Influence of 100 Hz amplitude modulation on the human medial olivocochlear reflex

Neuroscience Letters 580 (2014) 56–61

Contents lists available at ScienceDirect

Neuroscience Letters journal homepage: www.elsevier.com/locate/neulet

Influence of 100 Hz amplitude modulation on the human medial olivocochlear reflex Sriram Boothalingam a,∗ , David Purcell a,b , Susan Scollie a,b a b

National Centre for Audiology, Western University, London, Ontario, Canada N6G1H1 School of Communication Sciences and Disorders, Western University, London, Ontario, Canada N6G1H1

h i g h l i g h t s • Modulated noise evokes similar efferent (MOC) activity compared to unmodulated. • AM dips in noise energy may reduce its effectiveness in evoking MOC activity. • Temporal energy integration in MOC appears sensitive to amplitude modulation.

a r t i c l e

i n f o

Article history: Received 6 June 2014 Accepted 28 July 2014 Available online 4 August 2014 Keywords: Medial olivocochlear Otoacoustic emission Amplitude modulation Efferent inhibition

a b s t r a c t It is well known that medial olivocochlear system (MOC) activity causes inhibition of cochlear amplification that can be measured using otoacoustic emissions (OAEs). The temporal characteristics of this MOC inhibitory effect are still not well understood. Two experiments were performed to further explore a previously reported enhancement in MOC inhibition of OAEs by a broadband noise (BBN) elicitor modulated at 100 Hz (AM-BBN). In experiment I, MOC inhibition was measured for toneburst (1 and 2 kHz presented at 41.67 Hz) and stimulus-frequency (0.96–1.92 kHz) OAEs for two elicitor conditions, BBN and AM-BBN (100% modulation depth [MD]), in 27 young normal hearing adults. In experiment II, tonebursts were presented at 50 Hz instead of 41.67 Hz to test if the previously reported enhancement of the MOC response to 100 Hz AM-BBN is specific to a 50 Hz toneburst presentation rate. All elicitors caused significant reduction of both TB- and SF-OAE amplitude. AM-BBN evoked the same OAE inhibition compared to BBN in both experiments. This pattern was consistent across OAE types, and toneburst presentation rates. Results suggest that the MOC is not especially sensitive to 100 Hz AM-BBN; instead, AM dips in noise energy likely reduce its effectiveness in evoking MOC activity due to temporal energy integration. © 2014 Elsevier Ireland Ltd. All rights reserved.

1. Introduction The human auditory system has reciprocal connections through which higher auditory centres influence the working of lower auditory systems; this has been shown in animal models [1,2], and humans [3,4]. The final stop in the descending auditory pathway is the medial olivocochlear system (MOC). The MOC hyper-polarizes the cochlear outer hair cells (OHCs) through direct cholinergic action, consequently, reducing the gain of the cochlear active process [5]. Reduction in the cochlear active process can be recorded as reduced otoacoustic emission (OAE) level [6]. Such reduction in cochlear amplification is beneficial in several avenues such as, listening in noise [7–9], protection against acoustic injury [10],

∗ Corresponding author. Tel.: +1 519 661 2111x80480; fax: +1 519 661 3805. E-mail address: [email protected] (S. Boothalingam). http://dx.doi.org/10.1016/j.neulet.2014.07.048 0304-3940/© 2014 Elsevier Ireland Ltd. All rights reserved.

