Psychophysical threshold variability in cochlear implant subjects

Music Perception and Speech-in-Noise Skills of Typical Hearing and Cochlear Implant Listeners

Purpose Adult cochlear implant (CI) users rate music as one of the most important auditory stimuli, second to speech perception. However, few studies simultaneously examine music perception and speech-in-noise perception in adult CI recipients. This study explores the effect of auditory status on music perception and speech-in-noise perception recognition in noise as well as the relationship among music engagement, music perception, and speech-in-noise perception. Method Participants include 10 adults with typical hearing (TH) and 10 adults with long-term CI use. All participants completed the Music-Related Quality of Life Questionnaire, which assesses subjective music experiences and their importance; the Pitch Direction Discrimination, Familiar Melody Recognition, and Timbre Recognition subtests of the Clinical Assessment of Music Perception for Cochlear Implants; the Unfamiliar Melody Recognition subtest of the Profile of Music Perception Skills; and the Bamford-Kowal-Bench Speech-in-Noise Test. Results The TH group significantly outperformed the CI group for speech-in-noise perception and on all four music perception tasks. The CI group exhibited not only significantly poorer mean scores but also greater variability in performance compared to the TH group. Only Familiar Melody Recognition and Unfamiliar Melody Recognition subtests significantly correlated with speech-in-noise scores. Conclusions Patients and professionals should not assume speech perception and music perception in adult CI users derive from the same auditory or cognitive foundations. The lack of significant relationships among music engagement, music perception, and speech-in-noise perception scores in adult CI users suggests this population enjoys music despite poor and variable performance in discrete music tasks.

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.

Bioactive polymer scaffold for fabrication of vascularized engineering tissue

Tissue engineering seeks strategies to design polymeric scaffolds that allow high-cell-density cultures with signaling molecules and suitable vascular supply. One major obstacle in tissue engineering is the inability to create thick engineered-tissue constructs. A pre-vascularized tissue scaffold appears to be the most favorable approach to avoid nutrient and oxygen supply limitations as well as to allow waste removal, factors that are often hurdles in developing thick engineered tissues. Vascularization can be achieved using strategies in which cells are cultured in bioactive polymer scaffolds that can mimic extracellular matrix environments. This review addresses recent advances and future challenges in developing and using bioactive polymer scaffolds to promote tissue construct vascularization.

Evaluation of stochastic differential equation approximation of ion channel gating models

Fox and Lu derived an algorithm based on stochastic differential equations for approximating the kinetics of ion channel gating that is simpler and faster than "exact" algorithms for simulating Markov process models of channel gating. However, the approximation may not be sufficiently accurate to predict statistics of action potential generation in some cases. The objective of this study was to develop a framework for analyzing the inaccuracies and determining their origin. Simulations of a patch of membrane with voltage-gated sodium and potassium channels were performed using an exact algorithm for the kinetics of channel gating and the approximate algorithm of Fox & Lu. The Fox & Lu algorithm assumes that channel gating particle dynamics have a stochastic term that is uncorrelated, zero-mean Gaussian noise, whereas the results of this study demonstrate that in many cases the stochastic term in the Fox & Lu algorithm should be correlated and non-Gaussian noise with a non-zero mean. The results indicate that: (i) the source of the inaccuracy is that the Fox & Lu algorithm does not adequately describe the combined behavior of the multiple activation particles in each sodium and potassium channel, and (ii) the accuracy does not improve with increasing numbers of channels.

Relationship between perception of spectral ripple and speech recognition in cochlear implant and vocoder listeners

Spectral resolution has been reported to be closely related to vowel and consonant recognition in cochlear implant (CI) listeners. One measure of spectral resolution is spectral modulation threshold (SMT), which is defined as the smallest detectable spectral contrast in the spectral ripple stimulus. SMT may be determined by the activation pattern associated with electrical stimulation. In the present study, broad activation patterns were simulated using a multi-band vocoder to determine if similar impairments in speech understanding scores could be produced in normal-hearing listeners. Tokens were first decomposed into 15 logarithmically spaced bands and then re-synthesized by multiplying the envelope of each band by matched filtered noise. Various amounts of current spread were simulated by adjusting the drop-off of the noise spectrum away from the peak (40-5 dBoctave). The average SMT (0.25 and 0.5 cyclesoctave) increased from 6.3 to 22.5 dB, while average vowel identification scores dropped from 86% to 19% and consonant identification scores dropped from 93% to 59%. In each condition, the impairments in speech understanding were generally similar to those found in CI listeners with similar SMTs, suggesting that variability in spread of neural activation largely accounts for the variability in speech perception of CI listeners.

How cochlear implants encode speech

PURPOSE OF REVIEW

This review summarizes the history of cochlear implant signal processing and provides the rationale underlying current approaches. Present strategies are explained and recent research findings are summarized. It is suggested how these results may drive future advancements in signal processing.

RECENT FINDINGS

Substantial advances have been made in our understanding of the spectral and temporal cues necessary for cochlear implant recipients to perceive music, speech in noise, and interaural timing. It is clear that higher levels of both spectral and temporal resolution, as well as better loudness and pitch coding are necessary for higher levels of performance. These factors are highly interrelated, however, and are beneficial for differing aspects of hearing. Signal processing algorithms incorporating these findings are under active development and some are currently undergoing clinical investigation.

SUMMARY

Current implant devices, and those soon to be available, have substantial untapped potential to improve the auditory experience of their recipients. It is likely that in the near future, recent findings on pitch and loudness perception, as well as techniques to better emulate the normal functions of the cochlea will result in much higher levels of prosthetic hearing fidelity than are possible today. As the performance of these remarkable devices continues to improve, the population of hearing-impaired individuals who can benefit from implantation is likely to increase significantly.

Predicting the Threshold of Pulse-Train Electrical Stimuli Using a Stochastic Auditory Nerve Model: The Effects of Stimulus Noise

The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in some human subjects (Zeng et al., 2000). In this paper, thresholds for noise-modulated pulse-train stimuli are predicted utilizing a stochastic neural-behavioral model of ensemble fiber responses to bi-phasic stimuli. The neural refractory effect is described using a Markov model for a noise-free pulse-train stimulus and a closed-form solution for the steady-state neural response is provided. For noise-modulated pulse-train stimuli, a recursive method using the conditional probability is utilized to track the neural responses to each successive pulse. A neural spike count rule has been presented for both threshold and intensity discrimination under the assumption that auditory perception occurs via integration over a relatively long time period (Bruce et al., 1999). An alternative approach originates from the hypothesis of the multilook model (Viemeister and Wakefield, 1991), which argues that auditory perception is based on several shorter time integrations and may suggest an NofM model for prediction of pulse-train threshold. This motivates analyzing the neural response to each individual pulse within a pulse train, which is considered to be the brief look. A logarithmic rule is hypothesized for pulse-train threshold. Predictions from the multilook model are shown to match trends in psychophysical data for noise-free stimuli that are not always matched by the long-time integration rule. Theoretical predictions indicate that threshold decreases as noise variance increases. Theoretical models of the neural response to pulse-train stimuli not only reduce calculational overhead but also facilitate utilization of signal detection theory and are easily extended to multichannel psychophysical tasks.