A Computational Model of the Electrically or Acoustically Evoked Compound Action Potential in Cochlear Implant Users With Residual Hearing

OBJECTIVE

In cochlear implant users with residual acoustic hearing, compound action potentials (CAPs) can be evoked by acoustic (aCAP) or electric (eCAP) stimulation and recorded through the electrodes of the implant. We propose a novel computational model to simulate aCAPs and eCAPs in humans, considering the interaction between combined electric-acoustic stimulation that occurs in the auditory nerve.

METHODS

The model consists of three components: a 3D finite element method model of an implanted cochlea, a phenomenological single-neuron spiking model for electric-acoustic stimulation, and a physiological multi-compartment neuron model to simulate the individual nerve fiber contributions to the CAP.

RESULTS

The CAP morphologies closely resembled those known from humans. The spread of excitation derived from eCAPs by varying the recording electrode along the cochlear implant electrode array was consistent with published human data. The predicted CAP amplitude growth functions largely resembled human data, with deviations in absolute CAP amplitudes for acoustic stimulation. The model reproduced the suppression of eCAPs by simultaneously presented acoustic tone bursts for different masker frequencies and probe stimulation electrodes.

CONCLUSION

The proposed model can simulate CAP responses to electric, acoustic, or combined electric-acoustic stimulation. It considers the dependence on stimulation and recording sites in the cochlea, as well as the interaction between electric and acoustic stimulation in the auditory nerve.

SIGNIFICANCE

The model enhances comprehension of CAPs and peripheral electric-acoustic interaction. It can be used in the future to investigate objective methods, such as hearing threshold assessment or estimation of neural health through aCAPs or eCAPs.

Biophysics-inspired spike rate adaptation for computationally efficient phenomenological nerve modeling

This study introduces and evaluates the PHAST+ model, part of a computational framework designed to simulate the behavior of auditory nerve fibers in response to the electrical stimulation from a cochlear implant. PHAST+ incorporates a highly efficient method for calculating accommodation and adaptation, making it particularly suited for simulations over extended stimulus durations. The proposed method uses a leaky integrator inspired by classic biophysical nerve models. Through evaluation against single-fiber animal data, our findings demonstrate the model's effectiveness across various stimuli, including short pulse trains with variable amplitudes and rates. Notably, the PHAST+ model performs better than its predecessor, PHAST (a phenomenological model by van Gendt et al.), particularly in simulations of prolonged neural responses. While PHAST+ is optimized primarily on spike rate decay, it shows good behavior on several other neural measures, such as vector strength and degree of adaptation. The future implications of this research are promising. PHAST+ drastically reduces the computational burden to allow the real-time simulation of neural behavior over extended periods, opening the door to future simulations of psychophysical experiments and multi-electrode stimuli for evaluating novel speech-coding strategies for cochlear implants.

An Adaptive Leaky-Integrate and Firing Probability Model of an Electrically Stimulated Auditory Nerve Fiber

Most neural models produce a spiking output and often represent the stochastic nature of the spike generation process via a stochastic output. Nonspiking neural models, on the other hand, predict the probability of a spike occurring in response to a stimulus. We propose a nonspiking model for an electrically stimulated auditory nerve fiber, which not only predicts the total probability of a spike occurring in response to a biphasic pulse but also the distribution of the spike time. Our adaptive leaky-integrate and firing probability (aLIFP) model can account for refractoriness, facilitation, accommodation, and long-term adaptation. All model parameters have been fitted to single cell recordings from electrically stimulated cat auditory nerve fibers. Afterward, the model was validated on recordings from auditory nerve fibers from cats and guinea pigs. The nonspiking nature of the model makes it fast and deterministic while still accounting for the stochastic nature of the spike generation process. Therefore, the relationship between the input to the model or model parameters and the model's output can be observed more directly than with stochastically spiking models.

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.

What Is the Benefit of Ramped Pulse Shapes for Activating Auditory Cortex Neurons? An Electrophysiological Study in an Animal Model of Cochlear Implant

In all commercial cochlear implant (CI) devices, the activation of auditory nerve fibers is performed with rectangular pulses that have two phases of opposite polarity. Recently, several papers proposed that ramped pulse shapes could be an alternative shape for efficiently activating auditory nerve fibers. Here, we investigate whether ramped pulse shapes can activate auditory cortex (ACx) neurons in a more efficient way than the classical rectangular pulses. Guinea pigs were implanted with CI devices and responses of ACx neurons were tested with rectangular pulses and with four ramped pulse shapes, with a first-phase being either cathodic or anodic. The thresholds, i.e., the charge level necessary for obtaining significant cortical responses, were almost systematically lower with ramped pulses than with rectangular pulses. The maximal firing rate (FR) elicited by the ramped pulses was higher than with rectangular pulses. As the maximal FR occurred with lower charge levels, the dynamic range (between threshold and the maximal FR) was not modified. These effects were obtained with cathodic and anodic ramped pulses. By reducing the charge levels required to activate ACx neurons, the ramped pulse shapes should reduce charge consumption and should contribute to more battery-efficient CI devices in the future.

