Modeling auditory evoked brainstem responses to transient stimuli

A Time-Saving Alternative to "Peak-Picking" Algorithms: A Gaussian Mixture Model Feature Extraction Technique for the Neurodiagnostic Auditory Brainstem Response

OBJECTIVES

The accurate and efficient analysis of neurodiagnostic auditory brainstem responses (ABR) plays a critical role in assessing auditory pathway function in human and animal research and in clinical diagnosis. Traditional analysis of the neurodiagnostic ABR analysis involves visual inspection of the waveform and manually marking peaks and troughs. Visual inspection is a tedious and time-consuming task, especially in research where there may be hundreds or thousands of waveforms to analyze. "Peak-picking" algorithms have made this task faster; however, they are prone to the same errors as visual inspection. A Gaussian mixture model-based feature extraction technique (GMM-FET) is a descriptive model of ABR morphology and an alternative to peak-picking algorithms. The GMM-FET is capable of modeling multiple waves and accounting for wave interactions, compared with other template-matching approaches that fit single waves.

DESIGN

The present study is a secondary analysis applying the GMM-FET to 321 ABRs from adult humans from 2 datasets using different stimuli and recording parameters. Goodness-of-fit of the GMM-FET to waves I and V and surrounding waves, that is, the summating potential and waves IV and VI, was assessed, and latency and amplitude estimations by the GMM-FET were compared with estimations from visual inspection.

RESULTS

The GMM-FET had a similar success rate to visual inspection in extracting peak latency and amplitude, and there was low RMS error and high intraclass correlation between the model and response waveform. Mean peak latency differences between the GMM-FET and visual inspection were small, suggesting the two methods chose the same peak in the majority of waveforms. The GMM-FET estimated wave I amplitudes within 0.12 µV of visual inspection, but estimated larger wave V amplitudes than visual inspection.

CONCLUSIONS

The results suggest the GMM-FET is an appropriate method for extracting peak latencies and amplitudes for neurodiagnostic analysis of ABR waves I and V.

Echolocating bats show species-specific variation in susceptibility to acoustic forward masking

Echolocating bats rely on precise auditory temporal processing to detect echoes generated by calls that may be emitted at rates reaching 150-200 Hz. High call rates can introduce forward masking perceptual effects that interfere with echo detection; however, bats may have evolved specializations to prevent repetition suppression of auditory responses and facilitate detection of sounds separated by brief intervals. Recovery of the auditory brainstem response (ABR) was assessed in two species that differ in the temporal characteristics of their echolocation behaviors: Eptesicus fuscus, which uses high call rates to capture prey, and Carollia perspicillata, which uses lower call rates to avoid obstacles and forage for fruit. We observed significant species differences in the effects of forward masking on ABR wave 1, in which E. fuscus maintained comparable ABR wave 1 amplitudes when stimulated at intervals of <3 ms, whereas post-stimulus recovery in C. perspicillata required 12 ms. When the intensity of the second stimulus was reduced by 20-30 dB relative to the first, however, C. perspicillata showed greater recovery of wave 1 amplitudes. The results demonstrate that species differences in temporal resolution are established at early levels of the auditory pathway and that these differences reflect auditory processing requirements of species-specific echolocation behaviors.

Single neuron contributions to the auditory brainstem EEG

The auditory brainstem response (ABR) is an acoustically evoked EEG potential that is an important diagnostic tool for hearing loss, especially in newborns. The ABR originates from the response sequence of auditory brainstem nuclei, and a click-evoked ABR typically shows three positive peaks ('waves') within the first six milliseconds. However, an assignment of the waves of the ABR to specific sources is difficult, and a quantification of contributions to the ABR waves is not available. Here, we exploit the large size and physical separation of the barn owl first-order cochlear nucleus magnocellularis (NM) to estimate single-cell contributions to the ABR. We simultaneously recorded NM neurons' spikes and the EEG, and found that ≳ 5, 000 spontaneous single-cell spikes are necessary to isolate a significant spike-triggered average response at the EEG electrode. An average single-neuron contribution to the ABR was predicted by convolving the spike-triggered average with the cell's peri-stimulus time histogram. Amplitudes of predicted contributions of single NM cells typically reached 32.9 ± 1.1 nV (mean ± SE, range: 2.5 - 162.7 nV), or 0.07 ± 0.02% (median ± SE range: 0.01 - 4.0%) of the ABR amplitude. The time of the predicted peak coincided best with the peak of the ABR wave II, and this coincidence was independent of the click sound level. Our results suggest that wave II of the ABR is shaped by a small fraction of NM units.

