Rate modulation detection thresholds for cochlear implant users

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.

Applications of Phenomenological Loudness Models to Cochlear Implants

Cochlear implants electrically stimulate surviving auditory neurons in the cochlea to provide severely or profoundly deaf people with access to hearing. Signal processing strategies derive frequency-specific information from the acoustic signal and code amplitude changes in frequency bands onto amplitude changes of current pulses emitted by the tonotopically arranged intracochlear electrodes. This article first describes how parameters of the electrical stimulation influence the loudness evoked and then summarizes two different phenomenological models developed by McKay and colleagues that have been used to explain psychophysical effects of stimulus parameters on loudness, detection, and modulation detection. The Temporal Model is applied to single-electrode stimuli and integrates cochlear neural excitation using a central temporal integration window analogous to that used in models of normal hearing. Perceptual decisions are made using decision criteria applied to the output of the integrator. By fitting the model parameters to a variety of psychophysical data, inferences can be made about how electrical stimulus parameters influence neural excitation in the cochlea. The Detailed Model is applied to multi-electrode stimuli, and includes effects of electrode interaction at a cochlear level and a transform between integrated excitation and specific loudness. The Practical Method of loudness estimation is a simplification of the Detailed Model and can be used to estimate the relative loudness of any multi-electrode pulsatile stimuli without the need to model excitation at the cochlear level. Clinical applications of these models to novel sound processing strategies are described.

Encoding speech in cochlear implants using simultaneous amplitude and rate modulation

To improve speech perception for cochlear implant (CI) users, it is essential to improve the transmission of temporal envelopes. The most common speech processors deliver temporal envelopes via the CI using fixed-rate amplitude modulated (AM) pulse trains. Psychophysical studies suggest that rate modulation (RM) and AM are perceived by a shared temporal integration mechanism, but the potential for them to constructively combine to encode temporal envelopes has yet to be explored. In this experiment, a speech processing strategy called amplitude and rate temporal modulation was developed to encode speech temporal envelopes with simultaneous AM and RM. The strategy was tested for perception of clean speech at 60 and 40 dBA, and 60 dBA speech in noise (+10 dB SNR). The amount of RM was varied and the amount of AM was held constant to determine whether the addition of RM could enhance the perception of temporal envelopes and improve speech understanding. At the lowest RM amount, speech scores were poorest for all speech conditions. For 60 dBA clean speech and speech in noise, speech scores were significantly better at the highest RM amounts, suggesting that RM combined with AM can be used to enhance perception of temporal envelopes.