A diffusion model of the transient response of the cochlear inner hair cell synapse

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.

A Fundamental Inequality Governing the Rate Coding Response of Sensory Neurons

A fundamental inequality governing the spike activity of peripheral neurons is derived and tested against auditory data. This inequality states that the steady-state firing rate must lie between the arithmetic and geometric means of the spontaneous and peak activities during adaptation. Implications towards the development of auditory mechanistic models are explored.

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%.

A comparative study of eight human auditory models of monaural processing

A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.

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.

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.

Multidimensional stimulus encoding in the auditory nerve of the barn owl

Auditory perception depends on multi-dimensional information in acoustic signals that must be encoded by auditory nerve fibers (ANF). These dimensions are represented by filters with different frequency selectivities. Multiple models have been suggested; however, the identification of relevant filters and type of interactions has been elusive, limiting progress in modeling the cochlear output. Spike-triggered covariance analysis of barn owl ANF responses was used to determine the number of relevant stimulus filters and estimate the nonlinearity that produces responses from filter outputs. This confirmed that ANF responses depend on multiple filters. The first, most dominant filter was the spike-triggered average, which was excitatory for all neurons. The second and third filters could be either suppressive or excitatory with center frequencies above or below that of the first filter. The nonlinear function mapping the first two filter outputs to the spiking probability ranged from restricted to nearly circular-symmetric, reflecting different modes of interaction between stimulus dimensions across the sample. This shows that stimulus encoding in ANFs of the barn owl is multidimensional and exhibits diversity over the population, suggesting that models must allow for variable numbers of filters and types of interactions between filters to describe how sound is encoded in ANFs.

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

The basolateral membrane of the mammalian inner hair cell (IHC) expresses large voltage and Ca²⁺ gated outward K⁺ currents. To quantify how the voltage-dependent activation of the K⁺ channels affects the functionality of the auditory nerve innervating the IHC, this study adopts a model of mechanical-to-neural transduction in which the basolateral K⁺ conductances of the IHC can be made voltage-dependent or not. The model shows that the voltage-dependent activation of the K⁺ channels (i) enhances the phase-locking properties of the auditory fiber (AF) responses; (ii) enables the auditory nerve to encode a large dynamic range of sound levels; (iii) enables the AF responses to synchronize precisely with the envelope of amplitude modulated stimuli; and (iv), is responsible for the steep offset responses of the AFs. These results suggest that the basolateral K⁺ channels play a major role in determining the well-known response properties of the AFs and challenge the classical view that describes the IHC membrane as an electrical low-pass filter. In contrast to previous models of the IHC-AF complex, this study ascribes many of the AF response properties to fairly basic mechanisms in the IHC membrane rather than to complex mechanisms in the synapse.

Auditory brainstem response latency in forward masking, a marker of sensory deficits in listeners with normal hearing thresholds

In rodent models, acoustic exposure too modest to elevate hearing thresholds can nonetheless cause auditory nerve fiber deafferentation, interfering with the coding of supra-threshold sound. Low-spontaneous rate nerve fibers, important for encoding acoustic information at supra-threshold levels and in noise, are more susceptible to degeneration than high-spontaneous rate fibers. The change in auditory brainstem response (ABR) wave-V latency with noise level has been shown to be associated with auditory nerve deafferentation. Here, we measured ABR in a forward masking paradigm and evaluated wave-V latency changes with increasing masker-to-probe intervals. In the same listeners, behavioral forward masking detection thresholds were measured. We hypothesized that 1) auditory nerve fiber deafferentation increases forward masking thresholds and increases wave-V latency and 2) a preferential loss of low-spontaneous rate fibers results in a faster recovery of wave-V latency as the slow contribution of these fibers is reduced. Results showed that in young audiometrically normal listeners, a larger change in wave-V latency with increasing masker-to-probe interval was related to a greater effect of a preceding masker behaviorally. Further, the amount of wave-V latency change with masker-to-probe interval was positively correlated with the rate of change in forward masking detection thresholds. Although we cannot rule out central contributions, these findings are consistent with the hypothesis that auditory nerve fiber deafferentation occurs in humans and may predict how well individuals can hear in noisy environments.

Functional modeling of the human auditory brainstem response to broadband stimulation

Population responses such as the auditory brainstem response (ABR) are commonly used for hearing screening, but the relationship between single-unit physiology and scalp-recorded population responses are not well understood. Computational models that integrate physiologically realistic models of single-unit auditory-nerve (AN), cochlear nucleus (CN) and inferior colliculus (IC) cells with models of broadband peripheral excitation can be used to simulate ABRs and thereby link detailed knowledge of animal physiology to human applications. Existing functional ABR models fail to capture the empirically observed 1.2-2 ms ABR wave-V latency-vs-intensity decrease that is thought to arise from level-dependent changes in cochlear excitation and firing synchrony across different tonotopic sections. This paper proposes an approach where level-dependent cochlear excitation patterns, which reflect human cochlear filter tuning parameters, drive AN fibers to yield realistic level-dependent properties of the ABR wave-V. The number of free model parameters is minimal, producing a model in which various sources of hearing-impairment can easily be simulated on an individualized and frequency-dependent basis. The model fits latency-vs-intensity functions observed in human ABRs and otoacoustic emissions while maintaining rate-level and threshold characteristics of single-unit AN fibers. The simulations help to reveal which tonotopic regions dominate ABR waveform peaks at different stimulus intensities.

