The Journal of the Acoustical Society of America

Elephants and other large mammals produce low-frequency vocalizations extending well below the 20 Hz lower limit of human hearing, a regime known as infrasound. These rumbles serve vital social and reproductive functions over distances of several kilometers, yet they are inaudible to human observers and cannot be reproduced by conventional small loudspeakers. We present a complete signal-processing pipeline that renders sub-20 Hz elephant rumbles perceptible through a small loudspeaker by exploiting the missing-fundamental psychoacoustic effect. Butterworth bandpass filters isolate the infrasonic content; a full-wave integrator nonlinear device (NLD) generates the harmonic series required for virtual pitch perception; and a hysteresis-comparator fundamental-frequency estimator normalizes the NLD output. The pipeline was validated on African elephant field recordings and deployed on a credit-card-sized, low-cost single-board computer with an infrasound microphone and a small Bluetooth loudspeaker, demonstrating live operation in the field. The processed output shows a 10 dB to 15 dB elevation in the loudspeakers efficient band during call segments compared with background. The system enables zoo visitors and wildlife observers to perceive elephant rumbles in real time, opening new avenues for behavioral studies and public engagement with animal communication.

The role of medial olivocochlear (MOC) efferent gain control in auditory enhancement (AE) was investigated using a subcortical auditory model. AE refers to the influence of a precursor on detectability of targets. The absence (or presence) of a precursor component at the target frequency enhances (or suppresses) detection under simultaneous masking conditions. Furthermore, the enhanced target under simultaneous masking acts as a stronger forward masker for a delayed probe tone, known as AE under forward masking. Psychoacoustic studies of AE report findings that challenge conventional expectations, and the underlying mechanisms remain unclear. For instance, listeners with hearing impairment have AE under simultaneous masking but not forward masking (Kreft et al., 2018; Kreft and Oxenham, 2019), whereas listeners with normal hearing have level-dependent AE under forward masking (Kreft and Oxenham, 2019). Our model with MOC efferent gain control successfully replicated these findings. In contrast, a model without efferent gain control failed to capture these effects, supporting the hypothesis that MOC-mediated cochlear gain modulation may play a role in AE and its alteration by hearing loss.

Constant-frequency (CF) bats exhibit rapid oscillations of their external ears. Yet, the functional role of these movements has remained unresolved since their initial documentation over half a century ago. Although recent studies have demonstrated that pinna motion generates Doppler shifts, they do not explain why ear oscillations intensify at close range or how these dynamics contribute to echo perception. In this study, I investigate the hypothesis that oscillatory ear movements enhance echo information during CF echolocation. Using a simplified receiver-motion model, I examine how time-varying pinna pose reshapes the temporal and spectral structure of returning echoes. I show that ear oscillations inject dynamic transformations into the received signal, producing multiple informative views of the same echo and increasing both temporal contrast and spectral diversity around the CF carrier. These transformations are strongest under behavioural conditions in which target-state uncertainty is expected to be high, offering a potential functional explanation for the long-standing observation that ear-oscillation rate increases as bats approach a target. The results suggest that oscillatory ear movements act as an adaptive, receiver-side mechanism that enhances echo information during CF echolocation, complementing the well-known emitter-side adaptations of high-duty-cycle biosonar.

ObjectiveThe current study examined the frequency specificity of NB chirps by comparing the spectral characteristics of 500-, 1000-, 2000- and 4000-Hz NB CE-Chirp(R) LS stimuli with those of 2-1-2 tones. DesignSpectral characteristics including the centre frequency, bandwidth, and stimulus energy changes after stopband filtering were compared. The bandwidth was computed as the difference between the upper and lower frequencies at -20 dB (& -3 dB) cutoff points of the main lobe; the centre frequency was determined as the geometric mean of the upper and lower frequencies at the -20 dB (& -3 dB) cutoff points. ResultsAt 100 dB peSPL, the bandwidths of the 500-, 1000-, and 2000-Hz NB CE-Chirp(R) LS acoustic spectra were 1.7-2.5 times wider than the acoustic spectra for the 2-1-2 tones; the 4000-Hz NB CE-Chirp(R) LS bandwidths were 1.4-1.6 times wider than those of the 2-1-2 tones. The energy of NB CE-Chirp(R) LS stimuli was concentrated within {+/-}0.75 octave of the centre frequency, compared to {+/-}0.5 octave for 2-1-2 tones. ConclusionNB CE-Chirp(R) LS stimuli demonstrated poorer frequency specificity compared with 2-1-2 tones. Further studies are needed to investigate the place specificity of the ABRs to NB CE-Chirp(R) LS before implementing them clinically.