localization in noise [11], learning [12], and for proper development of the auditory system itself [13]. Since the MOC plays a multifaceted role in the auditory system, it is imperative to understand its response to stimuli of diverse spectral and temporal characteristics. Despite the wealth of understanding of the MOC’s effect for spectrally varying stimuli [14–16], the effect for various temporal patterns of the MOC elicitor remain unclear. Maison et al. [17] reported an enhanced MOC inhibition of 1 kHz toneburst OAEs (TBOAEs) for broadband noise (BBN) amplitude modulated at 100 Hz/100% depth (AM-BBN), compared to unmodulated noise and other modulation frequencies (MFs) and depths (MD). AM [18] and frequency modulated (FM; [19]) tones also elicit larger MOC inhibition than unmodulated tones, but this can partially be due to increase in the elicitor-tone bandwidth caused by modulation. The bandwidth of BBN does not change with AM. Contrary to Maison et al. [17], Backus [20], using stimulus frequency OAEs (SFOAEs), showed a monotonic increase in the overall

S. Boothalingam et al. / Neuroscience Letters 580 (2014) 56–61

MOC response as a function of elicitor MF (0.5–200 Hz). Backus [20] also reported that the largest MOC inhibition of SFOAEs was obtained for unmodulated BBN, and no special effect for 100 Hz AM was found. Backus [20] suggested that this is due to MOC time constants, which will be discussed further below. While the n-size in Backus [20] study was only four, the difference between the Maison et al. [17] and Backus [20] findings could possibly also arise due to the use of different OAE types: TBOAEs in the former and SFOAEs in the latter. Although both TBOAEs and SFOAEs are hypothesized to be generated by the same mechanism in the cochlea [21], it is possible that differences in MOC activation could be observed, possibly due to the use of a 50 Hz toneburst (TB) presentation rate in Maison et al. [17]. It is possible that the 50 Hz rate and its harmonics, produced during the neural transduction process, may interact with 100 Hz contralateral modulation at the neural level. Interactions are sometimes possible, as demonstrated with binaural auditory steady state responses (ASSRs) [22]. In addition, high click presentation rates (e.g., 50 Hz and above) have been shown to activate the contralateral MOC [23], and hence lower rates (e.g., 40 Hz) are employed in more recent studies [24]. For these reasons, we cannot rule out the possibility that enhanced MOC activity at 100 Hz MF in Maison et al. [17] may stem from the specific parameters used to evoke MOC activity and record OAEs, rather than a true MOC effect. Therefore, to investigate this rate effect further, two studies were conducted: the first study attempted to reconcile the results of Maison et al. [17] and Backus [20] using both SF- and TB-OAEs. TBs were specifically presented at 41.67 Hz (lower than the typical 50 Hz rate) in this experiment to minimize the possibility of the TBs evoking MOC activity by themselves [23,24]. In the second experiment, TBs were presented at 50 Hz to tease out the effect of TB presentation rate as a possible contributor to the enhanced 100 Hz AM-BBN MOC response reported by Maison et al. [17]. 2. Method 2.1. Participants Twenty-seven young adults (18–30 years) participated in the studies. All participants had normal hearing, defined by normal middle ear function and hearing thresholds of 20 dB HL or better between 0.25 and 8 kHz at octave intervals. In addition, acoustic reflex threshold (ART) for steady-state BBN was required to be ≥80 dB HL [6], measured using a clinical immitance meter (Madsen Otoflex, GN-Otometrics, Denmark). Spontaneous OAEs (SOAEs) were recorded to allow rejection of SFOAEs within 50 Hz of an SOAE to avoid phase related complexities [24]. The Health Sciences Research Ethics Board of Western University, Canada approved the study methods. Written informed consent was obtained from each participant after the nature of the study was explained. Participants sat in a comfortable chair in the double walled sound attenuated booth and were encouraged to relax, swallow as few times as comfortable, and sleep if possible. The ear being tested and the order of the OAE being tested were counterbalanced across participants. 2.2. Stimulus generation and recording Probe tones (fP ) in the frequency range 0.96–1.92 kHz (48 Hz intervals) were of 2.048 s in duration and were presented at 40 dB SPL. To obtain SFOAE, the suppression method [25] was used with discrete Fourier transforms. Each fP thus had a corresponding intra-cochlear suppressor (fS ) that was presented at 60 dB SPL, where fS = fP + 16 Hz with linear rise/fall ramps of 50 ms duration. Blackman-window gated TBs of frequencies 1 and 2 kHz, and 2 ms in duration were used to obtain TBOAEs [26]. The frequency range was chosen based on empirical evidence that contralateral MOC