A Computational Model of a Single Auditory Nerve Fiber for Electric-Acoustic Stimulation

Cochlear implant (CI) recipients with preserved acoustic low-frequency hearing in the implanted ear are a growing group among traditional CI users who benefit from hybrid electric-acoustic stimulation (EAS). However, combined ipsilateral electric and acoustic stimulation also introduces interactions between the two modalities that can affect the performance of EAS users. A computational model of a single auditory nerve fiber that is excited by EAS was developed to study the interaction between electric and acoustic stimulation. Two existing models of sole electric or acoustic stimulation were coupled to simulate responses to combined EAS. Different methods of combining both models were implemented. In the coupled model variant, the refractoriness of the simulated fiber leads to suppressive interaction between electrically evoked and acoustically evoked spikes as well as spontaneous activity. The second model variant is an uncoupled EAS model without electric-acoustic interaction. By comparing predictions between the coupled and the noninteracting EAS model, it was possible to infer electric-acoustic interaction at the level of the auditory nerve. The EAS model was used to simulate fiber populations with realistic inter-unit variability, where each unit was represented by the single-fiber model. Predicted thresholds and dynamic ranges, spike rates, latencies, jitter, and vector strengths were compared to empirical data. The presented EAS model provides a framework for future studies of peripheral electric-acoustic interaction.

Comparison of response properties of the electrically stimulated auditory nerve reported in human listeners and in animal models

Cochlear implants (CIs) provide acoustic information to implanted patients by electrically stimulating nearby auditory nerve fibers (ANFs) which then transmit the information to higher-level neural structures for further processing and interpretation. Computational models that simulate ANF responses to CI stimuli enable the exploration of the mechanisms underlying CI performance beyond the capacity of in vivo experimentation alone. However, all ANF models developed to date utilize to some extent anatomical/morphometric data, biophysical properties and/or physiological data measured in non-human animal models. This review compares response properties of the electrically stimulated auditory nerve (AN) in human listeners and different mammalian models. Properties of AN responses to single pulse stimulation, paired-pulse stimulation, and pulse-train stimulation are presented. While some AN response properties are similar between human listeners and animal models (e.g., increased AN sensitivity to single pulse stimuli with long interphase gaps), there are some significant differences. For example, the AN of most animal models is typically more sensitive to cathodic stimulation while the AN of human listeners is generally more sensitive to anodic stimulation. Additionally, there are substantial differences in the speed of recovery from neural adaptation between animal models and human listeners. Therefore, results from animal models cannot be simply translated to human listeners. Recognizing the differences in responses of the AN to electrical stimulation between humans and other mammals is an important step for creating ANF models that are more applicable to various human CI patient populations.

A Phenomenological Model Reproducing Temporal Response Characteristics of an Electrically Stimulated Auditory Nerve Fiber

The ability of cochlear implants (CIs) to restore hearing to profoundly deaf people is based on direct electrical stimulation of the auditory nerve fibers (ANFs). Still, CI users do not achieve as good hearing outcomes as their normal-hearing peers. The development and optimization of CI stimulation strategies to reduce that gap could benefit from computational models that can predict responses evoked by different stimulation patterns, particularly temporal responses for coding of temporal fine structure information. To that end, we present the sequential biphasic leaky integrate-and-fire (S-BLIF) model for the ANF response to various pulse shapes and temporal sequences. The phenomenological S-BLIF model is adapted from the earlier BLIF model that can reproduce neurophysiological single-fiber cat ANF data from single-pulse stimulations. It was extended with elements that simulate refractoriness, facilitation, accommodation and long-term adaptation by affecting the threshold value of the model momentarily after supra- and subthreshold stimulation. Evaluation of the model demonstrated that it can reproduce neurophysiological data from single neuron recordings involving temporal phenomena related to inter-pulse interactions. Specifically, data for refractoriness, facilitation, accommodation and spike-rate adaptation can be reproduced. In addition, the model can account for effects of pulse rate on the synchrony between the pulsatile input and the spike-train output. Consequently, the model offers a versatile tool for testing new coding strategies for, e.g., temporal fine structure using pseudo-monophasic pulses, and for estimating the status of the electrode-neuron interface in the CI user's cochlea.