Spectral similarity is often judged with a single metric such as RMSE, yet this can be misleading: physically different errors can produce similar scores. This is a critical limitation for computational biomechanics, where spectral agreement underpins both model validation and machine-learning loss design. Here, we develop a multi-metric framework for objective spectral biofidelity and test whether it better captures meaningful disagreement across complex frequency-domain responses. We evaluated 12 complementary similarity metrics, including CORA and ISO/TS 18571, using controlled spectral perturbations that mimic common real-world deviations such as resonance shifts, localized spikes, and broadband tilts. We then applied the framework to an SBI-tuned finite-element middle-ear model to assess convergence with training dataset size and robustness to measurement noise across repeated stochastic runs. No single metric performed reliably across all distortion types. Shape-based metrics tracked resonance morphology but could miss vertical scaling, whereas MaxError remained important for narrowband anomalies that smoother metrics underweighted. CORA and ISO 18571 did not consistently outperform simpler metrics. Rank aggregation using Borda count provided a robust consensus across metrics, enabling objective identification of training-data saturation and noise thresholds beyond which similarity rankings became unstable. These results show that spectral biofidelity cannot be reduced to a single norm. A multi-metric consensus provides a clearer and more physically meaningful basis for comparing experimental and simulated spectra, and offers a more defensible foundation for data-fidelity terms in physics-informed and simulation-based machine learning.

The Auditory Brainstem Response (ABR) can be used to evaluate hearing sensitivity of animals who are unable to respond to behavioral tasks. However, typical data collection methods are time consuming; decreasing the measurement time may save resources or allow researchers to spend more time on other tasks. Here, an adaptive algorithm is proposed for efficient estimation of ABR thresholds. The algorithm relies on the online update of the predicted hearing threshold from a Gaussian process model as ABR data are collected using iteratively optimized stimuli. To validate the algorithm, ABR threshold estimation is simulated by adaptively sub-sampling pre-collected ABR datasets for which the stimuli were systematically varied in frequency and level. The simulated experiment is performed on 5 datasets of Mouse (2 different datasets), Budgerigar, Gerbil, and Guinea Pig ABRs collected by different laboratories, with a total of 27 ears. The original datasets contain between 68 and 106 stimuli conditions, while the adaptive algorithm is run up to a total of 20 stimuli conditions. The adaptive algorithm ABR threshold estimate is compared against human rater estimates who view the full ABR dataset. The adaptive algorithm threshold matches the human estimates within 10 dB, averaged over frequency, for 19 out of 27 ears. The adaptive procedure is able to provide threshold estimates that are comparable to the human rater estimated thresholds while reducing the measurement time by a factor of 3 to 5. The standard deviation of threshold estimates from successive runs is smaller than the inter-human rater differences, indicating adequate test/retest reliability.

Vocoder simulations have played a crucial role in the development of sound coding and speech processing techniques for auditory implant devices. Vocoders have been extensively used to model the effects of implant signal processing as well as individual anatomy and physiology on speech perception of implant users. Traditionally, such simulations have been conducted on human subjects, which can be time-consuming and costly. In addition, perception of vocoded speech varies significantly across individual subjects, and can be significantly affected by small amounts of familiarization or exposure to vocoded sounds. In this study, we propose a novel method that differs from traditional vocoder studies. Rather than using actual human participants, we use a speech recognition model to examine the influence of vocoder-simulated cochlear implant processing on speech perception. We used the OpenAI Whisper, a recently developed advanced open-source deep learning speech recognition model. The Whisper models performance was evaluated on vocoded words and sentences in both quiet and noisy conditions with respect to several vocoder parameters such as number of spectral bands, input frequency range, envelope cut-off frequency, envelope dynamic range, and number of discriminable envelope steps. Our results indicate that the Whisper model exhibited human-like robustness to vocoder simulations, with performance closely mirroring that of human subjects in response to modifications in vocoder parameters. Furthermore, this proposed method has the advantage of being far less expensive and quicker than traditional human studies, while also being free from inter-individual variability in learning abilities, cognitive factors, and attentional states. Our study demonstrates the potential of employing advanced deep learning models of speech recognition in auditory prosthesis research.