Predicting early auditory evoked potentials using a computational model of auditory-nerve processing

Non-invasive electrophysiological measures, such as auditory evoked potentials (AEPs), play a crucial role in diagnosing auditory pathology. However, the relationship between AEP morphology and cochlear degeneration remains complex and not well understood. Dau [J. Acoust. Soc. Am. 113, 936-950 (2003)] proposed a computational framework for modeling AEPs that utilized a nonlinear auditory-nerve (AN) model followed by a linear unitary response function. While the model captured some important features of the measured AEPs, it also exhibited several discrepancies in response patterns compared to the actual measurements. In this study, an enhanced AEP modeling framework is presented, incorporating an improved AN model, and the conclusions from the original study were reevaluated. Simulation results with transient and sustained stimuli demonstrated accurate auditory brainstem responses (ABRs) and frequency-following responses (FFRs) as a function of stimulation level, although wave-V latencies remained too short, similar to the original study. When compared to physiological responses in animals, the revised model framework showed a more accurate balance between the contributions of auditory-nerve fibers (ANFs) at on- and off-frequency regions to the predicted FFRs. These findings emphasize the importance of cochlear processing in brainstem potentials. This framework may provide a valuable tool for assessing human AN models and simulating AEPs for various subtypes of peripheral pathologies, offering opportunities for research and clinical applications.

Computational modeling of the human compound action potential

The auditory nerve (AN) compound action potential (CAP) is an important tool for assessing auditory disorders and monitoring the health of the auditory periphery during surgical procedures. The CAP has been mathematically conceptualized as the convolution of a unit response (UR) waveform with the firing rate of a population of AN fibers. Here, an approach for predicting experimentally recorded CAPs in humans is proposed, which involves the use of human-based computational models to simulate AN activity. CAPs elicited by clicks, chirps, and amplitude-modulated carriers were simulated and compared with empirically recorded CAPs from human subjects. In addition, narrowband CAPs derived from noise-masked clicks and tone bursts were simulated. Many morphological, temporal, and spectral aspects of human CAPs were captured by the simulations for all stimuli tested. These findings support the use of model simulations of the human CAP to refine existing human-based models of the auditory periphery, aid in the design and analysis of auditory experiments, and predict the effects of hearing loss, synaptopathy, and other auditory disorders on the human CAP.

Comparisons of auditory brainstem response elicited by compound click-sawtooths sound and synthetic consonant-vowel /da/1

The auditory brainstem response to complex sounds (cABR) could be evoked using speech sounds such as the 40-ms synthetic consonant-vowel syllable /da/ (CV-da) that was commonly used in basic and clinical research. cABR consists of responses to formant energy as well as the energy of fundamental frequency. The co-existence of the two energy makes cABR a mixed response. We introduced a new stimulus of click-sawtooths (CSW) with similar time-lock patterns but without formant or harmonic energy. Ten young healthy volunteers were recruited and the cABRs of CV-da and CSW of their 20 ears were acquired. The response latencies, amplitudes, and frequency-domain analytic results were compared pairwisely between stimuli. The response amplitudes were significantly greater for CSW and the latencies were significantly shorter for CSW. The latency-intensity functions were also greater for CSW. For CSW, adjustments of energy component can be made without causing biased changes to the other. CSW may be used in future basic research and clinical applications.

A comparative study of eight human auditory models of monaural processing

A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.

Age-related reduction in frequency-following responses as a potential marker of cochlear neural degeneration

Healthy aging may be associated with neural degeneration in the cochlea even before clinical hearing loss emerges. Reduction in frequency-following responses (FFRs) to tonal carriers in older clinically normal-hearing listeners has previously been reported, and has been argued to reflect an age-dependent decline in temporal processing in the central auditory system. Alternatively, age-dependent loss of auditory nerve fibers (ANFs) may have little effect on audiometric sensitivity and yet compromise the precision of neural phase-locking relying on joint activity across populations of fibers. This peripheral loss may, in turn, contribute to reduced neural synchrony in the brainstem as reflected in the FFR. Here, we combined human electrophysiology and auditory nerve (AN) modeling to investigate whether age-related changes in the FFR would be consistent with peripheral neural degeneration. FFRs elicited by pure tones and frequency sweeps at carrier frequencies between 200 and 1200 Hz were obtained in older (ages 48-76) and younger (ages 20-30) listeners, both groups having clinically normal audiometric thresholds up to 6 kHz. The same stimuli were presented to a computational model of the AN in which age-related loss of hair cells or ANFs was modelled using human histopathological data. In the older human listeners, the measured FFRs to both sweeps and pure tones were found to be reduced across the carrier frequencies examined. These FFR reductions were consistent with model simulations of age-related ANF loss. In model simulations, the phase-locked response produced by the population of remaining fibers decreased proportionally with increasing loss of the ANFs. Basal-turn loss of inner hair cells also reduced synchronous activity at lower frequencies, albeit to a lesser degree. Model simulations of age-related threshold elevation further indicated that outer hair cell dysfunction had no negative effect on phase-locked AN responses. These results are consistent with a peripheral source of the FFR reductions observed in older normal-hearing listeners, and indicate that FFRs at lower carrier frequencies may potentially be a sensitive marker of peripheral neural degeneration.