Modeling auditory coding: from sound to spikes

Models are valuable tools to assess how deeply we understand complex systems: only if we are able to replicate the output of a system based on the function of its subcomponents can we assume that we have probably grasped its principles of operation. On the other hand, discrepancies between model results and measurements reveal gaps in our current knowledge, which can in turn be targeted by matched experiments. Models of the auditory periphery have improved greatly during the last decades, and account for many phenomena observed in experiments. While the cochlea is only partly accessible in experiments, models can extrapolate its behavior without gap from base to apex and with arbitrary input signals. With models we can for example evaluate speech coding with large speech databases, which is not possible experimentally, and models have been tuned to replicate features of the human hearing organ, for which practically no invasive electrophysiological measurements are available. Auditory models have become instrumental in evaluating models of neuronal sound processing in the auditory brainstem and even at higher levels, where they are used to provide realistic input, and finally, models can be used to illustrate how such a complicated system as the inner ear works by visualizing its responses. The big advantage there is that intermediate steps in various domains (mechanical, electrical, and chemical) are available, such that a consistent picture of the evolvement of its output can be drawn. However, it must be kept in mind that no model is able to replicate all physiological characteristics (yet) and therefore it is critical to choose the most appropriate model—or models—for every research question. To facilitate this task, this paper not only reviews three recent auditory models, it also introduces a framework that allows researchers to easily switch between models. It also provides uniform evaluation and visualization scripts, which allow for direct comparisons between models.

Basic response properties of auditory nerve fibers: a review

All acoustic information from the periphery is encoded in the timing and rates of spikes in the population of spiral ganglion neurons projecting to the central auditory system. Considerable progress has been made in characterizing the physiological properties of type-I and type-II primary auditory afferents and understanding the basic properties of type-I afferents in response to sounds. Here, we review some of these properties, with emphasis placed on issues such as the stochastic nature of spike timing during spontaneous and driven activity, frequency tuning curves, spike-rate-versus-level functions, dynamic-range and spike-rate adaptation, and phase locking to stimulus fine structure and temporal envelope. We also review effects of acoustic trauma on some of these response properties.

Relating the Variability of Tone-Burst Otoacoustic Emission and Auditory Brainstem Response Latencies to the Underlying Cochlear Mechanics

Forward and reverse cochlear latency and its relation to the frequency tuning of the auditory filters can be assessed using tone bursts (TBs). Otoacoustic emissions (TBOAEs) estimate the cochlear roundtrip time, while auditory brainstem responses (ABRs) to the same stimuli aim at measuring the auditory filter buildup time. Latency ratios are generally close to two and controversy exists about the relationship of this ratio to cochlear mechanics. We explored why the two methods provide different estimates of filter buildup time, and ratios with large inter-subject variability, using a time-domain model for OAEs and ABRs. We compared latencies for twenty models, in which all parameters but the cochlear irregularities responsible for reflection-source OAEs were identical, and found that TBOAE latencies were much more variable than ABR latencies. Multiple reflection-sources generated within the evoking stimulus bandwidth were found to shape the TBOAE envelope and complicate the interpretation of TBOAE latency and TBOAE/ABR ratios in terms of auditory filter tuning.

Modeling the influence of short term depression in vesicle release and stochastic calcium channel gating on auditory nerve spontaneous firing statistics

We propose several modifications to an existing computational model of stochastic vesicle release in inner hair cell ribbon synapses, with the aim of producing simulated auditory nerve fiber spiking data that more closely matches empirical data. Specifically, we studied the inter-spike-interval (ISI) distribution, and long and short term ISI correlations in spontaneous spiking in post-synaptic auditory nerve fibers. We introduced short term plasticity to the pre-synaptic release probability, in a manner analogous to standard stochastic models of cortical short term synaptic depression. This modification resulted in a similar distribution of vesicle release intervals to that estimated from empirical data. We also introduced a biophysical stochastic model of calcium channel opening and closing, but showed that this model is insufficient for generating a match with empirically observed spike correlations. However, by combining a phenomenological model of channel noise and our short term depression model, we generated short and long term correlations in auditory nerve spontaneous activity that qualitatively match empirical data.

Updated parameters and expanded simulation options for a model of the auditory periphery

A phenomenological model of the auditory periphery in cats was previously developed by Zilany and colleagues [J. Acoust. Soc. Am. 126, 2390-2412 (2009)] to examine the detailed transformation of acoustic signals into the auditory-nerve representation. In this paper, a few issues arising from the responses of the previous version have been addressed. The parameters of the synapse model have been readjusted to better simulate reported physiological discharge rates at saturation for higher characteristic frequencies [Liberman, J. Acoust. Soc. Am. 63, 442-455 (1978)]. This modification also corrects the responses of higher-characteristic frequency (CF) model fibers to low-frequency tones that were erroneously much higher than the responses of low-CF model fibers in the previous version. In addition, an analytical method has been implemented to compute the mean discharge rate and variance from the model's synapse output that takes into account the effects of absolute refractoriness.

