Implementation issues in approximate methods for stochastic Hodgkin-Huxley models.
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Action Potentials↗
Biomedical subjects
Ian C Bruce
Publications and source records attributed to Ian C Bruce.
Modeling auditory-nerve responses for high sound pressure levels in the normal and impaired auditory periphery.
This paper presents a computational model to simulate normal and impaired auditory-nerve (AN) fiber responses in cats. The model responses match physiological data over a wider dynamic range than previous auditory models. This is achieved by providing two modes of basilar membrane excitation to the inner hair cell (IHC) rather than one. The two modes are generated by two parallel filters, component 1 (C1) and component 2 (C2), and the outputs are subsequently transduced by two separate functions. The responses are then added and passed through the IHC low-pass filter followed by the IHC-AN synapse model and discharge generator. The C1 filter is a narrow-band, chirp filter with the gain and bandwidth controlled by a nonlinear feed-forward control path. This filter is responsible for low and moderate level responses. A linear, static, and broadly tuned C2 filter followed by a nonlinear, inverted and nonrectifying C2 transduction function is critical for producing transition region and high-level effects. Consistent with Kiang's two-factor cancellation hypothesis, the interaction between the two paths produces effects such as the C1/C2 transition and peak splitting in the period histogram. The model responses are consistent with a wide range of physiological data from both normal and impaired ears for stimuli presented at levels spanning the dynamic range of hearing.
Acoustic Stimulation↗
A novel model-based hearing compensation design using a gradient-free optimization method.
We propose a novel model-based hearing compensation strategy and gradient-free optimization procedure for a learning-based hearing aid design. Motivated by physiological data and normal and impaired auditory nerve models, a hearing compensation strategy is cast as a neural coding problem, and a Neurocompensator is designed to compensate for the hearing loss and enhance the speech. With the goal of learning the Neurocompensator parameters, we use a gradient-free optimization procedure, an improved version of the ALOPEX that we have developed, to learn the unknown parameters of the Neurocompensator. We present our methodology, learning procedure, and experimental results in detail; discussion is also given regarding the unsupervised learning and optimization methods.
Algorithms↗
Physiological assessment of contrast-enhancing frequency shaping and multiband compression in hearing aids.
Spectral enhancement is now being used in many hearing aids in an attempt to compensate for broadened cochlear filtering. However, spectral enhancement may be counteracted by multiband-compression algorithms designed to compensate for the reduced dynamic range of the impaired cochlea. An alternative scheme for spectral enhancement, contrast-enhancing frequency shaping (CEFS), has been proposed, which results in an improved neural representation of the first and second formants of voiced speech segments in the impaired ear. In this paper, models of the normal and impaired ear are used to assess the compatibility of CEFS with multiband compression. Model auditory nerve responses were assessed under four conditions: (1) unmodified speech presented to a normal ear; (2) amplified, unshaped speech presented to an impaired ear; (3) CEFS speech presented to an impaired ear; and (4) CEFS+multiband-compression speech presented to an impaired ear. The results show that multiband compression does not reduce the benefits of CEFS, and in some cases multiband compression assists in preventing distortion of the neural representation of formants. These results indicate that the combination of contrast-enhancing frequency shaping and multiband compression should lead to improved perception of voiced speech segments in hearing aid users.
Algorithms↗
An auditory-periphery model of the effects of acoustic trauma on auditory nerve responses.
Acoustic trauma degrades the auditory nerve's tonotopic representation of acoustic stimuli. Recent physiological studies have quantified the degradation in responses to the vowel /E/ and have investigated amplification schemes designed to restore a more correct tonotopic representation than is achieved with conventional hearing aids. However, it is difficult from the data to quantify how much different aspects of the cochlear pathology contribute to the impaired responses. Furthermore, extensive experimental testing of potential hearing aids is infeasible. Here, both of these concerns are addressed by developing models of the normal and impaired auditory peripheries that are tested against a wide range of physiological data. The effects of both outer and inner hair cell status on model predictions of the vowel data were investigated. The modeling results indicate that impairment of both outer and inner hair cells contribute to degradation in the tonotopic representation of the formant frequencies in the auditory nerve. Additionally, the model is able to predict the effects of frequency-shaping amplification on auditory nerve responses, indicating the model's potential suitability for more rapid development and testing of hearing aid schemes.
Animals↗
Biological basis of hearing-aid design.
We show that we can accurately model the auditory-nerve discharge patterns in response to sounds as complex as speech and ask how we may exploit this knowledge to test new strategies for hearing-aid signal processing. We describe the auditory-nerve representations of vowels in normal and noise-damaged ears. The normal representations are predicted well by a cochlear signal processing model originally developed by Carney (Carney, L. H. J. Acoust. Soc. Am. 93:401-417, 1993). Basilar-membrane tuning is represented by a time-varying narrow-band filter. Outer hair cell control of tuning is exerted by a nonlinear feedback path. We show that the effects of noise-induced outer hair cell damage can be modeled by scaling the feedback signal appropriately and use the model to test one strategy for hearing-aid speech processing. We conclude by discussing some aspects of future trends in biomedical engineering approaches to problems of hearing impairment.
Action Potentials↗