57

activity is more pronounced in the 1–2 kHz region [15,16,23]. Efferent elicitors were uniform BBN and AM-BBN (BBN modulated at 100 Hz and 100% depth; [17]). Elicitors had equal root-mean-square (RMS) amplitude and rise/fall ramps of 20 ms each to avoid causing a startle response. Signals were played through a digital-to-analogue converter (6289 m-series, National Instruments, TX) at a sampling rate of 32 kHz to three separate programmable attenuators (PA5; TuckerDavis Technologies, FL) that controlled the output signal levels of the probes (tones and TBs), suppressors, and elicitors. These signals were power amplified (SA1; Tucker-Davis Technologies, FL) and fed to two ER2 transducers (Etymotic Research, IL) connected to an ER-10B+ otoacoustic emission probe system (Etymotic Research, IL) that delivered the signals in the ear-canal. A single ER2 insert receiver delivered elicitors in the contralateral ear. Responses were recorded using the ER-10B+ (Etymotic Research, IL) probe system with the pre-amplifier gain set at +40 dB. The recorded signal was then bandpass filtered (Frequency devices Inc., IL) from 0.2 to 10 kHz with further 20 dB gain. The filtered response was then digitized by an analogue-to-digital converter which applied another 6 dB of gain prior to conversion (6289 m-series, National Instruments, TX). Stimulus delivery and response acquisition were controlled using custom programs developed in LabView (National Instruments, TX).

2.3. Experiment I Elicitor conditions for SFOAE and TBOAE were organized as illustrated in Fig. 1A and B, respectively. At least 8 sweeps for the SFOAE, and 20 sweeps for the TBOAE measurement were obtained. A total of 2120 TBs/elicitor condition were obtained from the 20 sweeps. The inter-sweep-block interval between elicitor conditions and the inter-sweep interval between sweeps ensured that MOC activity reverted to baseline before it was activated again with a different elicitor [27]. The SFOAE measurement at every frequency started with an in-the-canal calibration of stimulus levels to produce the desired stimulus SPL in the ear-canal. A single isovoltage calibration was used for TBOAE measurements. Prior to calculating an average SFOAE response, all epochs were evaluated offline using a discrete Fourier transform to obtain noise metrics in a 20 Hz band just below fP . Epochs whose noise metric exceeded the mean plus two standard deviations (SDs) were not included in the average. The SFOAE at each frequency was obtained by vector subtraction of ear-canal pressure recorded in average sweep-blocks 1 and 2 (see Fig. 1A). Final SFOAE and inhibition magnitude were obtained by averaging SFOAE across all included frequencies (Fig. 2A). The SFOAE experiment was typically 20.07 min long, and the TBOAE experiment was 6.14 min long. TBOAE responses (OAEs + background noise mixture) in the time window from 8.5 to 18.5 ms post stimulus onset were extracted and digitally band-pass filtered using a fourth order Butterworth filter (cut-offs: 0.5–2 kHz for 1 kHz TB and 1–3 kHz for 2 kHz TB). Although a different time window from Maison et al. [17] has been used in this study, all TBOAE frequency components can be expected to be captured within this time-window, based on their latency [28]. Consecutive TBOAE epochs were separated into two buffers (A and B); the correlation coefficient between the two buffers served as a measure of reliability. Noise and SNR for TBOAEs were calculated according to Eqs. (1) and (2), respectively:

 Noise =

2

¯ ¯ abs(bufferB − X) abs(bufferA − X) + 2 2

2

(1)

58

S. Boothalingam et al. / Neuroscience Letters 580 (2014) 56–61

Fig. 1. Panels A and B are block diagrams of SFOAE and TBOAE measurement paradigms, respectively. Left columns in both panels indicate the stimulus delivery channels. Shaded (in grey) regions represent stimulus presence.