A hardware model of the auditory periphery to transduce acoustic signals into neural activity

To improve the performance of cochlear implants, we have integrated a microdevice into a model of the auditory periphery with the goal of creating a microprocessor. We constructed an artificial peripheral auditory system using a hybrid model in which polyvinylidene difluoride was used as a piezoelectric sensor to convert mechanical stimuli into electric signals. To produce frequency selectivity, the slit on a stainless steel base plate was designed such that the local resonance frequency of the membrane over the slit reflected the transfer function. In the acoustic sensor, electric signals were generated based on the piezoelectric effect from local stress in the membrane. The electrodes on the resonating plate produced relatively large electric output signals. The signals were fed into a computer model that mimicked some functions of inner hair cells, inner hair cell–auditory nerve synapses, and auditory nerve fibers. In general, the responses of the model to pure-tone burst and complex stimuli accurately represented the discharge rates of high-spontaneous-rate auditory nerve fibers across a range of frequencies greater than 1 kHz and middle to high sound pressure levels. Thus, the model provides a tool to understand information processing in the peripheral auditory system and a basic design for connecting artificial acoustic sensors to the peripheral auditory nervous system. Finally, we discuss the need for stimulus control with an appropriate model of the auditory periphery based on auditory brainstem responses that were electrically evoked by different temporal pulse patterns with the same pulse number.

Modeling auditory evoked brainstem responses to transient stimuli

A quantitative model is presented that describes the formation of auditory brainstem responses (ABRs) to tone pulses, clicks, and rising chirps as a function of stimulation level. The model computes the convolution of the instantaneous discharge rates using the "humanized" nonlinear auditory-nerve model of Zilany and Bruce [J. Acoust. Soc. Am. 122, 402-417 (2007)] and an empirically derived unitary response function which is assumed to reflect contributions from different cell populations within the auditory brainstem, recorded at a given pair of electrodes on the scalp. It is shown that the model accounts for the decrease of tone-pulse evoked wave-V latency with frequency but underestimates the level dependency of the tone-pulse as well as click-evoked latency values. Furthermore, the model correctly predicts the nonlinear wave-V amplitude behavior in response to the chirp stimulation both as a function of chirp sweeping rate and level. Overall, the results support the hypothesis that the pattern of ABR generation is strongly affected by the nonlinear and dispersive processes in the cochlea.

Time course of dynamic range adaptation in the auditory nerve

Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797-13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430-6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological "dual adaptation" model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100-400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds.

Isolating mechanisms that influence measures of the precedence effect: theoretical predictions and behavioral tests

This study tests how peripheral auditory processing and spectral dominance impact lateralization of precedence effect (PE) stimuli consisting of a pair of leading and lagging clicks. Predictions from a model whose parameters were set from established physiological results were tested with specific behavioral experiments. To generate predictions, an auditory nerve model drove a binaural, cross correlation computation whose outputs were summed across frequency using weightings derived from past physiological studies. The model predicted that lateralization (1) depends on stimulus center frequency and the inter-stimulus delay (ISD) between leading and lagging clicks for narrowband clicks and (2) changes differently with lead click level for different ISDs. Behaviorally, subjects lateralized narrowband and wideband click pairs whose stimulus parameters were chosen based on modeling results to test how peripheral processing and frequency dominance contribute to lateralization of PE stimuli. Behavioral results (including unique measures with the lead attenuated relative to the lag) suggest that peripheral interactions between leading and lagging clicks on the basilar membrane and strong weighting of cues around 750 Hz influence lateralization of paired clicks with short ISDs. When combined with auditory nerve adaptation, which emphasizes onset information, lateralization of PE click pairs with a short ISD can be well predicted.

Power-law dynamics in an auditory-nerve model can account for neural adaptation to sound-level statistics

Neurons in the auditory system respond to recent stimulus-level history by adapting their response functions according to the statistics of the stimulus, partially alleviating the so-called "dynamic-range problem." However, the mechanism and source of this adaptation along the auditory pathway remain unknown. Inclusion of power-law dynamics in a phenomenological model of the inner hair cell (IHC)-auditory nerve (AN) synapse successfully explained neural adaptation to sound-level statistics, including the time course of adaptation of the mean firing rate and changes in the dynamic range observed in AN responses. A direct comparison between model responses to a dynamic stimulus and to an "inversely gated" static background suggested that AN dynamic-range adaptation largely results from the adaptation produced by the response history. These results support the hypothesis that the potential mechanism underlying the dynamic-range adaptation observed at the level of the auditory nerve is located peripheral to the spike generation mechanism and central to the IHC receptor potential.

A phenomenological model of the synapse between the inner hair cell and auditory nerve: long-term adaptation with power-law dynamics

There is growing evidence that the dynamics of biological systems that appear to be exponential over short time courses are in some cases better described over the long-term by power-law dynamics. A model of rate adaptation at the synapse between inner hair cells and auditory-nerve (AN) fibers that includes both exponential and power-law dynamics is presented here. Exponentially adapting components with rapid and short-term time constants, which are mainly responsible for shaping onset responses, are followed by two parallel paths with power-law adaptation that provide slowly and rapidly adapting responses. The slowly adapting power-law component significantly improves predictions of the recovery of the AN response after stimulus offset. The faster power-law adaptation is necessary to account for the "additivity" of rate in response to stimuli with amplitude increments. The proposed model is capable of accurately predicting several sets of AN data, including amplitude-modulation transfer functions, long-term adaptation, forward masking, and adaptation to increments and decrements in the amplitude of an ongoing stimulus.

