The University of Arizona Human Subjects Protection Program approved the following methods which were carried out with written, informed consent from all subjects. Eighteen adult participants without history of neurologic or otologic disease were enrolled in the study; however, due to attrition, 14 subjects (average age 22.25 years; 10 females) completed all six testing sessions. Otoscopy examinations found that all ear canals were free of excess cerumen and that tympanic membranes (TMs) appeared healthy in all subjects. Participants had normal tympanograms bilaterally, defined as ear canal volume of 0.6–1.5 cc and peak-compensated static admittance between 0.3 and 1.4 mL (Margolis and Heller, 1987), and contralateral acoustic reflex thresholds to 1–10 kHz BBN ≥70 dB SPL, measured using conventional admittance methods (Sun, 2008). The latter requirement was to mitigate the possible involvement of middle ear muscle contractions during MOC inhibition measurements, although others have shown that acoustic reflex thresholds can be lower when measured using more sensitive techniques (e.g., Zhao and Dhar, 2010; Lichtenhan et al., 2016). Air conduction hearing thresholds from 0.25 to 8 kHz were within normal limits (≤25 dB HL) bilaterally for all subjects.

With few exceptions, chirps produced larger raw peak amplitudes than clicks in individual ears, as evidenced by chirp-to-click CAP amplitude ratios (Figure 1). The size of the chirp/click amplitude ratio differed between subjects and showed a range of 0.76–4.22 across all stimulus levels. For most participants, the amplitude ratios decreased slightly as level was increased. Note that click-evoked responses at 50 dB ppeSPL were separable from the noise floor in all three test sessions in only 9 of the 14 participants; thus, amplitude ratios were calculated for only 9 participants at this level.

The mean raw amplitudes of chirp-evoked CAPs without CAS were larger than those for clicks at each level tested (Figure 2). Paired t-tests with Bonferroni corrections for multiple comparisons (α = 0.0125) revealed that these differences were significant at 50 [t₍₈₎ = −2.85, p = 0.008], 60 [t₍₁₃₎ = −7.19, p = 0.0009], 70 [t₍₁₃₎ = −4.28, p = 0.001], and 80 dB ppeSPL [t₍₁₃₎ = −2.57, p = 0.007].

Representative chirp- and click-evoked CAP waveforms without and with CAS from a randomly selected participant are plotted in Figure 3. This figure demonstrates three pertinent observations that were noted in most subjects including: (1) the overall amplitude advantage of chirps, especially at lower stimulus levels, (2) the small reductions in chirp- and click-evoked CAP amplitudes with CAS, and (3) the stability of pre-stimulus baselines prior to the N1 peak of the CAP.

Figure 4 displays chirp and click average level-series functions across all subjects and sessions without and with CAS. Level-series functions are expressed in both normalized and raw amplitudes for each stimulus type. For chirps, the average coefficient of variation across four stimulus levels and two noise conditions was 45% when expressed in raw amplitude and 20% when expressed in normalized amplitude; this mean difference was significant [t₍₁₄₎ = 3.46, p = 0.0038]. For clicks, the average coefficient of variation was 47% when expressed in raw amplitude and 29% when expressed in normalized amplitude, which was also a significant mean difference [t₍₁₄₎ = 2.86, p = 0.013]. Thus, we used the less-variable measurements expressed in normalized amplitude for subsequent MOC reflex inhibition of CAP analyses.

The chirp generated larger CAP amplitudes at each stimulus level in most subjects; however, the size of this advantage varied considerably across subjects. This finding is consistent with the observations of Chertoff et al. (2010; see Figure 3) who used higher presentation levels than the present study. Inter-subject differences in the chirp advantage may be related to multiple factors. First, the chirp used in the present study and by Chertoff et al. (2010) related frequency to basilar membrane delay using derived band CAP latencies from 15 normally hearing subjects reported by Eggermont (1979). Subject characteristics, such as sex, were not reported in that study, but it has been inferred that sex differences in cochlear length may affect basilar membrane delays and therefore the degree to which neural responses are synchronized (e.g., Don et al., 1993, 1994). With the current participant pool of 10 females and 4 males, it is possible that the chirp was not optimized for individual ears based on these differences. One way to quickly construct a CAP chirp that is more optimized for an individual ear than a click may be to use basilar membrane delay estimates from OAEs, as derived-band CAP masking procedures are time consuming. Secondly, some authors have encouraged the use of chirps that are optimized for different presentation levels (Elberling and Don, 2010; Elberling et al., 2010; Kristensen and Elberling, 2012), suggesting that cochlear frequency place maps do not scale simply with level. Our use of a chained stimulus paradigm, which allows for random level presentation of a single stimulus file, did not provide the flexibility to use multiple chirps optimized for different levels in this investigation.

