- The objective of this study was to improve the ability to detect cochlear nerve degeneration from auditory brainstem responses in humans
- During electrocochleography, 122 healthy volunteers completed two difficult word recognition tests, used as a proxy for cochlear nerve degeneration (which can degrade auditory processing and compromise speech discrimination)
- Electrocochleographic waveforms were filtered into high-pass and low-pass components, which separated auditory nerve fiber (ANF) responses from the hair-cell summating potential
- N1*, the trough-to-peak amplitude within the first 1.5 milliseconds, was defined as a new objective measure of ANF response and identified individuals who performed best on either word test
- If animal studies confirm that this approach to electrocochleography separates the neural spiking component from other generators, it should be useful in searching for additional biomarkers of cochlear nerve degeneration in humans
Cochlear nerve degeneration (CND) cannot be detected from audiometric or electrophysiological thresholds until it becomes extreme. In animals, it can be inferred from auditory brainstem responses—a typical response to high-level clicks includes a prominent negative peak at about one millisecond, called N1, and an inflection on its rising phase, called the hair-cell summating potential (SP).
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N1 is dominated by spikes of auditory nerve fibers (ANFs), whereas the SP includes contributions from hair cell receptor potentials and ANF post-synaptic potentials.
In humans, detecting CND from auditory brainstem responses is more challenging. The recordings are noisy, N1 is small when using conventional electrodes, and contributions of ANF spikes can't be cleanly separated from hair cells or ANF post-synaptic responses, because they sometimes overlap in time.
Stéphane F. Maison, AuD, PhD, CCC-A, principal investigator in the Eaton–Peabody Laboratories at Mass Eye and Ear, and colleagues have defined a new N1 measure that's well correlated with performance on difficult word recognition tasks, which were used as a proxy for CND. They report their findings in JASA Express Letters.
The study participants were 122 healthy volunteers aged 18 to 63, with no history of ear or hearing problems. They performed two sets of word recognition tests during electrocochleography (measurement of auditory brainstem responses from electrodes placed in the ear canal):
- A list of 50 phonemically balanced words from the Northwestern University Auditory Test No. 6, presented at 55 dB hearing level with time compression (65% reduced duration) and added reverberation (0.3-second echo)
- A modified version of the QuickSIN Speech-in-Noise test (Etymotic Research, Inc.): four lists of six sentences with five keywords per sentence in the presence of a four-talker babble noise at decreasing signal-to-noise ratio
Each electrocochleographic waveform was filtered into a high-pass and a low-pass component, with a cutoff of 470-Hz to isolate the 800-Hz spectral peak attributed to contributions of ANF spikes. The goal was to separate contributions of N1 from those of SP.
Hypothesizing that neural spikes would dominate the high-pass filtered waveform, the researchers defined N1*, the trough-to-peak amplitude within the first 1.5 milliseconds, as a new objective measure of ANF response. SP* amplitude was defined as the baseline-to-peak amplitude.
On both word tests, mean SP* was similar between best and worst performers (those who scored above the 75th percentile and below the 25th percentile, respectively). In contrast, significantly larger N1* amplitudes were seen for individuals who performed best on either test.
The earliest contribution of ANF spiking overlapped in time with the SP as conventionally measured and was opposite in phase. In previous research into CND biomarkers, classic electrocochleography showed a strong association between higher SP amplitudes and lower word scores. With the new metric, that paradoxical correlation disappeared.
This new approach to electrocochleographic analysis can be carried out objectively under computer control and may more cleanly separate the neural spiking component from other cellular generators. It may be useful in the search for additional CND biomarkers.
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