The Perception of Ramped Pulse Shapes in Cochlear Implant Users

The electric stimulation provided by current cochlear implants (CI) is not power efficient. One underlying problem is the poor efficiency by which information from electric pulses is transformed into auditory nerve responses. A novel stimulation paradigm using ramped pulse shapes has recently been proposed to remedy this inefficiency. The primary motivation is a better biophysical fit to spiral ganglion neurons with ramped pulses compared to the rectangular pulses used in most contemporary CIs. Here, we tested the hypotheses that ramped pulses provide more efficient stimulation compared to rectangular pulses and that a rising ramp is more efficient than a declining ramp. Rectangular, rising ramped and declining ramped pulse shapes were compared in terms of charge efficiency and discriminability, and threshold variability in seven CI listeners. The tasks included single-channel threshold detection, loudness-balancing, discrimination of pulse shapes, and threshold measurement across the electrode array. Results showed that reduced charge, but increased peak current amplitudes, was required at threshold and most comfortable levels with ramped pulses relative to rectangular pulses. Furthermore, only one subject could reliably discriminate between equally-loud ramped and rectangular pulses, suggesting variations in neural activation patterns between pulse shapes in that participant. No significant difference was found between rising and declining ramped pulses across all tests. In summary, the present findings show some benefits of charge efficiency with ramped pulses relative to rectangular pulses, that the direction of a ramped slope is of less importance, and that most participants could not perceive a difference between pulse shapes.

Spike-rate adaptation in a computational model of human-shaped spiral ganglion neurons

OBJECTIVES

The purpose of this study is to develop a biophysical model of human spiral ganglion neurons (SGNs) that includes voltage-gated hyperpolarization-activated cation (HCN) channels and low-threshold potassium voltage-gated, delayed-rectifier low-threshold potassium (KLT) channels, providing for a more complete simulation of spike-rate adaptation, a feature of most spiking neurons in which spiking activity is reduced in response to sustained stimulation.

METHODS

Our model incorporates features of spike-rate adaptation reported from in vivo studies, whilst also displaying similar behaviour to existing models of human SGNs, including the dependence of electrically evoked thresholds on the polarity of electrical pulses.

RESULTS

Hypothesizing that the mode of stimulation intracellular or extracellular predicts features of spike-rate adaptation similar to in vivo studies, including the influence of stimulus intensity and pulse-rate, we find that the mode of stimulation alters features of spike-rate adaptation. In particular, the reduction in spiking over time with sustained input was generally greater for extracellular, compared to intracellular, stimulation, when simulating a multi-compartment SGN with human morphological features. In contrast, time-constants of spike-rate adaption reported for in vivo data did not fit our predicted responses, highlighting the need for a more complete physiological understanding of the factors contributing to spike-rate adaptation in electrically stimulated human SGNs.

CONCLUSION

Our model extends previous computational models of SGNs with human morphology with ionic channels accounting for features of spike-rate adaptation.

SIGNIFICANCE

The significance of this work resides in the ability to improve the modeling of cochlear implant (CI) stimulation and its effects on neural responses. This will help develop novel, and perhaps personalised, stimulation strategies to reduce variability in CI user outcomes.

Phenomenological model of auditory nerve population responses to cochlear implant stimulation

BACKGROUND

Models of auditory nerve fiber (ANF) responses to electrical stimulation are helpful to develop advanced coding for cochlear implants (CIs). A phenomenological model of ANF population responses to CI electrical stimulation with a lower computational complexity compared to a biophysical model would be beneficial to evaluate new CI coding strategies.

NEW METHOD

This study presents a phenomenological model which combines four temporal characteristics of ANFs (refractoriness, facilitation, accommodation and spike rate adaptation) in addition to a spatial spread of the electric field.

RESULTS

The model predicts the performances of CI subjects in the melodic contour identification (MCI) experiment. The simulations for the MCI experiment were consistent with CI recipients' experimental outcomes that were not predictable from the electrical stimulation patterns themselves.

COMPARISON WITH EXISTING METHODS

Previously, no phenomenological population model of ANFs has combined all four aforementioned temporal phenomena.

CONCLUSIONS

The proposed model would help the further investigations of ANFs responses to different electrical stimulation patterns and comparison of different sound coding strategies in CIs.

Kilohertz-frequency stimulation of the nervous system: A review of underlying mechanisms

BACKGROUND

Electrical stimulation in the kilohertz-frequency range has gained interest in the field of neuroscience. The mechanisms underlying stimulation in this frequency range, however, are poorly characterized to date.

OBJECTIVE/HYPOTHESIS

To summarize the manifold biological effects elicited by kilohertz-frequency stimulation in the context of the currently existing literature and provide a mechanistic framework for the neural responses observed in this frequency range.

METHODS

A comprehensive search of the peer-reviewed literature was conducted across electronic databases. Relevant computational, clinical, and mechanistic studies were selected for review.

