Comparison of Performance for Cochlear-Implant Listeners Using Audio Processing Strategies Based on Short-Time Fast Fourier Transform or Spectral Feature Extraction.

Objectives: We compared sound quality and performance for a conventional cochlear-implant (CI) audio processing strategy based on short-time fast-Fourier transform (Crystalis) and an experimental strategy based on spectral feature extraction (SFE). In the latter, the more salient spectral features (acoustic events) were extracted and mapped into the CI stimulation electrodes. We hypothesized that (1) SFE would be superior to Crystalis because it can encode acoustic spectral features without the constraints imposed by the short-time fast-Fourier transform bin width, and (2) the potential benefit of SFE would be greater for CI users who have less neural cross-channel interactions.

How 'hidden hearing loss' noise exposure affects neural coding in the inferior colliculus of rats.

Exposure to brief, intense sound can produce profound changes in the auditory system, from the internal structure of inner hair cells to reduced synaptic connections between the auditory nerves and the inner hair cells. Moreover, noisy environments can also lead to alterations in the auditory nerve or to processing changes in the auditory midbrain, all without affecting hearing thresholds. This so-called hidden hearing loss (HHL) has been shown in tinnitus patients and has been posited to account for hearing difficulties in noisy environments.

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.

Modeling temporal information encoding by the population of fibers in the healthy and synaptopathic auditory nerve.

We report a theoretical study aimed at investigating the impact of cochlear synapse loss (synaptopathy) on the encoding of the envelope (ENV) and temporal fine structure (TFS) of sounds by the population of auditory nerve fibers. A computational model was used to simulate auditory-nerve spike trains evoked by sinusoidally amplitude-modulated (AM) tones at 10 Hz with various carrier frequencies and levels. The model included 16 cochlear channels with characteristic frequencies (CFs) from 250 Hz to 8 kHz.