Modeled auditory nerve responses to amplitude modulated cochlear implant stimulation

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.

A computational modelling framework for assessing information transmission with cochlear implants

Computational models are useful tools to investigate scientific questions that would be complicated to address using an experimental approach. In the context of cochlear-implants (CIs), being able to simulate the neural activity evoked by these devices could help in understanding their limitations to provide natural hearing. Here, we present a computational modelling framework to quantify the transmission of information from sound to spikes in the auditory nerve of a CI user. The framework includes a model to simulate the electrical current waveform sensed by each auditory nerve fiber (electrode-neuron interface), followed by a model to simulate the timing at which a nerve fiber spikes in response to a current waveform (auditory nerve fiber model). Information theory is then applied to determine the amount of information transmitted from a suitable reference signal (e.g., the acoustic stimulus) to a simulated population of auditory nerve fibers. As a use case example, the framework is applied to simulate published data on modulation detection by CI users obtained using direct stimulation via a single electrode. Current spread as well as the number of fibers were varied independently to illustrate the framework capabilities. Simulations reasonably matched experimental data and suggested that the encoded modulation information is proportional to the total neural response. They also suggested that amplitude modulation is well encoded in the auditory nerve for modulation rates up to 1000 Hz and that the variability in modulation sensitivity across CI users is partly because different CI users use different references for detecting modulation.

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 relation between polarity sensitivity and neural degeneration in a computational model of cochlear implant stimulation

The main aim of this computational modelling study was to test the validity of the hypothesis that sensitivity to the polarity of cochlear implant stimulation can be interpreted as a measure of neural health. For this purpose, the effects of stimulus polarity on neural excitation patterns were investigated in a volume conduction model of the implanted human cochlea, which was coupled with a deterministic active nerve fibre model based on characteristics of human auditory neurons. The nerve fibres were modelled in three stages of neural degeneration: intact, with shortened peripheral terminal nodes and with complete loss of the peripheral processes. The model simulated neural responses to monophasic, biphasic, triphasic and pseudomonophasic pulses of both polarities. Polarity sensitivity was quantified as the so-called polarity effect (PE), which is defined as the dB difference between cathodic and anodic thresholds. Results showed that anodic pulses mostly excited the auditory neurons in their central axons, while cathodic stimuli generally excited neurons in their peripheral processes or near their cell bodies. As a consequence, cathodic thresholds were more affected by neural degeneration than anodic thresholds. Neural degeneration did not have a consistent effect on the modelled PE values, though there were notable effects of electrode contact insertion angle and distance from the modiolus. Furthermore, determining PE values using charge-balanced multiphasic pulses as approximations of monophasic stimuli produced different results than those obtained with true monophasic pulses, at a degree that depended on the specific pulse shape; in general, pulses with lower secondary phase amplitudes showed polarity sensitivities closer to those obtained with true monophasic pulses. The main conclusion of this study is that polarity sensitivity is not a reliable indicator of neural health; neural degeneration affects simulated polarity sensitivity, but its effect is not consistently related to the degree of degeneration. Polarity sensitivity is not simply a product of the state of the neurons, but also depends on spatial factors.

A Fast Approximate Method for Predicting the Behavior of Auditory Nerve Fibers and the Evoked Compound Action Potential (ECAP) Signal

Background:

The goal of the current research is to develop a model based on computer simulations which describes both the behavior of the auditory nerve fibers and the cochlear implant system as a rehabilitation device.

Methods:

The approximate method was proposed as a low error and fast tool for predicting the behavior of auditory nerve fibers as well as the evoked compound action potential (ECAP) signal. In accurate methods every fiber is simulated; whereas, in approximate method information related to the response of every fiber and its characteristics such as the activation threshold of cochlear fibers are saved and interpolated to predict the behavior of a set of nerve fibers.

Results:

The approximate model can predict and analyze different stimulation techniques. Although precision is reduced to <1.66% of the accurate method, the required execution time for simulation is reduced by more than 98%.

Conclusion:

The amplitudes of the ECAP signal and the growth function were investigated by changing the parameters of the approximate model including geometrical parameters, electrical, and temporal parameters. In practice, an audiologist can tune the stimulation parameters to reach an effective restoration of the acoustic signal.

Short and long-term adaptation in the auditory nerve stimulated with high-rate electrical pulse trains are better described by a power law

Despite the introduction of many new sound-coding strategies speech perception outcomes in cochlear implant listeners have leveled off. Computer models may help speed up the evaluation of new sound-coding strategies, but most existing models of auditory nerve responses to electrical stimulation include limited temporal detail, as the effects of longer stimulation, such as adaptation, are not well-studied. Measured neural responses to stimulation with both short (400 ms) and long (10 min) duration high-rate (5kpps) pulse trains were compared in terms of spike rate and vector strength (VS) with model outcomes obtained with different forms of adaptation. A previously published model combining biophysical and phenomenological approaches was adjusted with adaptation modeled as a single decaying exponent, multiple exponents and a power law. For long duration data, power law adaptation by far outperforms the single exponent model, especially when it is optimized per fiber. For short duration data, all tested models performed comparably well, with slightly better performance of the single exponent model for VS and of the power law model for the spike rates. The power law parameter sets obtained when fitted to the long duration data also yielded adequate predictions for short duration stimulation, and vice versa. The power law function can be approximated with multiple exponents, which is physiologically more viable. The number of required exponents depends on the duration of simulation; the 400 ms data was well-replicated by two exponents (23 and 212 ms), whereas the 10-minute data required at least seven exponents (ranging from 4 ms to 600 s). Adaptation of the auditory nerve to high-rate electrical stimulation can best be described by a power-law or a sum of exponents. This gives an adequate fit for both short and long duration stimuli, such as CI speech segments.

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.

Effect of neural adaptation and degeneration on pulse-train ECAPs: A model study

Electrically evoked compound action potentials (eCAPs) are measurements of the auditory nerve's response to electrical stimulation. ECAP amplitudes during pulse trains can exhibit temporal alternations. The magnitude of this alternation tends to diminish over time during the stimulus. How this pattern relates to the temporal behavior of nerve fibers is not known. We hypothesized that the stochasticity, refractoriness, adaptation of the threshold and spike-times influence pulse-train eCAP responses. Thirty thousand auditory nerve fibers were modeled in a three-dimensional cochlear model incorporating pulse-shape effects, pulse-history effects, and stochasticity in the individual neural responses. ECAPs in response to pulse trains of different rates and amplitudes were modeled for fibers with different stochastic properties (by variation of the relative spread) and different temporal properties (by variation of the refractory periods, adaptation and latency). The model predicts alternation of peak amplitudes similar to available human data. In addition, the peak alternation was affected by changing the refractoriness, adaptation, and relative spread of auditory nerve fibers. As these parameters are related to factors such as the duration of deafness and neural survival, this study suggests that the eCAP pattern in response to pulse trains could be used to assess the underlying temporal and stochastic behavior of the auditory nerve. As these properties affect the nerve's response to pulse trains, they are of uttermost importance to sound perception with cochlear implants.

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.