RESULTS

The effects of kilohertz-frequency stimulation on neural tissue are diverse and yield effects that are distinct from conventional stimulation. Broadly, these can be divided into 1) subthreshold, 2) suprathreshold, 3) synaptic and 4) thermal effects. While facilitation is the dominating mechanism at the subthreshold level, desynchronization, spike-rate adaptation, conduction block, and non-monotonic activation can be observed during suprathreshold kilohertz-frequency stimulation. At the synaptic level, kilohertz-frequency stimulation has been associated with the transient depletion of the available neurotransmitter pool - also known as synaptic fatigue. Finally, thermal effects associated with extrinsic (environmental) and intrinsic (associated with kilohertz-frequency stimulation) temperature changes have been suggested to alter the neural response to stimulation paradigms.

CONCLUSION

The diverse spectrum of neural responses to stimulation in the kilohertz-frequency range is distinct from that associated with conventional stimulation. This offers the potential for new therapeutic avenues across stimulation modalities. However, stimulation in the kilohertz-frequency range is associated with distinct challenges and caveats that need to be considered in experimental paradigms.

Dendritic Degeneration of Human Auditory Nerve Fibers and Its Impact on the Spiking Pattern Under Regular Conditions and During Cochlear Implant Stimulation

Due to limitations of human in vivo studies, detailed computational models enable understanding the neural signaling in the degenerated auditory system and cochlear implants (CIs). Four human cochleae were used to quantify hearing levels depending on dendritic changes in diameter and myelination thickness from type I of the auditory nerve fibers (ANFs). Type I neurons transmit the auditory information as spiking pattern from the inner hair cells (IHCs) to the cochlear nucleus. The impact of dendrite diameter and degree of myelination on neural signal transmission was simulated for (1) synaptic excitation via IHCs and (2) stimulation from CI electrodes. An accurate three-dimensional human cochlear geometry, along with 30 auditory pathways, mimicked the CI environment. The excitation properties of electrical potential distribution induced by two CI were analyzed. Main findings: (1) The unimodal distribution of control dendrite diameters becomes multimodal for hearing loss cases; a group of thin dendrites with diameters between 0.3 and 1 μm with a peak at 0.5 μm appeared. (2) Postsynaptic currents from IHCs excite such thin dendrites easier and earlier than under control conditions. However, this advantage is lost as their conduction velocity decreases proportionally with the diameter and causes increased spike latency and jitter in soma and axon. Firing probability reduces through the soma passage due to the low intracellular current flow in thin dendrites during spiking. (3) Compared with dendrite diameter, variations in myelin thickness have a small impact on spiking performance. (4) Contrary to synaptic excitation, CIs cause several spike initiation sites in dendrite, soma region, and axon; moreover, fiber excitability reduces with fiber diameter. In a few cases, where weak stimuli elicit spikes of a target neuron (TN) in the axon, dendrite diameter reduction has no effect. However, in many cases, a spike in a TN is first initiated in the dendrite, and consequently, dendrite degeneration demands an increase in threshold currents. (5) Threshold currents of a TN and co-stimulation of degenerated ANFs in other frequency regions depend on the electrode position, including its distance to the outer wall, the cochlear turn, and the three-dimensional pathway of the TN.

HCN channels in the mammalian cochlea: Expression pattern, subcellular location, and age-dependent changes

Neuronal diversity in the cochlea is largely determined by ion channels. Among voltage‐gated channels, hyperpolarization‐activated cyclic nucleotide‐gated (HCN) channels open with hyperpolarization and depolarize the cell until the resting membrane potential. The functions for hearing are not well elucidated and knowledge about localization is controversial. We created a detailed map of subcellular location and co‐expression of all four HCN subunits across different mammalian species including CBA/J, C57Bl/6N, Ly5.1 mice, guinea pigs, cats, and human subjects. We correlated age‐related hearing deterioration in CBA/J and C57Bl/6N with expression levels of HCN1, −2, and −4 in individual auditory neurons from the same cohort. Spatiotemporal expression during murine postnatal development exposed HCN2 and HCN4 involvement in a critical phase of hair cell innervation. The huge diversity of subunit composition, but lack of relevant heteromeric pairing along the perisomatic membrane and axon initial segments, highlighted an active role for auditory neurons. Neuron clusters were found to be the hot spots of HCN1, −2, and −4 immunostaining. HCN channels were also located in afferent and efferent fibers of the sensory epithelium. Age‐related changes on HCN subtype expression were not uniform among mice and could not be directly correlated with audiometric data. The oldest mice groups revealed HCN channel up‐ or downregulation, depending on the mouse strain. The unexpected involvement of HCN channels in outer hair cell function where HCN3 overlaps prestin location emphasized the importance for auditory function. A better understanding may open up new possibilities to tune neuronal responses evoked through electrical stimulation by cochlear implants.

