Laurel H. Carney

A phenomenological model for the responses of auditory-nerve fibers: I. Nonlinear tuning with compression and suppression.

A phenomenological model was developed to describe responses of high-spontaneous-rate auditory-nerve (AN) fibers, including several nonlinear response properties. Level-dependent gain (compression), bandwidth, and phase properties were implemented with a control path that varied the gain and bandwidth of tuning in the signal-path filter. By making the bandwidth of the control path broad with respect to the signal path, the wide frequency range of two-tone suppression was included. By making the control-path filter level dependent and tuned to a frequency slightly higher than the signal-path filter, other properties of two-tone suppression were also included. These properties included the asymmetrical growth of suppression above and below the characteristic frequency and the frequency offset of the suppression tuning curve with respect to the excitatory tuning curve. The implementation of this model represents a relatively simple phenomenological description of a single mechanism that underlies several important nonlinear response properties of AN fibers. The model provides a tool for studying the roles of these nonlinearities in the encoding of simple and complex sounds in the responses of populations of AN fibers.

A model for the responses of low‐frequency auditory‐nerve fibers in cat

A computational model was developed for the responses of low-frequency auditory-nerve (AN) fibers in cat. The goal was to produce realistic temporal response properties and average discharge rates in response to simple and complex stimuli. Temporal and average-rate properties of AN responses change as a function of sound-pressure level due to nonlinearities in the auditory periphery. The input stage of the AN model is a narrow-band filter that simulates the mechanical tuning of the basilar membrane. The parameters of this filter vary continuously as a function of stimulus level via a feedback mechanism, simulating the compressive nonlinearity associated with the mechanics of the basilar membrane. A memoryless, saturating nonlinearity and two low-pass filters simulate transduction and membrane properties of the inner hair cell (IHC). A diffusion model for the IHC-AN synapse introduces adaptation. Finally, a nonhomogeneous Poisson process, modified by absolute and relative refractoriness, provides the output discharge times. Responses to several different stimuli are presented. These responses illustrate nonlinear temporal response properties that cannot be achieved with linear models for AN fibers.

Evaluating Auditory Performance Limits: I. One-Parameter Discrimination Using a Computational Model for the Auditory Nerve

A method for calculating psychophysical performance limits based on stochastic neural responses is introduced and compared to previous analytical methods for evaluating auditory discrimination of tone frequency and level. The method uses signal detection theory and a computational model for a population of auditory nerve (AN) fiber responses. The use of computational models allows predictions to be made over a wider parameter range and with more complete descriptions of AN responses than in analytical models. Performance based on AN discharge times (all-information) is compared to performance based only on discharge counts (rate-place). After the method is verified over the range of parameters for which previous analytical models are applicable, the parameter space is then extended. For example, a computational model of AN activity that extends to high frequencies is used to explore the common belief that rate-place information is responsible for frequency encoding at high frequencies due to the rolloff in AN phase locking above 2 kHz. This rolloff is thought to eliminate temporal information at high frequencies. Contrary to this belief, results of this analysis show that rate-place predictions for frequency discrimination are inconsistent with human performance in the dependence on frequency for high frequencies and that there is significant temporal information in the AN up to at least 10 kHz. In fact, the all-information predictions match the functional dependence of human performance on frequency, although optimal performance is much better than human performance. The use of computational AN models in this study provides new constraints on hypotheses of neural encoding of frequency in the auditory system; however, the method is limited to simple tasks with deterministic stimuli. A companion article in this issue (Evaluating Auditory Performance Limits: II) describes an extension of this approach to more complex tasks that include random variation of one parameter, for example, random-level variation, which is often used in psychophysics to test neural encoding hypotheses.

A phenomenological model of peripheral and central neural responses to amplitude-modulated tones

A phenomenological model with time-varying excitation and inhibition was developed to study possible neural mechanisms underlying changes in the representation of temporal envelopes along the auditory pathway. A modified version of an existing auditory-nerve model [Zhang et al., J. Acoust. Soc. Am. 109, 648-670 (2001)] was used to provide inputs to higher hypothetical processing centers. Model responses were compared directly to published physiological data at three levels: the auditory nerve, ventral cochlear nucleus, and inferior colliculus. Trends and absolute values of both average firing rate and synchrony to the modulation period were accurately predicted at each level for a wide range of stimulus modulation depths and modulation frequencies. The diversity of central physiological responses was accounted for with realistic variations of model parameters. Specifically, enhanced synchrony in the cochlear nucleus and rate-tuning to modulation frequency in the inferior colliculus were predicted by choosing appropriate relative strengths and time courses of excitatory and inhibitory inputs to postsynaptic model cells. The proposed model is fundamentally different than others that have been used to explain the representation of envelopes in the mammalian midbrain, and it provides a computational tool for testing hypothesized relationships between physiology and psychophysics.

A model for interaural time difference sensitivity in the medial superior olive: Interaction of excitatory and inhibitory synaptic inputs, channel dynamics, and cellular morphology

This study reports simulations of recent physiological results from the gerbil medial superior olive (MSO) that reveal that blocking glycinergic inhibition can shift the tuning for the interaural time difference (ITD) of the cell (Brand et al., 2002). Our simulations indicate that the model proposed in the study by Brand et al. (2002) requires precisely timed, short-duration inhibition with temporal accuracy exceeding that described in the auditory system. An alternative model is proposed that incorporates two anatomic observations in the MSO: (1) the axon arises from the dendrite that receives ipsilateral inputs; and (2) inhibitory synapses are located primarily on the soma in adult animals. When the inhibitory currents are activated or blocked, the model cell successfully simulates experimentally observed shifts in the best ITD. The asymmetrical cell structure allows an imbalance between the ipsilateral and contralateral excitatory inputs and shifts the ITD curve such that the best ITD is not at zero. Fine adjustment of the best ITD is achieved by the interplay of somatic sodium currents and synaptic inhibitory currents. The shift of the best ITD in the model is limited to ∼0.2 ms, which is behaviorally significant with respect to ITDs encountered in perceptual tasks. The model suggests a mechanism for dynamically “fine-tuning” the ITD sensitivity of MSO cells by the opponency between depolarizing sodium currents and hyperpolarizing inhibitory currents.