Tonotopic distribution of short-term adaptation properties in the cochlear nerve of normal and acoustically overexposed chicks

Cochlear nerve adaptation is thought to result, at least partially, from the depletion of neurotransmitter stores in hair cells. Recently, neurotransmitter vesicle pools have been identified in chick tall hair cells that might play a role in adaptation. In order to understand better the relationship between adaptation and neurotransmitter release dynamics, short-term adaptation was characterized by using peristimulus time histograms of single-unit activity in the chick cochlear nerve. The adaptation function resulting from 100-ms pure tone stimuli presented at the characteristic frequency, +20 dB relative to threshold, was well described as a single exponential decay process with an average time constant of 18.6+/-0.8 ms (mean+/-SEM). The number of spikes contributed by the adapting part of the response increased tonotopically for characteristic frequencies up to approximately 0.8 kHz. Comparison of the adaptation data with known physiological and anatomical hair cell properties suggests that depletion of the readily releasable pool is the basis of short-term adaptation in the chick. With this idea in mind, short-term adaptation was used as a proxy for assessing tall hair cell synaptic function following intense acoustic stimulation. After 48 h of exposure to an intense pure tone, the time constant of short-term adaptation was unaltered, whereas the number of spikes in the adapting component was increased at characteristic frequencies at and above the exposure frequency. These data suggest that the rate of readily releasable pool emptying is unaltered, but the neurotransmitter content of the pool is increased, by exposure to intense sound. The results imply that an increase in readily releasable pool size might be a compensatory mechanism ensuring the strength of the hair cell afferent synapse in the face of ongoing acoustic stress.

Modeling auditory-nerve responses for high sound pressure levels in the normal and impaired auditory periphery

This paper presents a computational model to simulate normal and impaired auditory-nerve (AN) fiber responses in cats. The model responses match physiological data over a wider dynamic range than previous auditory models. This is achieved by providing two modes of basilar membrane excitation to the inner hair cell (IHC) rather than one. The two modes are generated by two parallel filters, component 1 (C1) and component 2 (C2), and the outputs are subsequently transduced by two separate functions. The responses are then added and passed through the IHC low-pass filter followed by the IHC-AN synapse model and discharge generator. The C1 filter is a narrow-band, chirp filter with the gain and bandwidth controlled by a nonlinear feed-forward control path. This filter is responsible for low and moderate level responses. A linear, static, and broadly tuned C2 filter followed by a nonlinear, inverted and nonrectifying C2 transduction function is critical for producing transition region and high-level effects. Consistent with Kiang's two-factor cancellation hypothesis, the interaction between the two paths produces effects such as the C1/C2 transition and peak splitting in the period histogram. The model responses are consistent with a wide range of physiological data from both normal and impaired ears for stimuli presented at levels spanning the dynamic range of hearing.

Phase locking of auditory-nerve fibers to the envelopes of high-frequency sounds: implications for sound localization

Although listeners are sensitive to interaural time differences (ITDs) in the envelope of high-frequency sounds, both ITD discrimination performance and the extent of lateralization are poorer for high-frequency sinusoidally amplitude-modulated (SAM) tones than for low-frequency pure tones. Psychophysical studies have shown that ITD discrimination at high frequencies can be improved by using novel transposed-tone stimuli, formed by modulating a high-frequency carrier by a half-wave-rectified sinusoid. Transposed tones are designed to produce the same temporal discharge patterns in high-characteristic frequency (CF) neurons as occur in low-CF neurons for pure-tone stimuli. To directly test this hypothesis, we compared responses of auditory-nerve fibers in anesthetized cats to pure tones, SAM tones, and transposed tones. Phase locking was characterized using both the synchronization index and autocorrelograms. With both measures, phase locking was better for transposed tones than for SAM tones, consistent with the rationale for using transposed tones. However, phase locking to transposed tones and that to pure tones were comparable only when all three conditions were met: stimulus levels near thresholds, low modulation frequencies (<250 Hz), and low spontaneous discharge rates. In particular, phase locking to both SAM tones and transposed tones substantially degraded with increasing stimulus level, while remaining more stable for pure tones. These results suggest caution in assuming a close similarity between temporal patterns of peripheral activity produced by transposed tones and pure tones in both psychophysical studies and neurophysiological studies of central neurons.

Analysis of models for the synapse between the inner hair cell and the auditory nerve

A general mathematical approach was proposed to study phenomenological models of the inner-hair-cell and auditory-nerve (AN) synapse complex. Two models (Meddis, 1986; Westerman and Smith, 1988) were studied using this unified approach. The responses of both models to a constant-intensity stimulus were described mathematically, and the relationship between model parameters and response characteristics was investigated. The mathematical descriptions of the two models were essentially equivalent despite their structural differences. This analytical approach was used to study the effects of adaptation characteristics on model parameters and of model parameters on adaptation characteristics. The results provided insights into these models and the underlying biophysical processing. This analytical method was also used to study offset adaptation, and it was found that the offset adaptation of both models was limited by the models' structures. A modified version of the synapse model, which has the same onset adaptation but improved offset adaptation, is proposed here. This modified synapse model produces more physiologically realistic offset adaptation and also enhances the modulation gain of model AN fiber responses, consistent with AN physiology.