0 A: [SFOAE]

OAE Level (dBSPL)

10

No-elicitor BBN AM-BBN

8 B: [1 kHz-TB]

1k-No-elicitor 1k-BBN 1k-AM-BBN

2k-No-elicitor 2k-BBN 2k-AM-BBN

-2

4 6 -4 0 2

-6 -4

-8

-2 -22

-22

-22

-32

-32 Noise floor

-32 Noise floor

-42

-42 960

MOC inhibition (dB)

C: [2 kHz-TB]

1200

1440

1680

1920

Noise floor

-42 500

750

1000 1250 1500 1750 Frequency (Hz)

1000 1250 1500 1750 2000 2250

D: [MOC inhibition across OAEs and elicitors]

BBN

AM-BBN

3 2 1 0 SFOAE

TB-1kHz (41.6 Hz)

TB-2kHz (41.6 Hz) OAE type

TB-1kHz (50 Hz)

TB-2kHz (50 Hz)

Fig. 2. Panel A shows the grand average of SFOAE response across frequencies for all elicitor conditions. Panel B shows TBOAE for 1 kHz stimulus, and panel C shows TBOAE for 2 kHz stimulus (41.67 Hz presentation rate), for all elicitor conditions. Panel D shows mean MOC inhibition by the two elicitors for SF- and TB-OAE across frequencies and presentation rates. Error bars represent 95% confidence interval.

S. Boothalingam et al. / Neuroscience Letters 580 (2014) 56–61

 SNR = 10 ∗ log 10

¯ X Noise2

2

 −1

(2)

In Eq. (1), buffers A and B refer to the average responses in the respective buffers, and X¯ is the mean response across both buffers. TBOAE amplitude is the mean RMS of the response within the time window; frequency domain representations of TBOAEs are shown in Fig. 2B and C. 2.4. Experiment II Experiment II repeats Experiment I except that the TBs were presented at 50 Hz instead of 41.67 Hz. The 50 Hz TB rate was used to test if an interaction between TB presentation rate and 100 Hz AM-BBN could lead to the hypothesized enhancement in MOC inhibition for 100 Hz AM-BBN reported in Maison et al. [17]. This hypothesis was based on the ability of the auditory system to encode stimulus presentation rate, due to rectification in the cochlea and at the auditory nerve [29]. For example, the modulation frequency of a stimulus used to elicit the ASSR is not present in the spectrum of the acoustic stimulus, but rather appears during the transduction process [22]. In the present case, the neural response to the second harmonic of the 50 Hz presentation rate in the ipsilateral ear may interact with a 100 Hz AM response from the contralateral ear at the level of the brainstem, potentially causing an enhancement of MOC inhibition for 100 Hz AM-BBN. An enhancement is hypothesized because of the potential binaural stimulation at 100 Hz MF, with reference to monaural (contralateral) stimulation alone [22,30]. 2.5. Test for middle ear muscle reflex (MEMR) A change metric for TBOAE stimulus RMS levels (near the largest trough) across conditions (with MOC elicitors) with reference to the baseline no-elicitor condition was calculated to quantify the mean change in stimulus level during elicitor conditions. The observed changes in individual participants were <1.4%, and <0.12 dB of the stimulus level in no-elicitor condition [31,32], and included both increases and decreases in level across stimulus conditions, within participants. A significant MEMR would be expected to consistently increase probe tip stimulus levels at these low frequencies, suggesting that the observed changes in stimulus levels are likely due to random changes in noise. The changes are also very small compared to the observed level changes that we attribute to the MOC (1–2 dB), even given the nonlinear relationship between stimulus and response levels. Therefore, in conjunction with ARTs being at least 10 dB above our elicitor level [33], we conclude that any level change reported in the present study during elicitor presentations is likely only due to the MOC, and not MEMR. The same would apply for SFOAEs since the same elicitors were used for both SFOAEs and TBOAEs. 2.6. Test for probe-drift RMS amplitude of sample points around the largest stimulus trough for the first and last 20 stimulus epochs in every participant for all three elicitor conditions was obtained to test for change in stimulus level due to slow probe-drifts. Mean change in stimulus level for 1 kHz was −0.05 ± 0.12 dB, and −0.24 ± 0.22 dB for 2 kHz (including all elicitor conditions). A oneway repeated measures analysis of variance (RM-ANOVA) showed no effect of frequency (1 and 2 kHz; F[1,14] = 4.29, p > 0.05), elicitor condition (no-elicitor, BBN and AM-BBN; F[2,28] = 0.49, p > 0.05) and no interaction between frequency and elicitor conditions (F[2,28] = 0.75, p > 0.05). No-effect of elicitor condition suggests that

