Accuracy of averaged auditory brainstem response amplitude and latency estimates

Abstract

Objective: The aims were to 1) establish which of the four algorithms for estimating residual noise level and signal-to-noise ratio (SNR) in auditory brainstem responses (ABRs) perform better in terms of post-average wave-V peak latency and amplitude errors and 2) determine whether SNR or noise floor is a better stop criterion where the outcome measure is peak latency or amplitude. Design: The performance of the algorithms was evaluated by numerical simulations using an ABR template combined with electroencephalographic (EEG) recordings obtained without sound stimulus. The suitability of a fixed SNR versus a fixed noise floor stop criterion was assessed when variations in the wave-V waveform shape reflecting inter-subject variation was introduced. Study sample: Over 100 hours of raw EEG noise was recorded from 17 adult subjects, under different conditions (e.g. sleep or movement). Results: ABR feature accuracy was similar for the four algorithms. However, it was shown that a fixed noise floor leads to higher ABR wave-V amplitude accuracy; conversely, a fixed SNR yields higher wave-V latency accuracy. Conclusion: Similar performance suggests the use of the less computationally complex algorithms. Different stop criteria are recommended if the ABR peak latency or the amplitude is the outcome measure of interest.

Towards a differential diagnosis of cochlear synaptopathy and outer-hair-cell deficits in mixed sensorineural hearing loss pathologies

“…However, wave-I is small in humans and might yield unreliable measurements for the vertex electrode configuration (Plack et al, 2016; Mehraei et al, 2016; Garrett and Verhulst, 2019). For this reason, we focus on how sensorineural hearing loss affects the ABR wave-V, which can be recorded robustly in NH and HI humans (Gorga et al, 1985; Verhulst et al, 2016; Madsen et al, 2018; Garrett and Verhulst, 2019). The ABR wave-V for NH listeners occurs 5-7 ms after sound onset and reflects the ascending input activity to the IC (Møller and Burgess, 1986; Melcher and Kiang, 1996; Picton, 2010; Bidelman, 2015).…”

“…These simulations illustrate how EHF OHC damage can influence the ratio using a model which simulated CN and IC neuron transfer functions (Nelson and Carney, 2004) Based on the above arguments, and in the absence of a full physiological understanding of homeostatic gain processes and their effect on ABR waves, we refrained from introducing this concept in our model simulations. We also opted to use SNHL maps on the basis of the ABR wave-V because this response can be recorded reliably in NH and HI human listeners with higher signal-tonoise ratio than the ABR wave-I in the vertex electrode configuration (e.g., Gorga et al, 1985;Madsen et al, 2018;Garrett and Verhulst, 2019). Even if future physiology studies confirm a compensating brainstem or midbrain gain mechanism after synaptopathy, its potential effect is expected to be minimal for our SNHL maps as we consider the ABR wave-V amplitude in a ratio with the EFR P magnitude.…”

Objective measures for detecting the auditory brainstem response: comparisons of specificity, sensitivity and detection time

“…Recordings of spontaneous EEG background activity (no stimulus was used) were previously 185 collected by Madsen et al (2017) and Madsen (2010) from 17 subjects (12 male and 5 female) under 186 four conditions. The conditions were (i) asleep, where the subjects were asked to try and fall asleep, 187 though sleep was not confirmed, (ii) still, where the subjects were instructed to lie still with their eyes 188…”

Real-time Hearing Threshold Determination of Auditory Brainstem Responses by Cross-correlation Analysis

“…Such standardized data will benefit machine-learning-based approaches by minimizing annotation discrepancy in the training data (McKearney and MacKinnon, 2019). Second, when to stop averaging is an important decision during ABR recording (Don and Elberling, 1996; Madsen et al, 2018), the new method makes the ABR test more efficient by avoiding prolonged acquisition and redundant recordings.…”