Many voice disorders are linked to imbalanced muscle activity and known to exhibit asymmetric vocal fold vibration. However, the relation between imbalanced muscle activation and asymmetric vocal fold vibration is not well understood. This study introduces an asymmetric triangular body-cover model of the vocal folds, controlled by the activation of intrinsic laryngeal muscles, to investigate the effects of muscle imbalance on vocal fold oscillation. Various scenarios were considered, encompassing imbalance in individual muscles and muscle pairs, as well as accounting for asymmetry in lumped element parameters. The results highlight the antagonistic effect between the thyroarytenoid and cricothyroid muscles on the elastic and mass components of the vocal folds, as well as the impact on the vocal process from the imbalance in the lateral cricoarytenoid and interarytenoid adductor muscles. Measurements of amplitude and phase asymmetry were employed to emulate the oscillatory behavior of two pathological cases: unilateral paralysis and muscle tension dysphonia. The resulting simulations exhibit muscle imbalance consistent with expectations in the composition of these voice disorders, yielding asymmetries exceeding 30% for paralysis and below 5% for dysphonia. This underscores the versatility of muscle imbalance in representing phonatory scenarios and its potential for characterizing asymmetry in vocal fold vibration.

The neural response of the brainstem to brief sounds, known as the auditory brainstem response (ABR), is widely employed in the laboratory and the clinic to diagnose hearing loss. In contrast to behavioral methods that assess hearing using responses to sounds on a trial-by-trial basis, current ABR approaches are limited to analyzing the average ABR over hundreds of trials. Historically, trial-by-trial ABR analysis has not been possible owing to each trials small signal-to-noise ratio. Here we overcome this limitation and show how to classify individual ABR trials as detected or undetected. We use the distribution of single-trial ABRs to assess supra-threshold hearing and to define psychophysics-like thresholds, which we call auditory brainstem detection (ABD) thresholds. ABD thresholds decrease as more of the ABR epoch is taken into account, whereas traditional ABR thresholds do not change. Above the ABD thresholds and below 90 dB SPL, signal detection is significantly improved by utilizing more of the ABR epoch. Our method also allows us to rank the supra-threshold hearing ability of individual subjects. Despite having normal ABR thresholds, some subjects appear to have supra-threshold hearing deficits. The trial-by-trial method demonstrates that signal detection by the ensemble of auditory neurons in the brainstem is intrinsically stochastic not only at low stimulus levels, but also at levels up to 100 dB SPL. Significance StatementNeural responses to sound can be measured by electrodes placed on a subjects head and are commonly used in the laboratory and the clinic to assess hearing. Although the auditory system must distinguish each sound stimulus from intrinsic noise, current methods for ana-lyzing the response of the brainstem to sound only utilize the average response to hundreds of stimuli. Here we overcome this constraint by showing how to classify an individual sound stimulus as detected or undetected based on each auditory brainstem response. This ap-proach can assess hearing at all stimulus levels, indicates that subjects with normal hearing thresholds can exhibit supra-threshold hearing loss, and potentially extends the types of hearing deficits that can be diagnosed using auditory evoked potentials.