59

interleaving OAE evoking stimuli in short duration sweep-blocks (2.048 s in SFOAE, and 2.544 s in TBOAE measurements) avoided any unwanted effects of probe-drift across conditions. Therefore, we conclude that, with the use of short duration sweep-blocks (i.e., elicitor presentations) we should have avoided probe-drifts affecting our interpretation of MOC inhibition of OAEs across conditions. 2.7. Data inclusion criteria The following criteria were applied for data to be included in statistical analyses: an SNR of 12 dB or better, and less than 10% epoch rejection was required for both OAE types, and a minimum of 85% correlation between response buffers for TBOAE, and ≥80 dB HL ART with no large stimulus level changes in the MEMR test. Of the 27 participants, 10 were unique to experiment I, 9 to experiment II, and 8 participants took part in both experiments. Three from experiment I and two from experiment II were rejected based on inclusion criteria. All 22 included participants were considered for SFOAE, however, for both TBOAE experiment I (41.67 Hz), and TBOAE experiment II (50 Hz) there were 15 participants. 3. Results The Shapiro–Wilk test for normality indicated that data for all experimental conditions did not differ from a normal distribution (˛ = .05). Therefore, results were analyzed using parametric statistics. RM-ANOVAs were conducted as appropriate for Experiments I and II and are described below with Greenhouse–Geisser corrections where necessary. Post hoc tests with Bonferroni corrections for multiple comparisons were conducted to study the effect of each elicitor separately. 3.1. Experiment I (n = 22 for SFOAE, 15 for TBOAE) A one-way RM-ANOVA with elicitor condition (no-elicitor, BBN, AM-BBN) as the independent variable and SFOAE level as the dependent variable indicated a significant effect of the elicitor (F[1.49,31.47] = 77.78, p < 0.05, 2 partial = 0.79). A similar elicitor effect (F[1.05,14.71] = 30.59, p < 0.05, 2 partial = 0.69) was obtained for TBOAEs in a 2-way RM-ANOVA with frequency (1 and 2 kHz), and elicitor (no-elicitor, BBN, AM-BBN) as independent variables, and TBOAE level as the dependent variable. No interaction between elicitor and frequency (F[1.07,15.08] = 2.18, p > 0.05, 2 partial = 0.13) was found, despite a significant frequency effect (F[1,14] = 89.81, p < 0.05, 2 partial = 0.86), suggesting that 100 Hz AM-BBN did not elicit larger MOC inhibition than BBN. Post hoc comparisons (Fig. 2D) indicated that both elicitors caused significant (p < 0.05) reduction in both SFOAE (BBN: mean difference [MD] = 1.88 ± 0.43 [95% confidence interval]; AM-BBN: MD = 1.79 ± 0.36) and TBOAE (BBN: MD = 1.73 ± 0.82; AM-BBN: MD = 1.58 ± 0.79) levels (re: baseline no-elicitor). Differences between AM-BBN and BBN inhibition of TBOAEs approached significance (MD = −0.15 ± 0.15, p = 0.06), with a trend towards AM-BBN eliciting lower inhibition than BBN, contrary to Maison et al. [17]. 3.2. Experiment II (n = 15) Results were very similar to experiment I: there was a significant effect of elicitor (F[1.26,17.64] = 60.98, p < 0.05, 2 partial = 0.81) and frequency (F[1,14] = 67.73, p < 0.05 2 partial = 0.83), and no interaction between elicitor and frequency (F[1.81,25.44] = 1.87, p > 0.05, 2 partial = 0.12). Results of post hoc comparisons (see Fig. 2D) were also similar to experiment I, i.e., 100 Hz AM-BBN did not elicit larger MOC inhibition than BBN (MD = −0.07 ± 0.17, p = 0.70). However,