Behavioral and subcortical signatures of musical expertise in Mandarin Chinese speakers

Both musical training and native language have been shown to have experience-based plastic effects on auditory processing. However, the combined effects within individuals are unclear. Recent research suggests that musical training and tone language speaking are not clearly additive in their effects on processing of auditory features and that there may be a disconnect between perceptual and neural signatures of auditory feature processing. The literature has only recently begun to investigate the effects of musical expertise on basic auditory processing for different linguistic groups. This work provides a profile of primary auditory feature discrimination for Mandarin speaking musicians and nonmusicians. The musicians showed enhanced perceptual discrimination for both frequency and duration as well as enhanced duration discrimination in a multifeature discrimination task, compared to nonmusicians. However, there were no differences between the groups in duration processing of nonspeech sounds at a subcortical level or in subcortical frequency representation of a nonnative tone contour, for f_o or for the first or second formant region. The results indicate that musical expertise provides a cognitive, but not subcortical, advantage in a population of Mandarin speakers.

Modeling signal propagation in the human cochlea

The level-dependent component of the latency of human auditory brainstem responses (ABR) to tonebursts decreases by about 38% for every 20-dB increase in stimulus level over a wide range of both frequency and level [Neely, Norton, Gorga, and Jesteadt (1998). J. Acoust. Soc. Am. 31, 87-97]. This level-dependence has now been simulated in an active, nonlinear, transmission-line model of cochlear mechanics combined with an adaptation stage. The micromechanics in this model are similar to previous models except that a dual role is proposed for the tectorial membrane (TM): (1) passive sharpening the tuning of sensory-cell inputs (relative to basilar-membrane vibrations) and (2) providing an optimal phase shift (relative to basilar-membrane vibrations) of outer-hair-cell feedback forces, so that amplification is restricted to a limited range of frequencies. The adaptation stage, which represents synaptic adaptation of neural signals, contributes to the latency level-dependence more at low frequencies than at high frequencies. Compression in this model spans the range of audible sound levels with a compression ratio of about 2:1. With further development, the proposed model of cochlear micromechanics could be useful both (1) as a front-end to functional models of the auditory system and (2) as a foundation for understanding the physiological basis of cochlear amplification.

A comparative study of seven human cochlear filter models

Auditory models have been developed for decades to simulate characteristics of the human auditory system, but it is often unknown how well auditory models compare to each other or perform in tasks they were not primarily designed for. This study systematically analyzes predictions of seven publicly-available cochlear filter models in response to a fixed set of stimuli to assess their capabilities of reproducing key aspects of human cochlear mechanics. The following features were assessed at frequencies of 0.5, 1, 2, 4, and 8 kHz: cochlear excitation patterns, nonlinear response growth, frequency selectivity, group delays, signal-in-noise processing, and amplitude modulation representation. For each task, the simulations were compared to available physiological data recorded in guinea pigs and gerbils as well as to human psychoacoustics data. The presented results provide application-oriented users with comprehensive information on the advantages, limitations and computation costs of these seven mainstream cochlear filter models.

The neural encoding of formant frequencies contributing to vowel identification in normal-hearing listeners

Even though speech signals trigger coding in the cochlea to convey speech information to the central auditory structures, little is known about the neural mechanisms involved in such processes. The purpose of this study was to understand the encoding of formant cues and how it relates to vowel recognition in listeners. Neural representations of formants may differ across listeners; however, it was hypothesized that neural patterns could still predict vowel recognition. To test the hypothesis, the frequency-following response (FFR) and vowel recognition were obtained from 38 normal-hearing listeners using four different vowels, allowing direct comparisons between behavioral and neural data in the same individuals. FFR was employed because it provides an objective and physiological measure of neural activity that can reflect formant encoding. A mathematical model was used to describe vowel confusion patterns based on the neural responses to vowel formant cues. The major findings were (1) there were large variations in the accuracy of vowel formant encoding across listeners as indexed by the FFR, (2) these variations were systematically related to vowel recognition performance, and (3) the mathematical model of vowel identification was successful in predicting good vs poor vowel identification performers based exclusively on physiological data.