The chirp advantage reported here and by Chertoff et al. (2010) suggests that chirps may also be a useful tool in studying animal and human synaptopathy—a pathology in which noise exposure predominately insults high threshold auditory nerve fibers but spares low threshold fibers and hair cells (Kujawa and Liberman, 2009). Synaptopathy has been postulated as the basis of severe hearing difficulties in patients with normal audiograms (i.e., “hidden hearing loss”) and may also be involved in the generation of tinnitus (e.g., Schaette and McAlpine, 2011). The synaptopathy “phenotype” in animal models presents as significantly reduced CAP amplitudes evoked by suprathreshold sounds in the presence of normal (electrophysiologic) audiometric thresholds and OAE responses. Because chirp-evoked CAPs are larger and represent the summed activity from auditory nerve fibers along the length of the basilar membrane, they may provide a more sensitive measure of synaptopathy. Further, narrowband chirps tailored to evoke CAPs may be even more sensitive to synaptopathy in distinct cochlear regions.

Our findings suggest that chirps may be more suitable than clicks in studying the neural consequences of MOC reflex inhibition for a few reasons. First, chirp-evoked CAPs were larger than clicks even at the lowest stimulus level, which allowed for more accurate N1 peak identification in quiet and with CAS conditions (e.g., compare 60 dB ppeSPL waveforms for chirps and clicks in Figure 3). Since OHCs are more potently inhibited by the MOC reflex at low input levels, using a chirp may allow for more accurate estimates of MOC effects in this range. Because chirp-evoked CAPs reflect the summed activity over broader cochlear regions, they may also be more sensitive to the summated effects of MOC fibers than click-evoked CAPs, which mainly reflect neural synchrony from fibers innervating the cochlear base (Don and Eggermont, 1978). Second, the variability of CAP inhibition for chirps was smaller relative to clicks on both amplitude reduction and effective attenuation measurement scales (Figures 5, 6A,B). This finding suggests that chirps may be more sensitive to “true” physiologic changes attributable to MOC reflex activation than clicks. It is important to note, however, that chirp and click CAP effective attenuation was calculated from relatively weak linear regression fits to group data, which may have been caused by individual differences in both level-series function contours and magnitude of inhibition. An analysis of individual data using the same method resulted in even poorer linear fits due to the fewer data points in the models. Thus, a limitation of our work is that we were unable to reliably resolve efferent inhibition of CAPs at the single-subject level, which is of interest in studying individual variation in MOC function and in understanding the predictive relationships between pre-neural and neural efferent assays. This issue may have been resolved by focusing recording time on obtaining more response averages to fewer low-intensity input levels (Lichtenhan et al., 2016); however, an advantage of acquiring a level-series function spanning 40 dB was that CAS effects on CAPs evoked by different stimulus levels could be evaluated.

Involvement of the middle ear muscle reflex is always a consideration in MOC reflex experiments, as CAS can activate both mechanisms. The observed CAP amplitude reductions with CAS were unlikely to be the consequence of “sub-threshold” middle ear compliance changes from activation of the middle ear acoustic reflex because such a change would be expected to reduce responses to all input levels of the level-series function. In contrast, the CAS-induced changes in our data were primarily at low input levels, which is suggestive of changes in OHC function. Nevertheless, the possibility of middle ear muscle involvement cannot be fully ruled out, as some reports indicate that standard measures of acoustic reflex threshold, like the one used in our screening protocol, may overestimate the level at which the stapedius muscle is activated by CAS (Feeney and Keefe, 2001; Zhao and Dhar, 2010).

