A computational loudness model for electrical stimulation with cochlear implants

Cochlear implants (CIs) are devices that restore the sense of hearing in people with severe sensorineural hearing loss. An electrode array inserted in the cochlea bypasses the natural transducer mechanism that transforms mechanical sound waves into neural activity by artificially stimulating the auditory nerve fibers with electrical pulses. The perception of sounds is possible because the brain extracts features from this neural activity, and loudness is among the most fundamental perceptual features. A computational model that uses a three-dimensional (3D) representation of the peripheral auditory system of CI users was developed to predict categorical loudness from the simulated peripheral neural activity. In contrast, current state-of-the-art computational loudness models predict loudness from the electrical pulses with minimal parametrization of the electrode-nerve interface. In the proposed model, the spikes produced in a population of auditory nerve fibers were grouped by cochlear places, a physiological representation of the auditory filters in psychoacoustics, to be transformed into loudness contribution. Then, a loudness index was obtained with a spatiotemporal integration over this loudness contribution. This index served to define the simulated threshold of hearing (THL) and most comfortable loudness (MCL) levels resembling the growth function in CI users. The performance of real CI users in loudness summation experiments was also used to validate the computational model. These experiments studied the effect of stimulation rate, electrode separation and amplitude modulation. The proposed model provides a new set of perceptual features that can be used in computational frameworks for CIs and narrows the gap between simulations and the human peripheral neural activity.

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

Objective: In cochlear implant (CI) users with residual acoustic hearing, compound action potentials (CAPs) can be evoked by acoustic or electric stimulation and recorded through the electrodes of the CI. We propose a novel computational model to simulate electrically and acoustically evoked CAPs in humans, taking into account the interaction between combined electric-acoustic stimulation that occurs at the level of 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 predicted for electric pulses and for acoustic clicks, chirps, and tone bursts closely resembled those known from humans. The spread of excitation derived from electrically evoked CAPs by varying the recording electrode along the CI electrode array was consistent with published human data. The predicted CAP amplitude growth functions for both electric and acoustic stimulation largely resembled human data, with deviations in absolute CAP amplitudes for acoustic stimulation. The model reproduced the suppression of electrically evoked CAPs 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 takes into account the dependence on stimulation and recording sites in the cochlea, as well as the interaction between electric and acoustic stimulation. Significance: The model can be used in the future to investigate objective methods, such as hearing threshold assessment or estimation of neural health through electrically or acoustically evoked CAPs.