Michael G. Heinz

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.

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.

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.

Envelope Coding in Auditory Nerve Fibers Following Noise-Induced Hearing Loss

Recent perceptual studies suggest that listeners with sensorineural hearing loss (SNHL) have a reduced ability to use temporal fine-structure cues, whereas the effects of SNHL on temporal envelope cues are generally thought to be minimal. Several perceptual studies suggest that envelope coding may actually be enhanced following SNHL and that this effect may actually degrade listening in modulated maskers (e.g., competing talkers). The present study examined physiological effects of SNHL on envelope coding in auditory nerve (AN) fibers in relation to fine-structure coding. Responses were compared between anesthetized chinchillas with normal hearing and those with a mild–moderate noise-induced hearing loss. Temporal envelope coding of narrowband-modulated stimuli (sinusoidally amplitude-modulated tones and single-formant stimuli) was quantified with several neural metrics. The relative strength of envelope and fine-structure coding was compared using shuffled correlogram analyses. On average, the strength of envelope coding was enhanced in noise-exposed AN fibers. A high degree of enhanced envelope coding was observed in AN fibers with high thresholds and very steep rate-level functions, which were likely associated with severe outer and inner hair cell damage. Degradation in fine-structure coding was observed in that the transition between AN fibers coding primarily fine structure or envelope occurred at lower characteristic frequencies following SNHL. This relative fine-structure degradation occurred despite no degradation in the fundamental ability of AN fibers to encode fine structure and did not depend on reduced frequency selectivity. Overall, these data suggest the need to consider the relative effects of SNHL on envelope and fine-structure coding in evaluating perceptual deficits in temporal processing of complex stimuli.

Quantifying Envelope and Fine-Structure Coding in Auditory Nerve Responses to Chimaeric Speech

Any sound can be separated mathematically into a slowly varying envelope and rapidly varying fine-structure component. This property has motivated numerous perceptual studies to understand the relative importance of each component for speech and music perception. Specialized acoustic stimuli, such as auditory chimaeras with the envelope of one sound and fine structure of another have been used to separate the perceptual roles for envelope and fine structure. Cochlear narrowband filtering limits the ability to isolate fine structure from envelope; however, envelope recovery from fine structure has been difficult to evaluate physiologically. To evaluate envelope recovery at the output of the cochlea, neural cross-correlation coefficients were developed that quantify the similarity between two sets of spike-train responses. Shuffled auto- and cross-correlogram analyses were used to compute separate correlations for responses to envelope and fine structure based on both model and recorded spike trains from auditory nerve fibers. Previous correlogram analyses were extended to isolate envelope coding more effectively in auditory nerve fibers with low center frequencies, which are particularly important for speech coding. Recovered speech envelopes were present in both model and recorded responses to one- and 16-band speech fine-structure chimaeras and were significantly greater for the one-band case, consistent with perceptual studies. Model predictions suggest that cochlear recovered envelopes are reduced following sensorineural hearing loss due to broadened tuning associated with outer-hair cell dysfunction. In addition to the within-fiber cross-stimulus cases considered here, these neural cross-correlation coefficients can also be used to evaluate spatiotemporal coding by applying them to cross-fiber within-stimulus conditions. Thus, these neural metrics can be used to quantitatively evaluate a wide range of perceptually significant temporal coding issues relevant to normal and impaired hearing.

Quantifying the Information in Auditory-Nerve Responses for Level Discrimination

An analytical approach for quantifying the information in auditory-nerve (AN) fiber responses for the task of level discrimination is described. A simple analytical model for AN responses is extended to include temporal response properties, including the nonlinear-phase effects of the cochlear amplifier. Use of simple analytical models for AN discharge patterns allows quantification of the contributions of level-dependent aspects of the patterns to level discrimination. Specifically, the individual and combined contributions of the information contained in discharge rate, synchrony, and relative phase cues are explicitly examined for level discrimination of tonal stimuli. It is shown that the rate information provided by individual AN fibers is more constrained by increases in variance with increases in rate than by saturation. As noted in previous studies, there is sufficient average-rate information within a narrow-CF region to account for robust behavioral performance over a wide dynamic range; however, there is no model based on a simple limitation or use of AN information consistent with parametric variations in performance. This issue is explored in the current study through analysis of performance based on different aspects of AN patterns. For example, we show that performance predicted from use of all rate information degrades significantly as level increases above low–medium levels, inconsistent with Weber’s Law. At low frequencies, synchrony information extends the range over which behavioral performance can be explained by 10–15 dB, but only at low levels. In contrast to rate and synchrony, nonlinear-phase cues are shown to provide robust information at medium and high levels in near-CF fibers for low-frequency stimuli. The level dependence of the discharge rate and phase properties of AN fibers are influenced by the compressive nonlinearity of the inner ear. Evaluating the role of the compressive nonlinearity in level coding is important for understanding neural encoding mechanisms and because of its association with the cochlear amplifier, which is a fragile aspect of the ear believed to be affected in common forms of hearing impairment.

