While trans-tympanic needle electrodes or tympanic membrane electrodes provide larger electrophysiological responses, we favored the use of ear canal electrodes (tiptrodes) to provide better comfort to our participant. Stimuli were generated by a custom rig and transduced via ER-3A insert earphones, and data acquisition was handled by the Interacoustics Eclipse hardware and software. Furthermore, the single-neuron contribution to a gross potential derived by cross-correlating the spontaneous spike trains of single ANFs with the round-window electrical noise has a periodicity of ∼1.25 ms, which produces the spectral peak near 800 Hz ( Kiang et al., 1976 Prijs, 1986). Similarly, sound-evoked EcochGs show a spectral peak near 800 Hz ( Hancock et al., 2021), which is absent in patients with otoferlin mutations that disrupt transmitter release from the inner hair cell synapses ( Santarelli et al., 2019 Hancock et al., 2021), consistent with its association with ANF spikes. This 800 Hz neural peak dominates the spectrum of the electrical noise recorded at the round window (in quiet) and disappears when ANF spikes are pharmacologically blocked ( Dolan et al., 1990). Here, in hopes of identifying cleaner biomarkers of CND in humans, we try to improve the separation of ANF responses from the SP by filtering the EcochG waveforms into a high-pass and a low-pass component, with a cutoff near 500 Hz to isolate the 800 Hz spectral peak attributed to contributions of ANF spikes. Some of the discrepant outcomes may arise because of differences in the evoked-response metrics: e.g., baseline to N 1 peak ( Liberman et al., 2016), N 1 peak to P 1 trough ( Prendergast et al., 2017 Bramhall et al., 2019 Couth et al., 2020), or SP peak to N 1 peak ( Grant et al., 2020 Mepani et al., 2020), and/or from differences in the methods for data acquisition (including filter bandwidths) or extraction, i.e., visual inspection ( Prendergast et al., 2017 Grant et al., 2020) or mathematical modeling ( Valderrama et al., 2014 Kamerer et al., 2020 Hancock et al., 2021).Īlthough the analysis of evoked response waveforms in the time domain provides important cues regarding the generators that evoke them, contributions of ANF spikes cannot be cleanly separated from hair cell or ANF post-synaptic responses, as they can overlap in time ( Pappa et al., 2019 Lutz et al., 2022). Some have found correlations consistent with the contribution of CND to intelligibility ( Bramhall et al., 2015 Grant et al., 2020 Mepani et al., 2020 Lai and Bidelman, 2022), and others have not ( Prendergast et al., 2017 Guest et al., 2018). To pursue this idea, we and others have looked for correlations between the variability of N 1 responses and performance on a variety of difficult word-recognition tasks in normal-threshold subjects as a proxy for CND. We hypothesize that N 1 amplitude variability, at least in part, may be related to CND, i.e., the peripheral neural deficit that cannot be explained by a loss of outer hair cells. Furthermore, CND and the loss of afferent activity it produces may trigger an enhancement of central gain that further degrades performance on complex listening tasks ( Oxenham, 2016 Parthasarathy et al., 2020 Resnik and Polley, 2021). Indeed, a number of studies have linked measures of speech perception or signal-in-noise detection with neural deficits assessed by auditory brainstem responses (ABRs)/electrocochleography ( Bramhall et al., 2015 Liberman et al., 2016 Ridley et al., 2018 Grant et al., 2020 Lai and Bidelman, 2022), middle-ear muscle reflex ( Mepani et al., 2020 Shehorn et al., 2020), envelope following responses ( Mepani et al., 2021 Marcher-Rorsted et al., 2022), in vivo imaging of auditory nerve diameter ( Harris et al., 2021) or computational models ( Buran et al., 2022). However, the silencing of these neurons degrades auditory processing and may compromise speech discrimination ( Grant et al., 2022), particularly in noisy environments ( Monaghan et al., 2020 Resnik and Polley, 2021 Wu et al., 2021). This neural loss does not elevate audiometric or electrophysiological thresholds until it becomes extreme ( Woellner and Schuknecht, 1955 Chambers et al., 2016), partly because the most vulnerable cochlear neurons do not contribute to threshold detection in quiet ( Schmiedt et al., 1996 Furman et al., 2013). Studies of age-related hearing loss in animal models and human temporal bones have shown that cochlear nerve degeneration (CND) precedes hair cell loss ( Sergeyenko et al., 2013 Wu et al., 2019).
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