Effect of pulse phase duration on forward masking and spread of excitation in cochlear implant listeners

Previous cochlear implant (CI) research has shown that at a pulse train with a long pulse phase duration (PPD) requires less current but greater charge to obtain the same loudness as a pulse train with a short PPD. This might result in different excitation patterns between long and short PPDs. At equal loudness, long PPDs might produce greater masking due to greater charge. However, because they require less current, long PPDs may produce a smaller spatial spread of excitation (SOE) compared to short PPDs by evoking a greater neural firing probability within the relatively small current field. To investigate the effects of PPD on excitation patterns, overall masking and SOE were compared for equally loud stimuli with short or long PPD in 10 adult CI ears. Forward masking patterns were measured at relatively soft, medium, and loud presentation levels. Threshold shifts were calculated in terms of percent dynamic range (DR) of the probe. The area under the curve (AUC) of the masking functions was significantly larger for the long PPD than for the short PPD masker. The difference in AUC was proportional to the difference in charge between the short and long PPD maskers. To estimate SOE, the masking patterns were first normalized to the peak masking, and then AUC was calculated. SOE was significantly larger for the short PPD than for the long PPD masker. Thus, at equal loudness, long PPDs produced greater overall masking (possibly due to greater charge) but less SOE (possibly due to less current spread) than did short PPDs. The effect of the interaction between masking and SOE by long PPD stimulation remains to be tested.

Ramped pulse shapes are more efficient for cochlear implant stimulation in an animal model

In all commercial cochlear implant (CI) devices, the electric stimulation is performed with a rectangular pulse that generally has two phases of opposite polarity. To date, developing new stimulation strategies has relied on the efficacy of this shape. Here, we investigate the potential of a novel stimulation paradigm that uses biophysically-inspired electrical ramped pulses. Using electrically-evoked auditory brainstem response (eABR) recordings in mice, we found that less charge, but higher current level amplitude, is needed to evoke responses with ramped shapes that are similar in amplitude to responses obtained with rectangular shapes. The most charge-efficient pulse shape had a rising ramp over both phases, supporting findings from previous in vitro studies. This was also true for longer phase durations. Our study presents the first physiological data on CI-stimulation with ramped pulse shapes. By reducing charge consumption ramped pulses have the potential to produce more battery-efficient CIs and may open new perspectives for designing other efficient neural implants in the future.

Comparison of Multi-Compartment Cable Models of Human Auditory Nerve Fibers

Background: Multi-compartment cable models of auditory nerve fibers have been developed to assist in the improvement of cochlear implants. With the advancement of computational technology and the results obtained from in vivo and in vitro experiments, these models have evolved to incorporate a considerable degree of morphological and physiological details. They have also been combined with three-dimensional volume conduction models of the cochlea to simulate neural responses to electrical stimulation. However, no specific rules have been provided on choosing the appropriate cable model, and most models adopted in recent studies were chosen without a specific reason or by inheritance. Methods: Three of the most cited biophysical multi-compartment cable models of the human auditory nerve, i.e., Rattay et al. (2001b), Briaire and Frijns (2005), and Smit et al. (2010), were implemented in this study. Several properties of single fibers were compared among the three models, including threshold, conduction velocity, action potential shape, latency, refractory properties, as well as stochastic and temporal behaviors. Experimental results regarding these properties were also included as a reference for comparison. Results: For monophasic single-pulse stimulation, the ratio of anodic vs. cathodic thresholds in all models was within the experimental range despite a much larger ratio in the model by Briaire and Frijns. For biphasic pulse-train stimulation, thresholds as a function of both pulse rate and pulse duration differed between the models, but none matched the experimental observations even coarsely. Similarly, for all other properties including the conduction velocity, action potential shape, and latency, the models presented different outcomes and not all of them fell within the range observed in experiments. Conclusions: While all three models presented similar values in certain single fiber properties to those obtained in experiments, none matched all experimental observations satisfactorily. In particular, the adaptation and temporal integration behaviors were completely missing in all models. Further extensions and analyses are required to explain and simulate realistic auditory nerve fiber responses to electrical stimulation.

Spike-Conducting Integrate-and-Fire Model

Modeling is a useful tool for investigating various biophysical characteristics of neurons. Recent simulation studies of propagating action potentials (spike conduction) along axons include the investigation of neuronal activity evoked by electrical stimulation from implantable prosthetic devices. In contrast to point-neuron simulations, where a large variety of models are readily available, Hodgkin–Huxley-type conductance-based models have been almost the only option for simulating axonal spike conduction, as simpler models cannot faithfully replicate the waveforms of propagating spikes. Since the amount of available physiological data, especially in humans, is usually limited, calibration, and justification of the large number of parameters of a complex model is generally difficult. In addition, not all simulation studies of axons require detailed descriptions of nonlinear ionic dynamics. In this study, we construct a simple model of spike generation and conduction based on the exponential integrate-and-fire model, which can simulate the rapid growth of the membrane potential at spike initiation. In terms of the number of parameters and equations, this model is much more compact than conventional models, but can still reliably simulate spike conduction along myelinated and unmyelinated axons that are stimulated intracellularly or extracellularly. Our simulations of auditory nerve fibers with this new model suggest that, because of the difference in intrinsic membrane properties, the axonal spike conduction of high-frequency nerve fibers is faster than that of low-frequency fibers. The simple model developed in this study can serve as a computationally efficient alternative to more complex models for future studies, including simulations of neuroprosthetic devices.

