Synchronized Spontaneous Otoacoustic Emissions Provide a Signal-to-Noise Ratio Advantage in Medial-Olivocochlear Reflex Assays

Abstract

Detection of medial olivocochlear-induced (MOC) changes to transient-evoked otoacoustic emissions (TEOAE) requires high signal-to-noise ratios (SNR). TEOAEs associated with synchronized spontaneous (SS) OAEs exhibit higher SNRs than TEOAEs in the absence of SSOAEs, potentially making the former well suited for MOC assays. Although SSOAEs may complicate interpretation of MOC-induced changes to TEOAE latency, recent work suggests SSOAEs are not a problem in non-latency-dependent MOC assays. The current work examined the potential benefit of SSOAEs in TEOAE-based assays of the MOC efferents. It was hypothesized that the higher SNR afforded by SSOAEs would permit detection of smaller changes to the TEOAE upon activation of the MOC reflex. TEOAEs were measured in 24 female subjects in the presence and absence of contralateral broadband noise. Frequency bands with and without SSOAEs were identified for each subject. The prevalence of TEOAEs and statistically significant MOC effects were highest in frequency bands that also contained SSOAEs. The median TEOAE SNR in frequency bands with SSOAEs was approximately 8 dB higher than the SNR in frequency bands lacking SSOAEs. After normalizing by TEOAE amplitude, MOC-induced changes to the TEOAE were similar between frequency bands with and without SSOAEs. Smaller MOC effects were detectable across a subset of the frequency bands with SSOAEs, presumably due to a higher TEOAE SNR. These findings demonstrate that SSOAEs are advantageous in assays of the MOC reflex.

Keywords: auditory efferent system; cochlear processing; female; normal hearing.

Fig. 1

Example of an MOC-induced phase change to the TEOAE waveform. a Emission waveforms measured in Quiet and Noise conditions (thick, solid black line and thin, broken red line, respectively) across the duration of the TEOAE analysis window. b Waveforms constrained to a time window spanning 10.5–13.5 ms post-stimulus. Activation of the MOCR resulted in a slight amplitude decrease and phase shift

Fig. 2

TEOAE magnitudes (a) and SNRs (b) in instances where the TEOAE was measured in the presence and absence of an SSOAE (+SSOAE and −SSOAE, respectively). +SSOAE data are indicated by filled symbols, −SSOAE data are indicated by open symbols. The solid lines in each plot represent the median (across frequency and subject) data for TEOAEs with SSOAEs, whereas dashed lines represent the median data for TEOAEs without SSOAEs

Fig. 3

MOC metrics (a, b) and SNRs (c, d) in instances where the TEOAE was measured in the presence and absence of an SSOAE. The solid lines in each plot represent the median data for TEOAEs with SSOAEs, whereas dashed lines represent the median data for TEOAEs without SSOAEs.

Fig. 4

P_MOCT as a function of TEOAE magnitude in cases where SSOAEs were present and absent. The solid line represents a 1st-order power-fit to the combined +SSOAE and -SSOAE data. Coefficient values and the goodness of fit are provided in the plot

Fig. 5

MOCR% estimated from P_MOCT (MOCR_T%, a) and P_MOCM (MOCR_M%, b) within different frequency bands for instances where SSOAEs were present and absent. The solid lines in each plot indicate the frequency-specific median values of MOCR% for the +SSOAE data, whereas the broken lines indicate the median values of MOCR% for −SSOAE data

Fig. 6

Minimum detectable MOCR_T% as a function of TEOAE SNR. The minimum detectable MOCR_T% was calculated as δ_99.5% normalized by TEOAE magnitude. As TEOAE SNR increases, smaller values of MOCR_T% are detectable. The broken dashed line represents a 1st-order exponential fit to the combined +SSOAE and -SSOAE data. Coefficient values and the goodness of fit are provided in the plot

Fig. 7

Statistically significant and non-significant values of MOCR_T% as a function of TEOAE SNR when SSOAEs were present (a) and absent (b). The circle markers indicate a statistically significant MOC-induced change to the TEOAE, whereas cross markers indicate a non-significant change. Overlaid on the plots is the 1st-order exponential fit describing the minimum-detectable MOCR_T% as a function of TEOAE SNR (from Fig. 6)

Fig. 8

a, b Examples of TEOAE time-waveform envelopes in frequency bands with and without SSOAEs, respectively. Each panel shows the 3.78-kHz band emission waveform envelope measured in Quiet (solid line) and an estimate of the noise (shaded region). In both cases, the emission exhibits an amplitude peak around 6 ms (indicated by the inverted triangle marker). Following the amplitude peak, emission energy persists at a steady level throughout the duration of the analysis window for the subject with a SSOAE. In contrast, for the subject lacking a SSOAE, emission energy decayed into the noise floor within the 20-ms window. c Latencies of the emission’s peak amplitude. Overlaid on the plot is the predicted relationship between SFOAE latency and frequency from Shera and Guinan (2003); see Eq. 5. d SNR advantage associated with present SSOAEs for different definitions of the TEOAE. The solid line indicates data for when the TEOAE is defined over a duration of 6 cycles re: latency of the peak amplitude. The broken line indicates data for when the TEOAE is defined based on the energy within an analysis window extending to 20-ms post-stimulus