60

S. Boothalingam et al. / Neuroscience Letters 580 (2014) 56–61

both BBN (MD = 2.08 ± 0.66) and AM-BBN (MD = 2.01 ± 0.69) caused significant (p < 0.05) reduction in TBOAE level. 4. Discussion 4.1. Influence of 100 Hz modulation One of the main aims of this study was to better understand the physiology of the MOC in response to 100 Hz AM. Contrary to Maison et al. [17], the 100 Hz AM-BBN in this study did not elicit larger OAE inhibition than BBN in both OAE types. Since BBN and AM-BBN have the same spectral bandwidth, similar OAE inhibition may seem reasonable to expect and may be based on the modulation transfer function and time-constants of the MOC. The MOC has a ∼200 ms rise time and ∼100 ms decay time [27], and its modulation transfer function suggests that at elicitor MFs higher than 1 Hz, i.e., a modulation period of 1000 ms, the MOC becomes progressively less sensitive, but not insensitive, to modulation [20]. This is consistent with data from chinchillas, studied using distortion product OAEs, which show the MOC’s ability to follow elicitor MFs until 19 Hz, i.e., a modulation period of 52.6 ms [34]. It is apparent from these studies that a modulation period of 100 Hz AM (i.e., 10 ms) may be too fast for the MOC to follow instantaneously. Despite this inability, a trend towards lower inhibition for AM-BBN compared to BBN is observable in the current study (Fig. 2D), especially at 2 kHz. This is congruous with Backus [20], and also with Maison et al. [17] for their 50 Hz MF. Reduced MOC inhibition for AM-BBN might occur due to energy integration across time when the response is averaged over longer periods [35]. Although the elicitors’ RMS amplitudes were matched, the current data suggest that the increased energy at AM-BBN peaks may not be sufficient to compensate for the silent periods during modulation. The effective elicitor energy available may thus be smaller, even for faster AM rates, compared to BBN, as the MOC appears to be sensitive to AM. Modulations in noise energy may thus reduce its effectiveness in evoking MOC activity. 4.2. Relation between transient-stimuli presentation rate and elicitor modulation frequency Pairwise comparisons in experiments I and II show that AM-BBN does not evoke larger inhibition than BBN for either rate. Therefore, it can be suggested that Maison et al’s [17] 50 Hz TB presentation rate may not be responsible for the enhanced 100 Hz AM effect reported in their study. Since the MOC does not appear to have an enhancement of MOC inhibition at 100 Hz MF, the true reason for the difference in results obtained between the present study and Maison et al. [17] is currently unknown. 5. Conclusion The current study investigated the effect of stimulating the MOC with BBN and 100 Hz AM-BBN in a sample of 22 participants (15 for TBOAE). Results suggest that AM-BBN (100 Hz MF and 100% MD) does not evoke larger MOC inhibition compared to BBN, which is contrary to Maison et al. [17], but in keeping with Backus [20]. Any observable differences in the MOC response between BBN and AM-BBN are likely due to differences in their temporal characteristics: constant stimulation provided by BBN as opposed to the presence of sections of the modulation period that contain no noise energy in AM-BBN. Consistency of the results across the two OAE types, and TB presentation rates strengthen these findings.