Simulated auditory nerve axon demyelination alters sensitivity and response timing to extracellular stimulation

Since cochlear implant function involves direct depolarization of spiral ganglion neurons (SGNs) by applied current, SGN physiological health must be an important factor in cochlear implant (CI) outcomes. This expected relationship has, however, been difficult to confirm in implant recipients. Suggestively, animal studies have demonstrated both acute and progressive SGN ultrastructural changes (notably axon demyelination), even in the absence of soma death, and corresponding altered physiology following sensorineural deafening. Whether such demyelination occurs in humans and how such changes might impact CI function remains unknown. To approach this problem, we incorporated SGN demyelination into a biophysical model of extracellular stimulation of SGN fibers. Our approach enabled exploration of the entire parameter space corresponding to simulated myelin diameter and extent of fiber affected. All simulated fibers were stimulated distally with anodic monophasic, cathodic monophasic, anode-phase-first (AF) biphasic, and cathode-phase-first (CF) biphasic pulses from an extracellular disc electrode and monitored for spikes centrally. Not surprisingly, axon sensitivity generally decreased with demyelination, resulting in elevated thresholds, however, this effect was strongly non-uniform. Fibers with severe demyelination affecting only the most peripheral nodes responded nearly identically to normally myelinated fibers. Additionally, partial demyelination (<50%) yielded only minimal increases in threshold even when the entire fiber was impacted. The temporal effects of demyelination were more unexpected. Both latency and jitter of responses demonstrated resilience to modest changes but exhibited strongly non-monotonic and stimulus-dependent relationships to more profound demyelination. Normal, and modestly demyelinated fibers, were more sensitive to cathodic than anodic monophasic pulses and to CF than AF biphasic pulses, however, when demyelination was more severe these relative sensitivities were reversed. Comparison of threshold crossing between nodal segments demonstrated stimulus-dependent shifts in action potential initiation with different fiber demyelination states. For some demyelination scenarios, both phases of biphasic pulses could initiate action potentials at threshold resulting in bimodal latency and initiation site distributions and dramatically increased jitter. In summary, simulated demyelination leads to complex changes in fiber sensitivity and spike timing, mediated by alterations in action potential initiation site and slowed action potential conduction due to non-uniformities in the electrical properties of axons. Such demyelination-induced changes, if present in implantees, would have profound implications for the detection of fine temporal cues but not disrupt cues on the time scale of speech envelopes. These simulation results highlight the importance of exploring the SGN ultrastructural changes caused by a given etiology of hearing loss to more accurately predict cochlear implantation outcomes.

Analysis of a purely conductance-based stochastic nerve fibre model as applied to compound models of populations of human auditory nerve fibres used in cochlear implant simulations

The study presents the application of a purely conductance-based stochastic nerve fibre model to human auditory nerve fibres within finite element volume conduction models of a semi-generic head and user-specific cochleae. The stochastic, threshold and temporal characteristics of the human model are compared and successfully validated against physiological feline results with the application of a mono-polar, bi-phasic, cathodic first stimulus. Stochastic characteristics validated include: (i) the log(Relative Spread) versus log(fibre diameter) distribution for the discharge probability versus stimulus intensity plots and (ii) the required exponential membrane noise versus transmembrane voltage distribution. Intra-user, and to a lesser degree inter-user, comparisons are made with respect to threshold and dynamic range at short and long pulse widths for full versus degenerate single fibres as well as for populations of degenerate fibres of a single user having distributed and aligned somas with varying and equal diameters. Temporal characteristics validated through application of different stimulus pulse rates and different stimulus intensities include: (i) discharge rate, latency and latency standard deviation versus stimulus intensity, (ii) period histograms and (iii) interspike interval histograms. Although the stochastic population model does not reduce the modelled single deterministic fibre threshold, the simulated stochastic and temporal characteristics show that it could be used in future studies to model user-specific temporally encoded information, which influences the speech perception of CI users.