A phenomenological model of peripheral and central neural responses to amplitude-modulated tones

A phenomenological model with time-varying excitation and inhibition was developed to study possible neural mechanisms underlying changes in the representation of temporal envelopes along the auditory pathway. A modified version of an existing auditory-nerve model [Zhang et al., J. Acoust. Soc. Am. 109, 648-670 (2001)] was used to provide inputs to higher hypothetical processing centers. Model responses were compared directly to published physiological data at three levels: the auditory nerve, ventral cochlear nucleus, and inferior colliculus. Trends and absolute values of both average firing rate and synchrony to the modulation period were accurately predicted at each level for a wide range of stimulus modulation depths and modulation frequencies. The diversity of central physiological responses was accounted for with realistic variations of model parameters. Specifically, enhanced synchrony in the cochlear nucleus and rate-tuning to modulation frequency in the inferior colliculus were predicted by choosing appropriate relative strengths and time courses of excitatory and inhibitory inputs to postsynaptic model cells. The proposed model is fundamentally different than others that have been used to explain the representation of envelopes in the mammalian midbrain, and it provides a computational tool for testing hypothesized relationships between physiology and psychophysics.

A phenomenological model for the responses of auditory-nerve fibers. II. Nonlinear tuning with a frequency glide

A computational model was developed to simulate the responses of auditory-nerve (AN) fibers in cat. The model's signal path consisted of a time-varying bandpass filter; the bandwidth and gain of the signal path were controlled by a nonlinear feed-forward control path. This model produced realistic response features to several stimuli, including pure tones, two-tone combinations, wideband noise, and clicks. Instantaneous frequency glides in the reverse-correlation (revcor) function of the model's response to broadband noise were achieved by carefully restricting the locations of the poles and zeros of the bandpass filter. The pole locations were continuously varied as a function of time by the control signal to change the gain and bandwidth of the signal path, but the instantaneous frequency profile in the revcor function was independent of sound pressure level, consistent with physiological data. In addition, this model has other important properties, such as nonlinear compression, two-tone suppression, and reasonable Q10 values for tuning curves. The incorporation of both the level-independent frequency glide and the level-dependent compressive nonlinearity into a phenomenological model for the AN was the primary focus of this work. The ability of this model to process arbitrary sound inputs makes it a useful tool for studying peripheral auditory processing.

Intensity discrimination and increment detection in cochlear-implant users

Intensity difference limens (DLs) were measured in users of the Nucleus 22 and Clarion v1.2 cochlear implants and in normal-hearing listeners to better understand mechanisms of intensity discrimination in electric and acoustic hearing and to evaluate the possible role of neural adaptation. Intensity DLs were measured for three modes of presentation: gated (intensity increments gated synchronously with the pedestal), fringe (intensity increments delayed 250 or 650 ms relative to the onset of the pedestal), and continuous (intensity increments occur in the presence of a pedestal that is played throughout the experimental run). Stimuli for cochlear-implant listeners were trains of biphasic pulses; stimuli for normal-hearing listeners were a 1-kHz tone and a wideband noise. Clarion cochlear-implant listeners showed level-dependent effects of presentation mode. At low pedestal levels, gated thresholds were generally similar to thresholds obtained in the fringe and continuous conditions. At higher pedestal levels, however, the fringe and continuous conditions produced smaller intensity DLs than the gated condition, similar to the gated-continuous difference in intensity DLs observed in acoustic hearing. Nucleus cochlear-implant listeners did not show consistent threshold differences for the gated and fringe conditions, and were not tested in the continuous condition. It is not clear why a difference between gated and fringe thresholds occurred for the Clarion but not the Nucleus subjects. Normal-hearing listeners showed improved thresholds for the continuous condition relative to the gated condition, but the effect was larger for the 1-kHz tonal carrier than for the noise carrier. Findings suggest that adaptation occurring central to the inner hair cell synapse mediates the gated-continuous difference observed in Clarion cochlear-implant listeners and may also contribute to the gated-continuous difference in acoustic hearing.

Adaptation in a revised inner-hair cell model

A revised computational model of the inner-hair cell (IHC) and auditory-nerve (AN) complex was recently presented [Sumner et al., J. Acoust. Soc. Am. 111, 2178-2188 (2002)]. One key improvement is that the model reproduces the rate-intensity functions of low- (LSR), medium- (MSR), and high-spontaneous rate (HSR) fibers in the guinea-pig. Here we describe the adaptation characteristics of the model, and how they vary with model fiber type. Adaptation of the revised model for a HSR fiber is in line with an earlier version of the model [Meddis and Hewitt, J. Acoust. Soc. Am. 90, 904-917 (1991)]. In guinea-pig, poststimulus time histograms (PSTH) have been found to show less adaptation in LSR fibers. Evidence from chinchilla suggests that this is due to chronic adaptation resulting from short interstimulus intervals, and that fully recovered LSR fibers actually show more adaptation. However, the model is able to account for both variations of PSTH shape when fully recovered from adaptation. Interstimulus interval can also affect recovery in the model. The model is further tested against data previously used to evaluate models of AN adaptation. The tests are (i) recovery from adaptation of spontaneous rate and (ii) the recovery of response to acoustic stimuli ("forward masking"), (iii) the response to stimulus increments and (iv) decrements, and (v) the conservation of transient components. A HSR model fiber performs similarly to the earlier version of the model. However, there is considerable variation in response to increments and decrements between different model fibers.