Optical coherence tomography (OCT) has allowed in vivo recording of sound-induced vibrations of different regions within the organ of Corti complex (OCC), including the basilar membrane (BM), outer hair cell/Deiters cell (OHC/DC) region, and reticular lamina (RL). In the hook region of the gerbil cochlea, where measurements can be made with a substantially transverse optical axis, the three regions have different and characteristic motion responses: The OHC/DC region has greater motions than the other two regions at frequencies below the best frequency (sub-BF); the RL region typically has the greatest BF peak and smallest sub-BF motion. The phase of the OHC/DC-region motion increasingly lags BM motion phase as frequency increases; the RL-region motion phase leads BM, but with a relatively small value. All three regions are compressively nonlinear in the BF peak, but only the OHC/DC region shows sub-BF compressive nonlinearity. In this paper, we describe the strain that exists within the RL and OHC-body regions. These strains are large where the motion varies over short distances, and a region of large strain can be as short as a single 2.7 {micro}m measurement pixel, or extend over several pixels, with the extensive strains appearing more often at 70 than at 50 dB SPL. Beyond the region of large strain, over a distance that can exceed 20 m, the OHC/DC region displays nearly unvarying motion spatially -- this region appears to vibrate as a body. Statement of SignificanceThe sensory tissue of the cochlea responds actively to a sound stimulus: cell-based forces amplify and enhance the vibration of the sensory tissue. Measurements employing optical coherence tomography have identified major vibration patterns along a sensory-tissue-spanning line that includes the active outer hair cells. In this article, we describe the transitional motion between these major vibration regions and the motion strains that exist as vibration morphs from one region to the next. The findings are presented in frequency response curves to convey the frequency tuning and its stimulus-level dependence, and in one-dimensional heat maps to convey the extent of regional motions and strains. These findings fuel and constrain conceptual and physics-based models of cochlear amplification.

A common assumption about the cochlea is that the local characteristic frequency (CF) is determined by a local resonance of basilar-membrane (BM) stiffness with the mass of the organ-of-Corti (OoC) and entrained fluid. We modeled the cochlea while avoiding such a priori assumptions by using a finite-element model of a 20-m-thick cross-sectional slice of the middle turn of a passive gerbil cochlea. The model had anatomically accurate structural details with physiologically appropriate material properties and interactions between the fluid spaces and solid OoC structures. The longitudinally-facing sides of the slice had a phase difference that mimicked the traveling-wave wavelength at the location of the slice by using Floquet boundary conditions. A paired volume-velocity drive was applied in the scalae at the top and bottom of the slice with the amplitudes adjusted to mimic experimental BM motion. The development of this computationally efficient model with detailed anatomical structures is a key innovation of this work. The resulting OoC motion was greatest in the transverse direction, stereocilia-tip deflections were greatest in the radial direction and longitudinal motion was small in OoC tissue but became large in the sulcus at high frequencies. If the source velocity and wavelength were held constant across frequency, the OoC motion was almost flat across frequency, i.e., the slice showed no local resonance. A model with the source velocity held constant and the wavelength varied realistically across frequency, produced a low-pass frequency response. These results indicate that tuning in the gerbil middle turn is not produced by a resonance due to local OoC mechanical properties, but rather is produced by the characteristics of the traveling wave, manifested in the driving pressure and wavelength. STATEMENT OF SIGNIFICANCEThe sensory epithelium of hearing, the organ of Corti, is encased in the bone of the fluid-filled cochlea and is difficult to study experimentally. We provide a new method to study the cochlea: making an anatomically-detailed finite-element model of a small transverse slice of the cochlea using Floquet boundary conditions and incorporating global cochlear properties in the slice drive and the wavelength-frequency relationship. The model shows that the slice properties do not show a mechanical resonance and therefore do not produce the frequency-response tuning of the cochlea. Instead, tuning emerges from global cochlear properties carried by the traveling wave.

Auditory sensation is based in nanoscale vibration of the sensory tissue of the cochlea, the organ of Corti complex (OCC). Motion within the OCC is now observable due to optical coherence tomography. In the cochlear base, in response to sound stimulation, the region that includes the electro-motile outer hair cells (OHC) was observed to move with larger amplitude than the basilar membrane (BM) and surrounding regions. The intense motion is based in active cell mechanics, and the region was termed the "hotspot" (Cooper et al., 2018, Nature comm). In addition to this quantitative distinction, the hotspot moved qualitatively differently than the BM, in that its motion scaled nonlinearly with stimulus level at all frequencies, evincing sub-BF activity. Sub-BF activity enhances non-BF motion; thus the frequency tuning of the hotspot was reduced relative to the BM. Regions that did not exhibit sub-BF activity are here defined as the OCC "frame". By this definition the frame includes the BM, the medial and lateral OCC, and most significantly, the reticular lamina (RL). The frame concept groups the majority OCC as a structure that is largely shielded from sub-BF activity. This shielding, and how it is achieved, are key to the active frequency tuning of the cochlea. The observation that the RL does not move actively sub-BF indicates that hair cell stereocilia are not exposed to sub-BF activity. A complex difference analysis reveals the motion of the hotspot relative to the frame.