A Model of Electrically Stimulated Auditory Nerve Fiber Responses with Peripheral and Central Sites of Spike Generation

A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike. A single ANF is modeled as a network of two exponential integrate-and-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects of facilitation, accommodation, refractoriness, and spike-rate adaptation in ANF. Although the model is parameterized using data for either single or paired pulse stimulation with monophasic rectangular pulses, it correctly predicts effects of various stimulus pulse shapes, stimulation pulse rates, and level on the neural response statistics. The model may serve as a framework to explore the effects of different stimulus parameters on psychophysical performance measured in cochlear implant listeners.

Predictions of the Contribution of HCN Half-Maximal Activation Potential Heterogeneity to Variability in Intrinsic Adaptation of Spiral Ganglion Neurons

Spiral ganglion neurons (SGNs) exhibit a wide range in their strength of intrinsic adaptation on a timescale of 10s to 100s of milliseconds in response to electrical stimulation from a cochlear implant (CI). The purpose of this study was to determine how much of that variability could be caused by the heterogeneity in half-maximal activation potentials of hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channels, which are known to produce intrinsic adaptation. In this study, a computational membrane model of cat type I SGN was developed based on the Hodgkin-Huxley model plus HCN and low-threshold potassium (KLT) conductances in which the half-maximal activation potential of the HCN channel was varied and the response of the SGN to pulse train and paired-pulse stimulation was simulated. Physiologically plausible variation of HCN half-maximal activation potentials could indeed determine the range of adaptation on the timescale of 10s to 100s of milliseconds and recovery from adaptation seen in the physiological data while maintaining refractoriness within physiological bounds. This computational model demonstrates that HCN channels may play an important role in regulating the degree of adaptation in response to pulse train stimulation and therefore contribute to variable constraints on acoustic information coding by CIs. This finding has broad implications for CI stimulation paradigms in that cell-to-cell variation of HCN channel properties are likely to significantly alter SGN excitability and therefore auditory perception.

Temporal Considerations for Stimulating Spiral Ganglion Neurons with Cochlear Implants

A wealth of knowledge about different types of neural responses to electrical stimulation has been developed over the past 100 years. However, the exact forms of neural response properties can vary across different types of neurons. In this review, we survey four stimulus-response phenomena that in recent years are thought to be relevant for cochlear implant stimulation of spiral ganglion neurons (SGNs): refractoriness, facilitation, accommodation, and spike rate adaptation. Of these four, refractoriness is the most widely known, and many perceptual and physiological studies interpret their data in terms of refractoriness without incorporating facilitation, accommodation, or spike rate adaptation. In reality, several or all of these behaviors are likely involved in shaping neural responses, particularly at higher stimulation rates. A better understanding of the individual and combined effects of these phenomena could assist in developing improved cochlear implant stimulation strategies. We review the published physiological data for electrical stimulation of SGNs that explores these four different phenomena, as well as some of the recent studies that might reveal the biophysical bases of these stimulus-response phenomena.

Enhancing speech envelope by integrating hair-cell adaptation into cochlear implant processing

Cochlear implants (CIs) bypass some of the mechanisms that underlie normal neural behavior as occurs in acoustic hearing. One such neural mechanism is short-term adaptation, which has been proposed to have a significant role in speech perception. Acoustically-evoked neural adaptation has been mainly attributed to the depletion of neurotransmitter in the hair-cell to auditory-nerve synapse and is therefore not fully present in CI stimulation. This study evaluated a signal processing method that integrated a physiological model of hair-cell adaptation into CI speech processing. The linear high-pass adaptation process expanded the range of rapid variations of the electrical signal generated by the clinical processing strategy. Speech perception performance with the adaptation-based processing was compared to that of the clinical strategy in seven CI users. While there was large variability across subjects, the new processing improved sentence recognition and consonant identification scores in quiet in all the tested subjects with an average improvement of 8% and 6% respectively. Consonant recognition scores in babble noise were improved at the higher signal-to-noise ratios tested (10 and 6 dB) only. Information transfer analysis of consonant features showed significant improvements for manner and place of articulation features, but not for voicing. Enhancement of within-channel envelope cues was confirmed by consonant recognition results obtained with single-channel strategies that presented the overall amplitude envelope of the signal on a single active electrode. Adaptation-inspired envelope enhancement techniques can potentially improve perception of important speech features by CI users.