Mathematical models of cochlear nucleus onset neurons: I. Point neuron with many weak synaptic inputs

The cochlear nucleus (CN) presents a unique opportunity for quantitatively studying input-output transformations by neurons because it gives rise to a variety of different response types from a relatively homogeneous input source, the auditory nerve (AN). Particularly interesting among CN neurons are Onset (On) neurons, which have a prominent response to the onset of sustained sounds followed by little or no response in the steady-state. On neurons contrast sharply with their AN inputs, which respond vigorously throughout stimuli. On neurons can entrain to stimuli (firing once per cycle of a periodic stimulus) at up to 1000 Hz, unlike their AN inputs. To understand the mechanisms underlying these response patterns, we tested whether an integrate-to-threshold point-neuron model with a fixed refractory period can account for On discharge patterns for tones, systematically examining the effect of membrane time constant and the number and strength of the exclusively excitatory AN synaptic inputs. To produce both onset responses to high-frequency tone bursts and entrainment to a broad range of low-frequency tones, the model must have a short time constant ( approximately 0.125 ms) and a large number (>100) of weak synaptic inputs, properties that are consistent with the electrical properties and anatomy of On-responding cells. With these parameters, the model acts like a coincidence detector with a threshold-like relationship between the instantaneous discharge rates of the output and the inputs. Onset responses to high-frequency tone bursts result because the threshold effect enhances the initial response of the AN inputs and suppresses their relatively lower sustained response. However, when the model entrains across a broad range of frequencies, it also produces short interspike intervals at the onset of high-frequency tone bursts, a response pattern not found in all types of On neurons. These results show a tradeoff, that may be a general property of many neurons, between following rapid stimulus fluctuations and responding without short interspike intervals at the onset of sustained stimuli.

Exponential processes in human auditory excitation and adaptation

Peripheral auditory adaptation has been studied extensively in animal models, and multiple exponential components have been identified. This study explores the feasibility of estimating these component processes for human listeners with a peripheral model of adaptation. The processes were estimated from off-frequency masked detection data that probed temporal masking responses to a gated narrowband masker. The resulting response patterns reflected step-like onset and offset features with characteristically little evidence of confounding backward and forward masking. The model was implemented with linear combinations of exponential functions to represent the unadapted excitation response to gating the masker on and then off and the opposing effects of adaptation in each instance. The onset and offset of the temporal masking response were assumed to be approximately inverse operations and were modeled independently in this scheme. The unadapted excitation response at masker onset and the reversed excitation response at masker offset were each represented in the model by a single exponential function. The adaptation processes were modeled by three independent exponential functions, which were reversed at masker offset. Each adaptation component was subtractive and partially negated the unadapted excitation response to the dynamic masker. This scheme allowed for quantification of the response amplitude, action latency, and time constant for the unadapted excitation component and for each adaptation component. The results reveal that (1) the amplitudes of the unadapted excitation and reversed excitation components grow nonlinearly with masker level and mirror the 'compressive' input-output velocity response of the basilar membrane; (2) the time constants for the unadapted excitation and reversed excitation components are related inversely to masker intensity, which is compatible with neural synchrony increasing at masker onset (or offset) with increasing masker strength; (3) the composite strength of adaptation levels off at high masker levels; this 'saturation' response is consistent with a diminished contribution from peripheral neural adaptation processes at high sound levels; and (4) the response dynamics for two of the adaptation components correspond generally to those for the 'very rapid'/'rapid' processes and 'short-term' processes described in animal studies of peripheral neural adaptation. The action latency of a third adaptation component suggests the role of a second-order peripheral or central process. This modeling exercise (1) indicates that multiple adaptation processes, whatever their origins, contribute substantively to the form of the temporal masking response and (2) supports a sum-of-exponentials scheme for estimating properties of the component processes.

Evaluating auditory performance limits: i. one-parameter discrimination using a computational model for the auditory nerve

A method for calculating psychophysical performance limits based on stochastic neural responses is introduced and compared to previous analytical methods for evaluating auditory discrimination of tone frequency and level. The method uses signal detection theory and a computational model for a population of auditory nerve (AN) fiber responses. The use of computational models allows predictions to be made over a wider parameter range and with more complete descriptions of AN responses than in analytical models. Performance based on AN discharge times (all-information) is compared to performance based only on discharge counts (rate-place). After the method is verified over the range of parameters for which previous analytical models are applicable, the parameter space is then extended. For example, a computational model of AN activity that extends to high frequencies is used to explore the common belief that rate-place information is responsible for frequency encoding at high frequencies due to the rolloff in AN phase locking above 2 kHz. This rolloff is thought to eliminate temporal information at high frequencies. Contrary to this belief, results of this analysis show that rate-place predictions for frequency discrimination are inconsistent with human performance in the dependence on frequency for high frequencies and that there is significant temporal information in the AN up to at least 10 kHz. In fact, the all-information predictions match the functional dependence of human performance on frequency, although optimal performance is much better than human performance. The use of computational AN models in this study provides new constraints on hypotheses of neural encoding of frequency in the auditory system; however, the method is limited to simple tasks with deterministic stimuli. A companion article in this issue ("Evaluating Auditory Performance Limits: II") describes an extension of this approach to more complex tasks that include random variation of one parameter, for example, random-level variation, which is often used in psychophysics to test neural encoding hypotheses.

