Selective processing of auditory evoked responses with iterative-randomized stimulation and averaging: A strategy for evaluating the time-invariant assumption

Valderrama, Joaquin T.; Torre, Ángel de la; Medina, Carlos Alberto Guerrero; Segura, José C.; Thornton, A. R. D.

doi:10.1016/j.heares.2015.12.009

Cited by 9 publications

(4 citation statements)

References 37 publications

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“…Simultaneous presentation has been a successful tool used for estimating hearing thresholds with the auditory steady state response (Luts et al 2006; Van Maanen & Stapells 2010; Sininger et al 2018). While simultaneous presentation allows for multiple responses to be recorded, randomization allows for unrestricted analysis windows, affording higher stimulation rates and better estimates of the prestimulus noise (Eysholdt & Schreiner 1982; Burkard et al 1990; Wang et al 2013; Valderrama et al 2014; Valderrama et al 2016; Polonenko & Maddox 2019). These in turn provide better estimates of signal-to-noise ratio (SNR), a key metric that dictates testing time.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Parameters for Using the Parallel Auditory Brainstem Response to Quickly Estimate Hearing Thresholds

Polonenko

Maddox

2021

Ear &Amp; Hearing

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Objectives: Timely assessments are critical to providing early intervention and better hearing and spoken language outcomes for children with hearing loss. To facilitate faster diagnostic hearing assessments in infants, the authors developed the parallel auditory brainstem response (pABR), which presents randomly timed trains of tone pips at five frequencies to each ear simultaneously. The pABR yields high-quality waveforms that are similar to the standard, single-frequency serial ABR but in a fraction of the recording time. While well-documented for standard ABRs, it is yet unknown how presentation rate and level interact to affect responses collected in parallel. Furthermore, the stimuli are yet to be calibrated to perceptual thresholds. Therefore, this study aimed to determine the optimal range of parameters for the pABR and to establish the normative stimulus level correction values for the ABR stimuli. Design: Two experiments were completed, each with a group of 20 adults (18–35 years old) with normal-hearing thresholds (≤20 dB HL) from 250 to 8000 Hz. First, pABR electroencephalographic (EEG) responses were recorded for six stimulation rates and two intensities. The changes in component wave V amplitude and latency were analyzed, as well as the time required for all responses to reach a criterion signal-to-noise ratio of 0 dB. Second, behavioral thresholds were measured for pure tones and for the pABR stimuli at each rate to determine the correction factors that relate the stimulus level in dB peSPL to perceptual thresholds in dB nHL. Results: The pABR showed some adaptation with increased stimulation rate. A wide range of rates yielded robust responses in under 15 minutes, but 40 Hz was the optimal singular presentation rate. Extending the analysis window to include later components of the response offered further time-saving advantages for the temporally broader responses to low-frequency tone pips. The perceptual thresholds to pABR stimuli changed subtly with rate, giving a relatively similar set of correction factors to convert the level of the pABR stimuli from dB peSPL to dB nHL. Conclusions: The optimal stimulation rate for the pABR is 40 Hz but using multiple rates may prove useful. Perceptual thresholds that subtly change across rate allow for a testing paradigm that easily transitions between rates, which may be useful for quickly estimating thresholds for different configurations of hearing loss. These optimized parameters facilitate expediency and effectiveness of the pABR to estimate hearing thresholds in a clinical setting.

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Section: Introductionmentioning

confidence: 99%

Optimizing Parameters for Using the Parallel Auditory Brainstem Response to Quickly Estimate Hearing Thresholds

Polonenko

Maddox

2021

Ear &Amp; Hearing

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“…Overcoming this problem requires signal-processing algorithms that enable deconvolution of overlapping auditory evoked potentials. Some examples of these algorithms are iterative randomized stimulation and averaging (IRSA, Valderrama et al, 2014 , 2016 ; de la Torre et al, 2019 ) and subspace-constrained least squares deconvolution (SC-LS, de la Torre et al, 2022 ). Importantly, IRSA enables the recording of the full-range response evoked by the fine structure of natural speech ( Valderrama et al, 2019 ), and therefore provides a novel measure that may help advance knowledge in how the human auditory system encodes speech in challenging listening scenarios—a critical step to characterize HHL with objective biomarkers.…”

Section: Discussionmentioning

confidence: 99%

The hunt for hidden hearing loss in humans: From preclinical studies to effective interventions

2022

Self Cite

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Many individuals experience hearing problems that are hidden under a normal audiogram. This not only impacts on individual sufferers, but also on clinicians who can offer little in the way of support. Animal studies using invasive methodologies have developed solid evidence for a range of pathologies underlying this hidden hearing loss (HHL), including cochlear synaptopathy, auditory nerve demyelination, elevated central gain, and neural mal-adaptation. Despite progress in pre-clinical models, evidence supporting the existence of HHL in humans remains inconclusive, and clinicians lack any non-invasive biomarkers sensitive to HHL, as well as a standardized protocol to manage hearing problems in the absence of elevated hearing thresholds. Here, we review animal models of HHL as well as the ongoing research for tools with which to diagnose and manage hearing difficulties associated with HHL. We also discuss new research opportunities facilitated by recent methodological tools that may overcome a series of barriers that have hampered meaningful progress in diagnosing and treating of HHL.

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“…Our Ad-Hoc approaches depend on identifying a characteristic dipole signature (radially or tangentially directed) in the EEG, and we verify performance only for a single dipole case. However, the characterization of EEG assuming a dipole EEG topography is ubiquitous (though with methodological considerations; [111][112][113][114]) leveraging conventional signal processing such as averaging (repeated evoked response), filtering, ICA, etc [110,[115][116][117]; mapping EEG to tES parameters based on dipoles, when they are identified in the EEG, is a rational first approximation [111][112][113][114]. The robustness of the technique across brain regions remains to be verified, but bipolar and concentric ring stimulation montages are robust across underlying anatomy [45,118].…”

Section: Discussionmentioning

confidence: 99%

A simple method for EEG guided transcranial electrical stimulation without models

Cancelli

Cottone²,

Tecchio³

et al. 2016

J. Neural Eng.

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Selective processing of auditory evoked responses with iterative-randomized stimulation and averaging: A strategy for evaluating the time-invariant assumption

Cited by 9 publications

References 37 publications

Optimizing Parameters for Using the Parallel Auditory Brainstem Response to Quickly Estimate Hearing Thresholds

Optimizing Parameters for Using the Parallel Auditory Brainstem Response to Quickly Estimate Hearing Thresholds

The hunt for hidden hearing loss in humans: From preclinical studies to effective interventions

A simple method for EEG guided transcranial electrical stimulation without models

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