Tone-burst auditory brainstem response wave V latencies in normal-hearing and hearing-impaired ears

The metric used to equate stimulus level [sound pressure level (SPL) or sensation level (SL)] between ears with normal hearing (NH) and ears with hearing loss (HL) in comparisons of auditory function can influence interpretation of results. When stimulus level is equated in dB SL, higher SPLs are presented to ears with HL due to their reduced sensitivity. As a result, it may be difficult to determine if differences between ears with NH and ears with HL are due to cochlear pathology or level-dependent changes in cochlear mechanics. To the extent that level-dependent changes in cochlear mechanics contribute to auditory brainstem response latencies, comparisons between normal and pathologic ears may depend on the stimulus levels at which comparisons are made. To test this hypothesis, wave V latencies were measured in 16 NH ears and 15 ears with mild-to-moderate HL. When stimulus levels were equated in SL, latencies were shorter in HL ears. However, latencies were similar for NH and HL ears when stimulus levels were equated in SPL. These observations demonstrate that the effect of stimulus level on wave V latency is large relative to the effect of HL, at least in cases of mild-to-moderate HL.

Functional modeling of the human auditory brainstem response to broadband stimulation

Population responses such as the auditory brainstem response (ABR) are commonly used for hearing screening, but the relationship between single-unit physiology and scalp-recorded population responses are not well understood. Computational models that integrate physiologically realistic models of single-unit auditory-nerve (AN), cochlear nucleus (CN) and inferior colliculus (IC) cells with models of broadband peripheral excitation can be used to simulate ABRs and thereby link detailed knowledge of animal physiology to human applications. Existing functional ABR models fail to capture the empirically observed 1.2-2 ms ABR wave-V latency-vs-intensity decrease that is thought to arise from level-dependent changes in cochlear excitation and firing synchrony across different tonotopic sections. This paper proposes an approach where level-dependent cochlear excitation patterns, which reflect human cochlear filter tuning parameters, drive AN fibers to yield realistic level-dependent properties of the ABR wave-V. The number of free model parameters is minimal, producing a model in which various sources of hearing-impairment can easily be simulated on an individualized and frequency-dependent basis. The model fits latency-vs-intensity functions observed in human ABRs and otoacoustic emissions while maintaining rate-level and threshold characteristics of single-unit AN fibers. The simulations help to reveal which tonotopic regions dominate ABR waveform peaks at different stimulus intensities.

Relating the Variability of Tone-Burst Otoacoustic Emission and Auditory Brainstem Response Latencies to the Underlying Cochlear Mechanics

Forward and reverse cochlear latency and its relation to the frequency tuning of the auditory filters can be assessed using tone bursts (TBs). Otoacoustic emissions (TBOAEs) estimate the cochlear roundtrip time, while auditory brainstem responses (ABRs) to the same stimuli aim at measuring the auditory filter buildup time. Latency ratios are generally close to two and controversy exists about the relationship of this ratio to cochlear mechanics. We explored why the two methods provide different estimates of filter buildup time, and ratios with large inter-subject variability, using a time-domain model for OAEs and ABRs. We compared latencies for twenty models, in which all parameters but the cochlear irregularities responsible for reflection-source OAEs were identical, and found that TBOAE latencies were much more variable than ABR latencies. Multiple reflection-sources generated within the evoking stimulus bandwidth were found to shape the TBOAE envelope and complicate the interpretation of TBOAE latency and TBOAE/ABR ratios in terms of auditory filter tuning.

Cochlear neuropathy and the coding of supra-threshold sound

Many listeners with hearing thresholds within the clinically normal range nonetheless complain of difficulty hearing in everyday settings and understanding speech in noise. Converging evidence from human and animal studies points to one potential source of such difficulties: differences in the fidelity with which supra-threshold sound is encoded in the early portions of the auditory pathway. Measures of auditory subcortical steady-state responses (SSSRs) in humans and animals support the idea that the temporal precision of the early auditory representation can be poor even when hearing thresholds are normal. In humans with normal hearing thresholds (NHTs), paradigms that require listeners to make use of the detailed spectro-temporal structure of supra-threshold sound, such as selective attention and discrimination of frequency modulation (FM), reveal individual differences that correlate with subcortical temporal coding precision. Animal studies show that noise exposure and aging can cause a loss of a large percentage of auditory nerve fibers (ANFs) without any significant change in measured audiograms. Here, we argue that cochlear neuropathy may reduce encoding precision of supra-threshold sound, and that this manifests both behaviorally and in SSSRs in humans. Furthermore, recent studies suggest that noise-induced neuropathy may be selective for higher-threshold, lower-spontaneous-rate nerve fibers. Based on our hypothesis, we suggest some approaches that may yield particularly sensitive, objective measures of supra-threshold coding deficits that arise due to neuropathy. Finally, we comment on the potential clinical significance of these ideas and identify areas for future investigation.