Many sounds contain spectral modulations at multiple scales, but much is still unknown about how such spectral features are represented in the auditory system. One behavioral task that provides insight into this question is profile analysis. In a typical profile-analysis task, listeners are asked to discriminate between a complex tone with equal-amplitude components and a complex tone with a single incremented component. Because listeners can perform profile analysis even when the overall sound level of the stimuli is randomized from interval to interval, this task is thought to be a useful index of relative processing of spectral shape, rather than just sensitivity to absolute level changes. Here, we measured profile analysis across the frequency range in a group of listeners that varied widely in their hearing status. We then modeled the resulting behavioral data by decoding responses to the stimuli from computational models of the auditory nerve and inferior colliculus. We found that both hearing loss at the target frequency and increases in the target frequency were associated with poorer profile-analysis thresholds, and that these results could both be explained as the result of corresponding changes in sensitivity of temporal modulation-sensitive cells at the level of the inferior colliculus. These results suggest that key features of profile-analysis may reflect the limits of central neural tuning to temporal modulations.

Efferent projections from the brainstem to the inner ear are well-described anatomically and physiologically but their precise function remains debated. The medial olivocochlear (MOC) system and its reflex, the MOCR, have been particularly well studied. In animals, anatomical and physiological data are fine-grained and extensive and suggest an important role for the MOCR in anti-masking e.g. to improve the detection of tones in background noise. Extensive behavioral studies in human support this role, but direct linking of behavioral paradigms to the MOCR is challenging because of the difficulty in obtaining appropriate human neural measures. We developed a new approach in which mass potentials were recorded near the cochlea of normal hearing and awake human volunteers to increase the signal-to-noise (SNR) ratio, and examined whether broadband noise to the contralateral ear elicited MOCR anti-masking effects as reported in animals. Probing the mass potential to the onset of brief tones at 4 and 6 kHz, convincing anti-masking or suppressive effects consistent with the MOCR were not detected. We then changed the recording technique to examine the neural phase-locked contribution to the mass potential in response to long, low-frequency tones, and found that contralateral sound suppressed neural responses in a systematic and progressive manner. We followed up with psychophysical experiments in which we found that contralateral noise elevated detection threshold for tones up to 4 kHz. Our study provides a new way to study efferent effects in the human peripheral auditory system and shows that contralateral efferent effects are biased towards low frequencies.

O_LIAnimals with specialized hearing such as bats utilize the directionality of their hearing for complicated tasks such as navigation and foraging. The directionality of hearing can be described through the head related transfer function (HRTF). Current state of the art for obtaining the HRTF involves either direct measurement with a microphone at the eardrum, or a CT (micro computed tomography) scan to create a 3D model of the head for acoustic modelling. Both methods usually involve dead animals. C_LIO_LIWe developed a 3D photogrammetry approach to create scaled 3D models of bats with sufficient detail to simulate the HRTF using the boundary element method (BEM). We designed a setup of 28 cameras to obtain 3D models and HRTF from live awake bats. We directly compare the mesh models generated by our photogrammetry method and from CT scans as well as the simulated HRTFs from both with measurements using an in-ear microphone. C_LIO_LIGeometries of the mesh models match well between photogrammetry and CT, but with increasing errors where line of sight is compromised for photogrammetry. The resulting HRTFs are in great agreement when comparing CT and in-ear measurements to photogrammetry (correlation coefficients above 0.6). The 3D model and simulated HRTF of the live and awake bat likewise aligns well to the results from the deceased animals. C_LIO_LIPhotogrammetry is a viable alternative to CT scans for the generation of surface models of small animals. These models allow numerical modelling of HRTFs at biologically relevant frequencies. Moreover, photogrammetry allows for model generation and subsequent HRTF simulation of live, awake animals, abolishing the need for euthanasia and anesthesia. It paves the way for large scale acquisition of 3D models for various purposes including HRTFs. C_LI