OAE measurements are used far more often as an indirect assay of MOC reflex effects than CAP amplitudes, as they require less time to collect and are less inherently variable than electrophysiologic techniques (see Figure 6). This difference is presumably because far-field CAP recordings are influenced by more sources of noise (e.g., background EEG, myogenic and electrical noise, high electrode impedance due to small surface area) than OAEs. Based on these technical differences, a compelling argument can be made for using OAE based assays of the MOC reflex in a clinical setting, for example. It is, however, of great importance to understand the relationships between pre-neural and neural inhibition because the latter reflects modulation of the auditory nerve signal mediating hearing, which cannot be assessed with OAEs. Pre-neural and neural inhibition comparisons must be made in light of evidence that there is not a one-to-one correspondence between changes in OHC function and modulation of IHC neurotransmitter release, which is the basis for auditory nerve fiber depolarization (Guinan, 2012). However, by expressing CEOAE and CAP inhibition in terms of effective attenuation, direct comparisons can be made between MOC reflex effects on each type of response.

Our observation that CEOAE effective attenuation underestimated chirp- and click-evoked CAP effective attenuation by up to ~1.5 dB at low stimulus levels was consistent with previous reports in animals and humans (e.g., Puria et al., 1996; Lichtenhan et al., 2016). The source of this consistently reported discrepancy is not clear. OHCs are postsynaptic only to MOC fibers, whereas the auditory nerve is postsynaptic to both MOC and lateral olivocochlear (LOC) fibers, which directly contact type I auditory nerve fibers (Warr and Guinan, 1979). This anatomical configuration suggests that CAP inhibition reflects the summation of MOC and LOC inhibition, whereas OAEs only reflect MOC inhibition. However, several lines of evidence appear to refute this suggestion. Gifford and Guinan (1987) measured CAP inhibition from cats while electrically stimulating different regions of the caudal brainstem. They observed that stimulating the floor of the fourth ventricle (which diffusely activates the OCB proper) is comparable to the combined inhibitory effects of directly stimulating MOC neurons. When LOC neurons were directly stimulated, no inhibitory effects on the CAP were observed. The investigators also documented that increases in cochlear microphonic amplitude were related to decreases in CAP amplitude during OCB stimulation, indicating that the same process (i.e., direct modulation of OHCs) likely mediates each effect. Brown et al. (1983) measured IHC receptor potential tuning curves (from the AC component) with and without fourth ventricle electrical stimulation and observed 9–24 dB of inhibition at the tuning curve “tips” (i.e., center frequency) with no change away from center frequencies. Basilar membrane displacement tuning curves show similar effects (Murugasu and Russell, 1996; Cooper and Guinan, 2003). While these measurements are pre-neural, they are remarkably similar to auditory nerve tuning curves using the same paradigm (Wiederhold and Kiang, 1970; Bonfils et al., 1986). Thus, there is strong evidence that the MOC system is the main effector of inhibition in both pre-neural and neural assays. In contrast, there is no evidence that the LOC system can be excited with acoustic stimulation and its role in hearing remains poorly understood. The best available evidence suggests that the LOC system's influence on hearing is likely through slow “top-down” potentiation of auditory nerve activity (Sahley and Nodar, 1994; Groff and Liberman, 2003; Le Prell et al., 2005), which may protect auditory nerve fibers from acoustic trauma (e.g., Darrow et al., 2007).

If the MOC reflex accounts for inhibition measured from both OHCs and the auditory nerve, it may be expected that effective attenuation slopes of CEOAEs and CAPs would be parallel. We observed at the group level that the slopes of click CAP and CEOAE effective attenuation were similar to each other and quite different than chirp CAP effective attenuation (Figure 6D). Because we did not measure chirp-evoked OAEs, it is unclear if this difference is stimulus related or explained by some other mechanism. The temporal differences between clicks and chirps make the chirp a better stimulus for evoking synchronized neural responses, but these differences would not be expected to produce significantly dissimilar composite emission amplitudes evoked by each stimulus. Previous work has indicated that stimulus frequency OAEs (SFOAEs) and CEOAEs are generated in a nearly equivalent manner through coherent reflection when the spectral power within a bandwidth on the basilar membrane is equal (Neumann et al., 1994; Kalluri and Shera, 2007); if a chirp is conceptualized as a swept SFOAE, the effect of MOC reflex inhibition on chirp-evoked OAEs and CEOAEs would be expected to be similar. To our knowledge, there have been no experiments comparing MOC reflex inhibition of click- and chirp-evoked OAEs; therefore, the origin of the differences in effective attenuation slopes between chirp-evoked CAPs and pre-neural and neural measurements evoked with clicks in the group data is not clear.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.