Acknowledgements The authors would like to thank the two anonymous reviewers for their valuable comments and suggestions. This study was funded by a Western University Graduate Research Scholarship to S.B., Natural Sciences and Engineering Research Council of Canada (RGPIN-05320-2007) to D.P., Ontario Research Fund (LEF#RE-03009) and Canada Foundation for Innovation Grant to the National Centre for Audiology. References [1] J.A. Winer, Decoding the auditory corticofugal systems, Hear Res. 212 (2006) 1–8. [2] Z. Xiao, N. Suga, Modulation of cochlear hair cells by the auditory cortex in the mustached bat, Nat. Neurosci. 5 (2002) 57–63. [3] S. Khalfa, R. Bougeard, N. Morand, E. Veuillet, J. Isnard, M. Guenot, P. Ryvlin, C. Fischer, L. Collet, Evidence of peripheral auditory activity modulation by the auditory cortex in humans, Neuroscience 104 (2001) 347–358. [4] X. Perrot, P. Ryvlin, J. Isnard, M. Guénot, H. Catenoix, C. Fischer, F. Mauguière, L. Collet, Evidence for corticofugal modulation of peripheral auditory activity in humans, Cereb. Cortex. 16 (2006) 941–948. [5] E. Murugasu, I.J. Russell, The effect of efferent stimulation on basilar membrane displacement in the basal turn of the guinea pig cochlea, J. Neurosci. 16 (1996) 325–332. [6] J.J. Guinan, Olivocochlear efferents: anatomy, physiology, function, and the measurement of efferent effects in humans, Ear Hear 27 (2006) 589–607. [7] A. Kumar, C.S. Vanaja, Functioning of olivocochlear bundle and speech perception in noise, Ear Hear 25 (2004) 142–146. [8] S.K. Mishra, M.E. Lutman, Top-down influences of the medial olivocochlear efferent system in speech perception in noise, PLOS ONE 9 (1) (2014) e85756. [9] S.P. Bhagat, P.H. Carter, Efferent-induced change in human cochlear compression and its influence on masking of tones, Neurosci. Lett. 485 (2010) 94–97. [10] R. Rajan, Centrifugal pathways protect hearing sensitivity at the cochlea in noisy environments that exacerbate the damage induced by loud sound, J. Neurosci. 20 (2000) 6684–6693. [11] G. Andéol, A. Guillaume, C. Micheyl, S. Savel, L. Pellieux, A. Moulin, Auditory efferents facilitate sound localization in noise in humans, J. Neurosci. 31 (2011) 6759–6763. [12] S. Irving, D.R. Moore, M.C. Liberman, C.J. Sumner, Olivocochlear efferent control in sound localization and experience-dependent learning, J. Neurosci. 31 (2011) 2493–2501. [13] D.D. Simmons, Development of the inner ear efferent system across vertebrate species, J. Neurobiol. 53 (2002) 228–250. [14] S. Maison, C. Micheyl, G. Andéol, S. Gallégo, L. Collet, Activation of medial olivocochlear efferent system in humans: influence of stimulus bandwidth, Hear Res. 140 (2000) 111–125. [15] W. Lilaonitkul, J.J. Guinan, Human medial olivocochlear reflex: effects as functions of contralateral, ipsilateral, and bilateral elicitor bandwidths, J. Assoc. Res. Otolaryngol. 10 (2009) 459–470. [16] W. Zhao, S. Dhar, Frequency tuning of the contralateral medial olivocochlear reflex in humans, J. Neurophysiol. 108 (2012) 25–30. [17] S. Maison, C. Micheyl, L. Collet, Sinusoidal amplitude modulation alters contralateral noise suppression of evoked otoacoustic emissions in humans, Neuroscience 91 (1999) 133–138. [18] S. Maison, C. Micheyl, L. Collet, Medial olivocochlear efferent system in humans studied with amplitude-modulated tones, J. Neurophysiol. 77 (1997) 1759–1768. [19] S. Maison, C. Micheyl, L. Collet, Contralateral frequency-modulated tones suppress transient-evoked otoacoustic emissions in humans, Hear Res. 117 (1998) 114–118. [20] B.C. Backus, Using Stimulus Frequency Otoacoustic Emissions to Study Basic Properties of the Human Medial Olivocochlear Reflex, Massachusetts Institute of Technology, 2005, Available at: http://dspace.mit.edu/handle/1721.1/33840 [21] R. Kalluri, C.A. Shera, Near equivalence of human click-evoked and stimulusfrequency otoacoustic emissions, J. Acoust. Soc. Am. 121 (2007) 2097–2110. [22] O.G. Lins, P.E. Picton, T.W. Picton, S.C. Champagne, A. Durieux-Smith, Auditory steady-state responses to tones amplitude-modulated at 80–110 Hz, J. Acoust. Soc. Am. 97 (1995) 3051–3063. [23] E. Veuillet, L. Collet, R. Duclaux, Effect of contralateral acoustic stimulation on active cochlear micromechanical properties in human subjects: dependence on stimulus variables, J. Neurophysiol. 65 (1991) 724–735. [24] N.A. Francis, J.J. Guinan Jr., Acoustic stimulation of human medial olivocochlear efferents reduces stimulus-frequency and click-evoked otoacoustic emission delays: implications for cochlear filter bandwidths, Hear Res. 267 (2010) 36–45. [25] D. Brass, D.T. Kemp, Suppression of stimulus frequency otoacoustic emissions, J. Acoust. Soc. Am. 93 (1993) 920–939. [26] S.J. Norton, S.T. Neely, Tone-burst-evoked otoacoustic emissions from normalhearing subjects, J. Acoust. Soc. Am. 81 (1987) 1860–1872. [27] B.C. Backus, J.J. Guinan, Time-course of the human medial olivocochlear reflex, J. Acoust. Soc. Am. 119 (2006) 2889–2904.