Rapid acquisition of auditory subcortical steady state responses using multichannel recordings

OBJECTIVE

Auditory subcortical steady state responses (SSSRs), also known as frequency following responses (FFRs), provide a non-invasive measure of phase-locked neural responses to acoustic and cochlear-induced periodicities. SSSRs have been used both clinically and in basic neurophysiological investigation of auditory function. SSSR data acquisition typically involves thousands of presentations of each stimulus type, sometimes in two polarities, with acquisition times often exceeding an hour per subject. Here, we present a novel approach to reduce the data acquisition times significantly.

METHODS

Because the sources of the SSSR are deep compared to the primary noise sources, namely background spontaneous cortical activity, the SSSR varies more smoothly over the scalp than the noise. We exploit this property and extract SSSRs efficiently, using multichannel recordings and an eigendecomposition of the complex cross-channel spectral density matrix.

RESULTS

Our proposed method yields SNR improvement exceeding a factor of 3 compared to traditional single-channel methods.

CONCLUSIONS

It is possible to reduce data acquisition times for SSSRs significantly with our approach.

SIGNIFICANCE

The proposed method allows SSSRs to be recorded for several stimulus conditions within a single session and also makes it possible to acquire both SSSRs and cortical EEG responses without increasing the session length.

Latency of tone-burst-evoked auditory brain stem responses and otoacoustic emissions: level, frequency, and rise-time effects

Simultaneous measurement of auditory brain stem response (ABR) and otoacoustic emission (OAE) delays may provide insights into effects of level, frequency, and stimulus rise-time on cochlear delay. Tone-burst-evoked ABRs and OAEs (TBOAEs) were measured simultaneously in normal-hearing human subjects. Stimuli included a wide range of frequencies (0.5-8 kHz), levels (20-90 dB SPL), and tone-burst rise times. ABR latencies have orderly dependence on these three parameters, similar to previously reported data by Gorga et al. [J. Speech Hear. Res. 31, 87-97 (1988)]. Level dependence of ABR and TBOAE latencies was similar across a wide range of stimulus conditions. At mid-frequencies, frequency dependence of ABR and TBOAE latencies were similar. The dependence of ABR latency on both rise time and level was significant; however, the interaction was not significant, suggesting independent effects. Comparison between ABR and TBOAE latencies reveals that the ratio of TBOAE latency to ABR forward latency (the level-dependent component of ABR total latency) is close to one below 1.5 kHz, but greater than two above 1.5 kHz. Despite the fact that the current experiment was designed to test compatibility with models of reverse-wave propagation, existing models do not completely explain the current data.

Quantifying attentional modulation of auditory-evoked cortical responses from single-trial electroencephalography

Selective auditory attention is essential for human listeners to be able to communicate in multi-source environments. Selective attention is known to modulate the neural representation of the auditory scene, boosting the representation of a target sound relative to the background, but the strength of this modulation, and the mechanisms contributing to it, are not well understood. Here, listeners performed a behavioral experiment demanding sustained, focused spatial auditory attention while we measured cortical responses using electroencephalography (EEG). We presented three concurrent melodic streams; listeners were asked to attend and analyze the melodic contour of one of the streams, randomly selected from trial to trial. In a control task, listeners heard the same sound mixtures, but performed the contour judgment task on a series of visual arrows, ignoring all auditory streams. We found that the cortical responses could be fit as weighted sum of event-related potentials evoked by the stimulus onsets in the competing streams. The weighting to a given stream was roughly 10 dB higher when it was attended compared to when another auditory stream was attended; during the visual task, the auditory gains were intermediate. We then used a template-matching classification scheme to classify single-trial EEG results. We found that in all subjects, we could determine which stream the subject was attending significantly better than by chance. By directly quantifying the effect of selective attention on auditory cortical responses, these results reveal that focused auditory attention both suppresses the response to an unattended stream and enhances the response to an attended stream. The single-trial classification results add to the growing body of literature suggesting that auditory attentional modulation is sufficiently robust that it could be used as a control mechanism in brain-computer interfaces (BCIs).