Inherent envelope fluctuations in forward masking: Effects of age and hearing loss

Otoacoustic emissions but not behavioral measurements predict cochlear-nerve frequency tuning in an avian vocal-communication specialist

Frequency analysis by the cochlea forms a key foundation for all subsequent auditory processing. Stimulus-frequency otoacoustic emissions (SFOAEs) are a potentially powerful alternative to traditional behavioral experiments for estimating cochlear tuning without invasive testing, as is necessary in humans. Which methods accurately predict cochlear tuning remains controversial due to only a single animal study comparing SFOAE-based, behavioral, and cochlear frequency tuning in the same species. The budgerigar ( Melopsittacus undulatus ) is a parakeet species with human-like behavioral sensitivity to many sounds and the capacity to mimic speech. Intriguingly, previous studies of critical bands, psychophysical tuning curves, and critical ratios in budgerigars show that behavioral tuning sharpness increases dramatically with increasing frequency from 1-3.5 kHz, doubling once per octave with peak tuning sharpness from 3.5-4 kHz. The pattern contrasts with slower monotonic growth of behavioral tuning sharpness with increasing frequency in other animals, including most avian species, suggesting a possible auditory specialization in budgerigars. We measured SFOAE-based and cochlear-afferent tuning in budgerigars, for comparison to previously reported behavioral results. SFOAE-based and cochlear-afferent tuning sharpness both increased monotonically and relatively slowly for higher frequencies, in contrast to the behavioral pattern. SFOAE-based tuning in budgerigars accurately predicted cochlear frequency tuning, and both measures aligned with typical patterns of cochlear tuning in other species. Divergent behavioral tuning in budgerigars is unlikely attributable to the periphery and could reflect specializations for central processing of masked signals. Our findings highlight the value of SFOAEs for estimating cochlear tuning and caution against direct inference of cochlear tuning from behavioral critical bands, psychophysical tuning curves, and critical ratios.

A Subcortical Model for Auditory Forward Masking with Efferent Control of Cochlear Gain

Previous physiological and psychophysical studies have explored whether feedback to the cochlea from the efferent system influences forward masking. The present work proposes that the limited growth-of-masking (GOM) observed in auditory nerve (AN) fibers may have been misunderstood; namely, that this limitation may be due to the influence of anesthesia on the efferent system. Building on the premise that the unanesthetized AN may exhibit GOM similar to more central nuclei, the present computational modeling study demonstrates that feedback from the medial olivocochlear (MOC) efferents may contribute to GOM observed physiologically in onset-type neurons in both the cochlear nucleus and inferior colliculus (IC). Additionally, the computational model of MOC efferents used here generates a decrease in masking with longer masker-signal delays similar to that observed in IC physiology and in psychophysical studies. An advantage of this explanation over alternative physiological explanations (e.g., that forward masking requires inhibition from the superior paraolivary nucleus) is that this theory can explain forward masking observed in the brainstem, early in the ascending pathway. For explaining psychoacoustic results, one strength of this model is that it can account for the lack of elevation in thresholds observed when masker level is randomly varied from interval-to-interval, a result that is difficult to explain using the conventional temporal window model of psychophysical forward masking. Future directions for evaluating the efferent mechanism as a contributing mechanism for psychoacoustic results are discussed.

Neural Fluctuation Contrast as a Code for Complex Sounds: The Role and Control of Peripheral Nonlinearities

The nonlinearities of the inner ear are often considered to be obstacles that the central nervous system has to overcome to decode neural responses to sounds. This review describes how peripheral nonlinearities, such as saturation of the inner-hair-cell response and of the IHC-auditory-nerve synapse, are instead beneficial to the neural encoding of complex sounds such as speech. These nonlinearities set up contrast in the depth of neural-fluctuations in auditory-nerve responses along the tonotopic axis, referred to here as neural fluctuation contrast (NFC). Physiological support for the NFC coding hypothesis is reviewed, and predictions of several psychophysical phenomena, including masked detection and speech intelligibility, are presented. Lastly, a framework based on the NFC code for understanding how the medial olivocochlear (MOC) efferent system contributes to the coding of complex sounds is presented. By modulating cochlear gain control in response to both sound energy and fluctuations in neural responses, the MOC system is hypothesized to function not as a simple feedback gain-control device, but rather as a mechanism for enhancing NFC along the tonotopic axis, enabling robust encoding of complex sounds across a wide range of sound levels and in the presence of background noise. Effects of sensorineural hearing loss on the NFC code and on the MOC feedback system are presented and discussed.

Subcortical auditory model including efferent dynamic gain control with inputs from cochlear nucleus and inferior colliculus

An auditory model has been developed with a time-varying, gain-control signal based on the physiology of the efferent system and subcortical neural pathways. The medial olivocochlear (MOC) efferent stage of the model receives excitatory projections from fluctuation-sensitive model neurons of the inferior colliculus (IC) and wide-dynamic-range model neurons of the cochlear nucleus. The response of the model MOC stage dynamically controls cochlear gain via simulated outer hair cells. In response to amplitude-modulated (AM) noise, firing rates of most IC neurons with band-enhanced modulation transfer functions in awake rabbits increase over a time course consistent with the dynamics of the MOC efferent feedback. These changes in the rates of IC neurons in awake rabbits were employed to adjust the parameters of the efferent stage of the proposed model. Responses of the proposed model to AM noise were able to simulate the increasing IC rate over time, whereas the model without the efferent system did not show this trend. The proposed model with efferent gain control provides a powerful tool for testing hypotheses, shedding insight on mechanisms in hearing, specifically those involving the efferent system.