auditory-Nerve Fibers Reveals Stereotyped Distortions and an Exponential Transfer Function with a Level-Dependent Slope

Phase locking of auditory-nerve-fiber (ANF) responses to the fine structure of acoustic stimuli is a hallmark of the auditory system's temporal precision and is important for many aspects of hearing. Period histograms from phase-locked ANF responses to low-frequency tones exhibit spike-rate and temporal asymmetries, but otherwise retain an approximately sinusoidal shape as stimulus level increases, even beyond the level at which the mean spike rate saturates. This is intriguing because apical cochlear mechanical vibrations show little compression, and mechanoelectrical transduction in the receptor cells is thought to obey a static sigmoidal nonlinearity, which might be expected to produce peak clipping at moderate and high stimulus levels. Here we analyze phase-locked responses of ANFs from cats of both sexes. We show that the lack of peak clipping is due neither to ANF refractoriness nor to spike-rate adaptation on time scales longer than the stimulus period. We demonstrate that the relationship between instantaneous pressure and instantaneous rate is well described by an exponential function whose slope decreases with increasing stimulus level. Relatively stereotyped harmonic distortions in the input to the exponential can account for the temporal asymmetry of the period histograms, including peak splitting. We show that the model accounts for published membrane-potential waveforms when assuming a power-of-three, but not a power-of-one, relationship to exocytosis. Finally, we demonstrate the relationship between the exponential transfer functions and the sigmoidal pseudotransducer functions obtained in the literature by plotting the maxima and minima of the voltage responses against the maxima and minima of the stimuli.SIGNIFICANCE STATEMENT Phase locking of auditory-nerve-fiber responses to the temporal fine structure of acoustic stimuli is important for many aspects of hearing, but the mechanisms underlying phase locking are not fully understood. Intriguingly, period histograms retain an approximately sinusoidal shape across sound levels, even when the mean rate has saturated. We find that neither refractoriness nor spike-rate adaptation is responsible for this behavior. Instead, the peripheral auditory system operates as though it contains an exponential transfer function whose slope changes with stimulus level. The underlying mechanism is distinct from the comparatively weak cochlear mechanical compression in the cochlear apex, and likely resides in the receptor cells.