Conductive hearing loss (CHL) with a normal otoscopic exam can be difficult to diagnose because routine clinical measures such as audiometric air-bone gaps (ABGs) can identify a conductive component but often cannot distinguish among specific underlying mechanical pathologies (e.g., stapes fixation versus superior canal dehiscence, which may produce similar audiograms). Wideband tympanometry (WBT) is a fast, noninvasive test that can provide additional mechanical information across a broad range of frequencies (200 Hz to 8 kHz). However, WBT metrics are influenced by variations in ear canal geometry and probe placement and can be challenging to interpret clinically. In this study, we extend prior WBT absorbance-based classification work by estimating the middle ear input impedance at the tympanic membrane (ZME), a WBT-derived metric intended to reduce ear canal effects. To estimate ZME, we fit an analog circuit model of the ear canal, middle ear, and inner ear to raw WBT data collected at tympanometric peak pressure (TPP). Data from 27 normal ears, 32 ears with superior canal dehiscence, and 38 ears with stapes fixation were analyzed. A multinomial logistic regression classifier was trained using principal component analysis (retaining 90% variance) and stratified 5-fold cross-validation with regularization. We compared feature sets based on ABGs alone, ABGs combined with absorbance, and ABGs combined with the magnitude of ZME. The combination of ABGs and the magnitude of ZME produced the best performance, achieving an overall accuracy of 85.6% compared to 80.4% for ABGs alone and 78.4% for ABGs combined with absorbance. These results suggest that incorporating model-derived middle ear impedance features with standard audiometric measures (ABGs) can improve automated pathology classification for stapes fixation and superior canal dehiscence.

In a loudness-matching paradigm, a reduction in the loudness of sounds with bandwidths less than one-half octave compared to a tone of equal sound pressure level has been observed previously for five-tone complexes at 60 dB SPL centered at 1 kHz. Here, this loudness-reduction phenomenon is explored using band-limited noise across wide ranges of frequency and level. Additionally, these measurements are simulated by a model of loudness judgement based on neural ensemble averaging (NEA), which serves as a proxy for central auditory signal processing. Multi-frequency equal-loudness contours (ELC) were measured for each of the adult participants (N=100) with pure-tone average (PTA) thresholds that ranged from normal to moderate hearing loss using a categorical-loudness-scaling (CLS) paradigm. Presentation level and center frequency of the test stimuli were determined on each trial according to a Bayesian adaptive algorithm, which enabled multi-frequency ELC estimation within about five minutes of testing. Three separate test conditions differed by stimulus type: (1) pure-tone, (2) quarter-octave noise and (3) octave noise. For comparison, loudness judgements for all three stimulus types were also simulated by the NEA model, which comprised a nonlinear, active, time-domain cochlear model with an appended stage of neural spike generation. Mid-bandwidth loudness reduction was observed to be greatest at moderate stimulus levels and frequencies near 1 kHz. This feature was approximated by the NEA model, which suggests involvement of an early stage of the central auditory system in the formation of loudness judgements.