Maturation of NaV and KV Channel Topographies in the Auditory Nerve Spike Initiator before and after Developmental Onset of Hearing Function

Auditory nerve excitation and thus hearing depend on spike-generating ion channels and their placement along the axons of auditory nerve fibers (ANFs). The developmental expression patterns and native axonal locations of voltage-gated ion channels in ANFs are unknown. Therefore, we examined the development of heminodes and nodes of Ranvier in the peripheral axons of type I ANFs in the rat cochlea with immunohistochemistry and confocal microscopy. Nodal structures presumably supporting presensory spiking formed between postnatal days 5 (P5) and P7, including Ankyrin-G, NaV1.6, and Caspr. These immature nodal structures lacked low-voltage-activated KV1.1 which was not enriched at juxtaparanodes until approximately P13, concurrent with the developmental onset of acoustic hearing function. Anatomical alignment of ANF spike-initiating heminodes relative to excitatory input from inner hair cell (IHC) ribbon synapses continued until approximately P30. High-voltage-activated KV3.1b and KV2.2 were expressed in mutually exclusive domains: KV3.1b was strictly localized to nodes and heminodes, whereas KV2.2 expression began at the juxtaparanodes and continued centrally along the first internode. At spike-initiating heminodes in the distal osseous spiral lamina, NaV1.1 partly overlapped NaV1.6 and ankyrin-G. ANFs displayed KV7.2 and KV7.3 at heminodes, nodes, internodes, and the unmyelinated synaptic terminal segments beneath IHCs in the organ of Corti. In response to sound, spikes are initiated at the heminode, which is tightly coupled to the IHC ribbon synapse ∼20-40 μm away. These results show that maturation of nodal alignment and ion channel content may underlie postnatal improvements of ANF excitability and discharge synchrony.

SIGNIFICANCE STATEMENT

Acoustic and electrical hearing depends on rapid, reliable, and precise spike generation in auditory nerve fibers. A limitation of current models and therapies is a lack of information on the identities and topographies of underlying ion channels. We report the developmental profile of the auditory nerve spike generator with a focus on NaV1.1, NaV1.6, KV1.1, KV2.2, KV3.1b, KV7.2, and KV7.3 in relation to the scaffold ankyrin-G. Molecular anatomy of the spike generator matures in the weeks after developmental onset of hearing function. Subcellular positioning of voltage-gated ion channels will enable multicompartmental modeling of auditory nerve responses elicited by afferent chemical neurotransmission from hair cells and modulated by efferent neurotransmitters or evoked by extracellular field stimulation from a cochlear implant.

A neural-based vocoder implementation for evaluating cochlear implant coding strategies

Most simulations of cochlear implant (CI) coding strategies rely on standard vocoders that are based on purely signal processing techniques. However, these models neither account for various biophysical phenomena, such as neural stochasticity and refractoriness, nor for effects of electrical stimulation, such as spectral smearing as a function of stimulus intensity. In this paper, a neural model that accounts for stochastic firing, parasitic spread of excitation across neuron populations, and neuronal refractoriness, was developed and augmented as a preprocessing stage for a standard 22-channel noise-band vocoder. This model was used to subjectively and objectively assess consonant discrimination in commercial and experimental coding strategies. Stimuli consisting of consonant-vowel (CV) and vowel-consonant-vowel (VCV) tokens were processed by either the Advanced Combination Encoder (ACE) or the Excitability Controlled Coding (ECC) strategies, and later resynthesized to audio using the aforementioned vocoder model. Baseline performance was measured using unprocessed versions of the speech tokens. Behavioural responses were collected from seven normal hearing (NH) volunteers, while EEG data were recorded from five NH participants. Psychophysical results indicate that while there may be a difference in consonant perception between the two tested coding strategies, mismatch negativity (MMN) waveforms do not show any marked trends in CV or VCV contrast discrimination.

The history and future of neural modeling for cochlear implants

This special issue of Network: Computation in Neural Systems on the topic of "Computational models of the electrically stimulated auditory system" incorporates review articles spanning a wide range of approaches to modeling cochlear implant stimulation of the auditory system. The purpose of this overview paper is to provide a historical context for the different modeling endeavors and to point toward how computational modeling could play a key role in the understanding, evaluation, and improvement of cochlear implants in the future.

A phenomenological model of myelinated nerve with a dynamic threshold

To evaluate coding strategies for cochlear implants a model of the human cochlear nerve is required. Nerve models based on voltage-clamp experiments, such as the Frankenhaeuser-Huxley model of myelinated nerve, can have over forty parameters and are not amenable for fitting to physiological data from a different animal or type of nerve. Phenomenological nerve models, such as leaky integrate-and-fire (LIF) models, have fewer parameters but have not been validated with a wide range of stimuli. In the absence of substantial cochlear nerve data, we have used data from a toad sciatic nerve for validation (50 Hz to 2 kHz with levels up to 20 dB above threshold). We show that the standard LIF model with fixed refractory properties and a single set of parameters cannot adequately predict the toad rate-level functions. Given the deficiency of this standard model, we have abstracted the dynamics of the sodium inactivation variable in the Frankenhaeuser-Huxley model to develop a phenomenological LIF model with a dynamic threshold. This nine-parameter model predicts the physiological rate-level functions much more accurately than the standard LIF model. Because of the low number of parameters, we expect to be able to optimize the model parameters so that the model is more appropriate for cochlear implant simulations.