FREQUENCY GLIDES IN THE IMPULSE RESPONSES OF AUDITORY-NERVE FIBERS

Previous reports of frequency modulations, or glides, in the impulse responses of the auditory periphery have been limited to analyses of basilar-membrane measurements and responses of auditory-nerve (AN) fibers with best frequencies (BFs) greater than 1.7 kHz. These glides increased in frequency as a function of time. In this study, the instantaneous frequency as a function of time was measured for impulse responses of AN fibers in the cat with a range of BFs (250-4500 Hz). Impulse responses were estimated from responses to wideband noise using the reverse-correlation technique. The impulse responses had increasing frequency glides for fibers with BFs greater than 1500 Hz, nearly constant frequency as a function of time of BFs between 750 and 1500 Hz, and decreasing frequency glides for BFs below 750 Hz. Over the levels tested, the glides for fibers at all BFs were nearly independent of stimulus level, consistent with previous reports of impulse responses of the basilar membrane and AN fibers. Implications of the different glide directions observed for different BFs are discussed, specifically in relation to models for the auditory periphery as well as for the derivation of impulse responses for the human auditory periphery based on psychophysical measurements.

Determination of the potential benefit of time-frequency gain manipulation

Objective: The purpose of this study was to determine the maximum benefit provided by a time-frequency gain-manipulation algorithm for noise-reduction (NR) based on an ideal detector of speech energy. The amount of detected energy necessary to show benefit using this type of NR algorithm was examined, as well as the necessary speed and frequency resolution of the gain manipulation. Design: NR was performed using time-frequency gain manipulation, wherein the gains of individual frequency bands depended on the absence or presence of speech energy within each band. Three different experiments were performed: (1) NR using ideal detectors, (2) NR with nonideal detectors, and (3) NR with ideal detectors and different processing speeds and frequency resolutions. All experiments were performed using the Hearing-in-Noise test (HINT). A total of 6 listeners with normal hearing and 14 listeners with hearing loss were tested. Results: HINT thresholds improved for all listeners with NR based on the ideal detectors used in Experiment I. The nonideal detectors of Experiment II required detection of at least 90% of the speech energy before an improvement was seen in HINT thresholds. The results of Experiment III demonstrated that relatively high temporal resolution (<100 msec) was required by the NR algorithm to improve HINT thresholds. Conclusions: The results indicated that a single-microphone NR system based on time-frequency gain manipulation improved the HINT thresholds of listeners. However, to obtain benefit in speech intelligibility, the detectors used in such a strategy were required to detect an unrealistically high percentage of the speech energy and to perform the gain manipulations on a fast temporal basis.

Updated parameters and expanded simulation options for a model of the auditory periphery

A phenomenological model of the auditory periphery in cats was previously developed by Zilany and colleagues [J. Acoust. Soc. Am. 126, 2390-2412 (2009)] to examine the detailed transformation of acoustic signals into the auditory-nerve representation. In this paper, a few issues arising from the responses of the previous version have been addressed. The parameters of the synapse model have been readjusted to better simulate reported physiological discharge rates at saturation for higher characteristic frequencies [Liberman, J. Acoust. Soc. Am. 63, 442-455 (1978)]. This modification also corrects the responses of higher-characteristic frequency (CF) model fibers to low-frequency tones that were erroneously much higher than the responses of low-CF model fibers in the previous version. In addition, an analytical method has been implemented to compute the mean discharge rate and variance from the models synapse output that takes into account the effects of absolute refractoriness.

Auditory nerve model for predicting performance limits of normal and impaired listeners

A computational auditory nerve (AN) model was developed for use in modeling psychophysical experiments with normal and impaired human listeners. In this phenomenological model, many physiologically vulnerable response properties associated with the cochlear amplifier are represented by a single nonlinear control mechanism, including the effects of level-dependent tuning, compression, level-dependent phase, suppression, and fast nonlinear dynamics on the responses of high, medium, and low spontaneous-rate (SR) AN fibers. Several model versions are described that can be used to evaluate the relative effects of these nonlinear properties.

Spatiotemporal encoding of sound level: Models for normal encoding and recruitment of loudness

This study explores the hypothesis that sound level is encoded in the spatiotemporal response patterns of auditory nerve (AN) fibers. The temporal properties of AN fiber responses depend upon sound level due to nonlinearities in the auditory periphery. In particular, the compressive nonlinearity of the inner ear introduces systematic changes in the timing of the responses of AN fibers as a function of level. Changes in single fiber responses that depend upon both sound level and characteristic frequency (CF) result in systematic changes in the spatiotemporal response patterns across populations of AN fibers. This study investigates the changes in the spatiotemporal response patterns as a function of level using a computational model for responses of low-frequency AN fibers. A mechanism that could extract information encoded in this form is coincidence detection across AN fibers of different CFs. This study shows that this mechanism could play a role in encoding of sound level for simple and complex stimuli. The model demonstrates that this encoding scheme would be influenced by auditory pathology that affects the peripheral compressive nonlinearity in a way that is consistent with the phenomenon of recruitment of loudness, which often accompanies sensorineural hearing loss.