ObjectiveIn recent years, many researchers have recommended using narrowband chirp (NBchirp) stimuli for Auditory Brainstem Response (ABR) audiometry instead of more-standard 2-1-2 cycles linear-gated tones, primarily because NBchirps often result in larger ABR wave V amplitudes. However, the acoustic frequency spectra of currently recommended NBchirps are wider than those for 2-1-2 tones, and it is currently not known whether ABRs to these NBchirps have similar (or poorer) cochlear place specificity compared to 2-1-2 tones. The current study used the high-pass noise/derived response technique to assess the cochlear regions contributing to ABRs evoked by NBchirp versus 2-1-2 stimuli. DesignA total of 24 adults with normal hearing participated (N=12 for each stimulus frequency). Stimuli were 60-dB peSPL 500- and 2000-Hz NBchirps and 2-1-2 tones mixed with high-pass (HP) filtered masking noise. The level of broadband (pink) noise required to mask the ABR was determined individually, then the broadband noise at this level was HP filtered at [1/2]-octave intervals. Three ABR replications were obtained for each condition, with recordings stopped when the residual noise level of each replication was reduced to 40 nanovolts. Derived responses (DRs) representing 1-octave-wide or [1/2]-octave-wide cochlear regions were calculated by subtracting ABRs recorded in HP noise. ResultsNon-masked ABR amplitudes in response to NBchirps were significantly larger than those to 2-1-2 stimuli, averaging 55% larger for 500 Hz and 81% larger for 2000 Hz. For both 500- and 2000-Hz stimuli, HP noise masking produced significant amplitude decreases, occurring 1 to [1/2] octave higher for ABRs to NBchirps versus 2-1-2 tones. One-octave-wide and [1/2]-octave-wide DR amplitude profiles for the ABRs to 2-1-2 tones showed good cochlear place specificity, as described in previous studies. DR results for the NBchirps were similar but showed important differences. The profiles for the 2000-Hz NBchirps showed significantly larger amplitudes in the 4- and 1-kHz DRs compared to the 2-1-2 stimuli. Many more responses were seen 1-octave away for the 2000-Hz NBchirp compared to 2-1-2 tone. DR results for 500-Hz tones showed similar patterns but differences did not quite reach statistical significance, except amplitudes to NBchirps were larger at DR354, DR500 and DR707. A measure of the width of the 1-octave-wide and [1/2]-octave-wide DR amplitude profiles (BW0.075, in Hz) showed the 500- and 2000-Hz NBchirp profiles were significantly wider (32% to 77%) compared to those for 2-1-2 stimuli. As the cochlear area able to respond decreased, wave V amplitudes to NBchirp stimuli decreased more than those for 2-1-2 stimuli, with no difference between stimuli for [1/2]-octave-wide responses. ConclusionABRs to narrowband chirps reflect wider cochlear contributions than those to 2-1-2 tones. Responses to NBchirps arise from cochlear regions as far as one octave away from the stimulus frequency. In contrast, responses to 2-1-2 tones arise from cochlear regions primarily within approximately {+/-}0.5 octaves of the stimulus frequency. Further research in individuals with hearing loss is required to determine whether the wider bandwidths for NBchirps result in threshold mis-estimations, and whether NBchirp amplitude advantages over more-standard stimuli remain with hearing loss.

Reliable hearing assessment at home can improve accessibility and reduce dependence on in-clinic testing. To be viable, home-based procedures must provide accurate results within short measurement times and remain robust to factors such as ambient noise and variable user attention. This study validated two such procedures--a Graded Response Bracketing method for pure-tone threshold estimation and a reinforced adaptive categorical loudness scaling method for loudness-growth assessment--using remote, smartphone-based testing. Fifteen young adults with normal hearing completed the tasks at home and in the laboratory. Ambient noise levels in home environments were also recorded. Test-retest reliability was assessed by repeating the home measurements on a separate occasion. Remote measurements closely matched laboratory results, with mean differences below 1 dB for threshold estimation and below 5 dB for loudness scaling. Test-retest differences obtained at home were small, remaining below 2 dB for threshold estimation and below 1 dB for loudness scaling. These findings demonstrate that smartphone-based pure-tone audiometry and loudness-scaling assessments can achieve high accuracy, efficiency, and reliability when using these procedures, provided that basic acoustic-hygiene conditions (e.g., sufficiently low ambient noise) are maintained.

Experiments on human auditory perception have shown that interaural time difference (ITD) is sufficient to generate spatial percepts, even though stimuli containing only the ITD cue are perceived as being emitted from inside the head instead of from external locations at specific azimuths. These experiments are thus interpreted as "lateralization" instead of "localization" tasks. In fact, lateralized spatial perception has been quantified using tasks in which participants have to report their estimates by selecting a putative location inside the head, or matching the perceived position to sounds with a given interaural level difference. Therefore, these estimates are made with respect to internal frames of reference, but it is unclear whether these percepts have any significance for the more ecological problem of locating an external sound source. In order to investigate the link between internalized spatial percepts and sound localization, we designed a new task in which subjects are instructed to report externalized azimuthal location for sounds containing only ITD cues. Despite the mismatch between an internalized percept having to be reported as emanating from an external location, subjects were able to estimate azimuths consistently. Furthermore, normalized estimates were indistinguishable from those obtained using traditional lateralization tasks. Our results revealed a direct relationship between perceived azimuths and ITD, which deviates from that obtained from acoustical analysis of binaural recordings, revealing estimation biases. Intriguingly, these results indicate that externalized percepts are not required for the generation of azimuthal percepts.