Evaluating auditory performance limits: II. One-parameter discrimination with random-level variation

Previous studies have combined analytical models of stochastic neural responses with signal detection theory (SDT) to predict psychophysical performance limits; however, these studies have typically been limited to simple models and simple psychophysical tasks. A companion article in this issue ("Evaluating Auditory Performance Limits: I") describes an extension of the SDT approach to allow the use of computational models that provide more accurate descriptions of neural responses. This article describes an extension to more complex psychophysical tasks. A general method is presented for evaluating psychophysical performance limits for discrimination tasks in which one stimulus parameter is randomly varied. Psychophysical experiments often randomly vary a single parameter in order to restrict the cues that are available to the subject. The method is demonstrated for the auditory task of random-level frequency discrimination using a computational auditory nerve (AN) model. Performance limits based on AN discharge times (all-information) are compared to performance limits based only on discharge counts (rate place). Both decision models are successful in predicting that random-level variation has no effect on performance in quiet, which is the typical result in psychophysical tasks with random-level variation. The distribution of information across the AN population provides insight into how different types of AN information can be used to avoid the influence of random-level variation. The rate-place model relies on comparisons between fibers above and below the tone frequency (i.e., the population response), while the all-information model does not require such across-fiber comparisons. Frequency discrimination with random-level variation in the presence of high-frequency noise is also simulated. No effect is predicted for all-information, consistent with the small effect in human performance; however, a large effect is predicted for rate-place in noise with random-level variation.

A phenomenological model for the responses of auditory-nerve fibers: I. Nonlinear tuning with compression and suppression

A phenomenological model was developed to describe responses of high-spontaneous-rate auditory-nerve (AN) fibers, including several nonlinear response properties. Level-dependent gain (compression), bandwidth, and phase properties were implemented with a control path that varied the gain and bandwidth of tuning in the signal-path filter. By making the bandwidth of the control path broad with respect to the signal path, the wide frequency range of two-tone suppression was included. By making the control-path filter level dependent and tuned to a frequency slightly higher than the signal-path filter, other properties of two-tone suppression were also included. These properties included the asymmetrical growth of suppression above and below the characteristic frequency and the frequency offset of the suppression tuning curve with respect to the excitatory tuning curve. The implementation of this model represents a relatively simple phenomenological description of a single mechanism that underlies several important nonlinear response properties of AN fibers. The model provides a tool for studying the roles of these nonlinearities in the encoding of simple and complex sounds in the responses of populations of AN fibers.

Structure and function in the saccule of the goldfish (Carassius auratus): a model of diversity in the non-amniote ear

The vertebrate inner ear is comprised of a remarkable diversity of cell types, including several types of sensory hair cells. In amniotes (reptiles, birds, and mammals), the morphological and physiological characteristics that distinguish these cell types have been well documented, while cellular variation in the ears of non-amniotes (all other vertebrate groups) has remained underrecognized. Since non-amniotes have become increasingly popular models for developmental and genetic research, a more comprehensive understanding of structure and function in the inner ears of these species is warranted. This paper first reviews the large body of data describing the morphology and physiology of hair cells and afferent neurons in the inner ear of the goldfish (Carassius auratus). In particular, we examine the structure of the goldfish saccule, an endorgan that has been the subject of numerous investigations on audition. New data on the structural variation of synaptic bodies in saccular hair cells are also presented, and the functional implications of these data are discussed. Finally, we conclude that hair cell structure varies along the length of the goldfish saccule in a manner consistent with known physiological characteristics of the endorgan. The saccule provides an excellent model for investigating structure-function relationships in the vertebrate inner ear, as well as the development of auditory and vestibular sensory epithelia.

Temporal aspects of the effects of cooling on responses of single auditory nerve fibers

During an investigation of the effects of cochlear cooling on frequency tuning and input/output relations of single auditory nerve fibers in gerbil (Ohlemiller and Siegel (1994) Hear. Res. 80, 174-190), cooling-related changes in post-stimulus time histogram (PSTH) shape and phase-locking to tonebursts were characterized in a small sample of neurons. Local cochlear cooling by 5-10 degrees C below normal core temperature did not alter overall PSTH shape, although some evidence was found for a reduction in the time constants of rapid and short term rate adaptation. The relative contributions of rapid and short term response components appeared unaltered. Effects of cooling on phase-locking were assessed by calculating the synchronization index for responses to intense ( > 70 dB SPL) tonebursts at 0.5, 1.0, and 2.0 kHz. Synchronization filter functions exhibited modest reductions in both magnitude and the upper frequency limit of phase-locking. The effects of cooling on the temporal character of responses appear distinct from those of a simple reduction in stimulus intensity. Results are interpreted in terms of cooling-related changes in responses of cochlear hair cells and afferent neurons, and suggest that temperature artifacts are unlikely to underlie reported species differences in PSTH shape and phase-locking.

Nonlinear feedback models for the tuning of auditory nerve fibers

The tuning of auditory nerve (AN) fibers is generally characterized by an increase in bandwidth and, for mid- to high-frequency fibers, a downward shift in the center frequency as sound level increases. Changes in bandwidth are accompanied by changes in the phase properties of the fibers; thus the timing of neural discharges also changes as a function of sound level. This study focuses on the magnitude and phase properties of models designed to reproduce the nonlinear properties of AN fibers that were studied electrophysiologically. The forward path of each model consisted of a linear second-order resonance, and each feedback path contained a saturating nonlinearity. In model 1, the feedback path was a simple memoryless, saturating nonlinearity. In model 2, a low-pass filter was added after the feedback nonlinearity. The ability of each model to simulate aspects of the nonlinear tuning of AN fibers is discussed. Model 2 was able to simulate a wider range of nonlinear behavior for different AN fibers and thus has promise for use in simulations of populations of fibers tuned to different frequencies.