Auditory-nerve rate responses are inconsistent with common hypotheses for the neural correlates of loudness recruitment.

AbstractA number of perceptual phenomena related to normal and impaired level coding can be accounted for by the degree of compression in the basilar-membrane (BM) magnitude response. However, the narrow dynamic ranges of auditory-nerve (AN) fibers complicate these arguments. Because the AN serves as an information bottleneck, an improved understanding of the neural coding of level may clarify some of the limitations of current hearing aids. Here three hypotheses for the neural correlate of loudness recruitment were evaluated based on AN responses from normal-hearing cats and from cats with a noise-induced hearing loss (NIHL). Auditory-nerve fiber rate-level functions for tones were analyzed to test the following hypotheses: Loudness recruitment results from steeper AN rate functions after impairment. This hypothesis was not supported; AN rate functions were not steeper than normal following NIHL, despite steeper estimated BM responses based on the AN data.Loudness is based on the total AN discharge count, and recruitment results from an abnormally rapid spread of excitation after impairment. Whereas abnormal spread of excitation can be observed, steeper growth of total AN rate is not seen over the range of sound levels where recruitment is observed in human listeners.Loudness of a narrowband stimulus is based on AN responses in a narrow BF region, and recruitment results from compression of the AN-fiber threshold distribution after impairment. This hypothesis was not supported because there was no evidence that impaired AN threshold distributions were compressed and the growth of AN activity summed across BFs near the stimulus frequency was shallower than normal.Overall, these results suggest that loudness recruitment cannot be accounted for based on summed AN rate responses and may depend on neural mechanisms involved in the central representation of intensity.

Diminished temporal coding with sensorineural hearing loss emerges in background noise

Behavioral studies in humans suggest that sensorineural hearing loss (SNHL) decreases sensitivity to the temporal structure of sound, but neurophysiological studies in mammals provide little evidence for diminished temporal coding. We found that SNHL in chinchillas degraded peripheral temporal coding in background noise substantially more than in quiet. These results resolve discrepancies between previous studies and help to explain why perceptual difficulties in hearing-impaired listeners often emerge in noisy situations.

Psychophysiological Analyses Demonstrate the Importance of Neural Envelope Coding for Speech Perception in Noise

Understanding speech in noisy environments is often taken for granted; however, this task is particularly challenging for people with cochlear hearing loss, even with hearing aids or cochlear implants. A significant limitation to improving auditory prostheses is our lack of understanding of the neural basis for robust speech perception in noise. Perceptual studies suggest the slowly varying component of the acoustic waveform (envelope, ENV) is sufficient for understanding speech in quiet, but the rapidly varying temporal fine structure (TFS) is important in noise. These perceptual findings have important implications for cochlear implants, which currently only provide ENV; however, neural correlates have been difficult to evaluate due to cochlear transformations between acoustic TFS and recovered neural ENV. Here, we demonstrate the relative contributions of neural ENV and TFS by quantitatively linking neural coding, predicted from a computational auditory nerve model, with perception of vocoded speech in noise measured from normal hearing human listeners. Regression models with ENV and TFS coding as independent variables predicted speech identification and phonetic feature reception at both positive and negative signal-to-noise ratios. We found that: (1) neural ENV coding was a primary contributor to speech perception, even in noise; and (2) neural TFS contributed in noise mainly in the presence of neural ENV, but rarely as the primary cue itself. These results suggest that neural TFS has less perceptual salience than previously thought due to cochlear signal processing transformations between TFS and ENV. Because these transformations differ between normal and impaired ears, these findings have important translational implications for auditory prostheses.

Auditory-nerve responses predict pitch attributes related to musical consonance-dissonance for normal and impaired hearing.

Human listeners prefer consonant over dissonant musical intervals and the perceived contrast between these classes is reduced with cochlear hearing loss. Population-level activity of normal and impaired model auditory-nerve (AN) fibers was examined to determine (1) if peripheral auditory neurons exhibit correlates of consonance and dissonance and (2) if the reduced perceptual difference between these qualities observed for hearing-impaired listeners can be explained by impaired AN responses. In addition, acoustical correlates of consonance-dissonance were also explored including periodicity and roughness. Among the chromatic pitch combinations of music, consonant intervals/chords yielded more robust neural pitch-salience magnitudes (determined by harmonicity/periodicity) than dissonant intervals/chords. In addition, AN pitch-salience magnitudes correctly predicted the ordering of hierarchical pitch and chordal sonorities described by Western music theory. Cochlear hearing impairment compressed pitch salience estimates between consonant and dissonant pitch relationships. The reduction in contrast of neural responses following cochlear hearing loss may explain the inability of hearing-impaired listeners to distinguish musical qualia as clearly as normal-hearing individuals. Of the neural and acoustic correlates explored, AN pitch salience was the best predictor of behavioral data. Results ultimately show that basic pitch relationships governing music are already present in initial stages of neural processing at the AN level.