S. Boothalingam et al. / Neuroscience Letters 580 (2014) 56–61 [28] C.A. Shera, J.J. Guinan, A.J. Oxenham, Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements, Proc. Natl. Acad. Sci. U. S. A. 99 (2002) 3318–3323. [29] M.S. John, A. Dimitrijevic, T.W. Picton, Efficient stimuli for evoking auditory steady-state responses, Ear Hear 24 (2003) 406– 423. [30] C.I. Berlin, L.J. Hood, A.E. Hurley, H. Wen, D.T. Kemp, Binaural noise suppresses linear click-evoked otoacoustic emissions more than ipsilateral or contralateral noise, Hear Res. 87 (1995) 96–103. [31] C. Abdala, S. Mishra, A. Garinis, Maturation of the human medial efferent reflex revisited, J. Acoust. Soc. Am. 133 (2013) 938–950.

61

[32] C. Abdala, S. Dhar, M. Ahmadi, P. Luo, Aging of the medial olivocochlear reflex and associations with speech perception, J. Acoust. Soc. Am. 135 (2014) 754–765. [33] X.M. Sun, Contralateral suppression of distortion product otoacoustic emissions and the middle-ear muscle reflex in human ears, Hear Res. 237 (2008) 66–75. [34] R.V. Harrison, A. Sharma, T. Brown, S. Jiwani, A.L. James, Amplitude modulation of DPOAEs by acoustic stimulation of the contralateral ear, Acta Otolaryngol. 128 (2008) 404–407. [35] S. Maison, J. Durrant, C. Gallineau, C. Micheyl, L. Collet, Delay and temporal integration in medial olivocochlear bundle activation in humans, Ear Hear 22 (2001) 65–74.