Nonlinear effects of noise on phase-locked cochlear-nerve responses to sinusoidal stimuli

It is well known that, in a cochlear afferent axon with background spike activity, a sinusoidal stimulus (tone) of sufficiently low frequency will produce periodic modulation of the instantaneous spike rate, the alternating half cycles of which comprise excursions above and below the mean background spike rate. It also is known that if the amplitude of the stimulus is sufficiently small, the instantaneous spike rate follows very nearly a sinusoidal trajectory through these positive and negative excursions. For such cases, we define the AC responsiveness of a primary auditory afferent axon to be the amplitude of sinusoidal modulation of the instantaneous spike rate divided by the amplitude of the tone producing that modulation. In the experiments described in this paper, changes in AC responsiveness were followed during and after sudden changes in the background noise level. When the amplitude of the tone was sufficiently small relative to that of the noise, we found that the AC responsiveness can be strongly dependent on the time elapsed since the last change in noise level, while being nearly independent of the amplitude of the tone itself. Under those circumstances, after transitions between noise levels 20 dB apart, we observed changes in AC responsiveness that consistently followed time courses similar to those of the short-term mean (background) spike rate (approximating the adapting response to the noise alone), unfolding over several milliseconds or tens of milliseconds. At the time of the transition between noise levels, there was another change in AC responsiveness, which appeared to be instantaneous; as the noise level increased, the AC responsiveness immediately increased with it. This seemingly paradoxical effect and the similarity of the time courses of AC responsiveness and short-term mean spike rate both are consistent with a simple, descriptive model of spike generation involving the shifting of threshold along a bell curve.

Quantifying 2-factor phase relations in non-linear responses from low characteristic-frequency auditory-nerve fibers

Auditory-nerve excitation by two response factors that can be in antiphase has been hypothesized by Kiang (1990) on the basis of non-linear interference in responses to tones (Kiang et al., 1969). The general conditions for antiphasic responses and the relevance of the hypothesis for other auditory stimuli are unknown. Clarification was sought in a systematic modeling study of published data on level-dependent non-linear responses from low characteristic-frequency (CF) auditory-nerve fibers for a broad variety of acoustic stimuli. The MBPNL non-linear I/O model of cochlear frequency analysis (Goldstein, 1990), which incorporates the 2-factor hypothesis, was used to simulate the reported non-linear phenomena. It was found that experiments with paired click stimuli (Goblick and Pfeiffer, 1969) and with octave-band complex tones (Horst et al., 1990), in addition to experiments with single clicks or tones, are sensitive to the phase difference between factors. Surprisingly, the paired-click transient responses require a quadrature phase, while the complex-tone steady-state responses require an antiphase relation. The MBPNL model simulations of all low-CF data surveyed,for simple and complex stimuli, are consistent with a quadrature phase for transient responses and antiphase relation for steady-state responses. It is hypothesized that some adaptive, low-CF, cochlear mechanism, not described by the basic MBPNL model, produces a temporal transition of the '2-factor' response from an initial quadrature relation (tip leading) to a final antiphase relation. New experimental and modeling research guided by this working hypothesis is proposed.

Spatiotemporal encoding of sound level: models for normal encoding and recruitment of loudness

This study explores the hypothesis that sound level is encoded in the spatiotemporal response patterns of auditory nerve (AN) fibers. The temporal properties of AN fiber responses depend upon sound level due to nonlinearities in the auditory periphery. In particular, the compressive nonlinearity of the inner ear introduces systematic changes in the timing of the responses of AN fibers as a function of level. Changes in single fiber responses that depend upon both sound level and characteristic frequency (CF) result in systematic changes in the spatiotemporal response patterns across populations of AN fibers. This study investigates the changes in the spatiotemporal response patterns as a function of level using a computational model for responses of low-frequency AN fibers. A mechanism that could extract information encoded in this form is coincidence detection across AN fibers of different CFs. This study shows that this mechanism could play a role in encoding of sound level for simple and complex stimuli. The model demonstrates that this encoding scheme would be influenced by auditory pathology that affects the peripheral compressive nonlinearity in a way that is consistent with the phenomenon of recruitment of loudness, which often accompanies sensorineural hearing loss.

The effects of temperature change and transient hypoxia on auditory nerve fiber response in the goldfish (Carassius auratus)

Temperature change and hypoxia produce consistent, reversible effects on the response of single auditory nerve fibers in the goldfish. Cooling and hypoxia produce reductions of a cell's spontaneous activity, sensitivity, most excitatory or best frequency (BF) at a given signal level, and overall responsiveness to acoustic stimulation. Warming above ambient temperatures increases a cell's spontaneous activity, sensitivity, BF, and responsiveness. Adaptation, or the tendency for responsiveness to decline with time during a stimulus, increases during hypoxia and cooling, and decreases during warming. The effects of temperature change and hypoxia on a fiber's BF are similar to the effects of overall sound level. Since BF normally increases with sound level, the BF-shift with temperature change and hypoxia can be understood as a change in sensitivity or the overall effectiveness of a stimulus at a given sound level. The effects on neural response of temperature change and hypoxia are probably due in part to changes in the release and replenishment of neurotransmitter at the synapses between hair cells and auditory nerve fibers.