Amplitude and phase equalization of stimuli for click evoked auditory brainstem responses Rainer Beutelmann and Geneviève LaumenDaniel TollinGeorg M. KlumpBLM

Citation: J. Acoust. Soc. Am. 137, EL71 (2015); doi: 10.1121/1.4903921 View online: http://dx.doi.org/10.1121/1.4903921 View Table of Contents: http://asa.scitation.org/toc/jas/137/1 Published by the Acoustical Society of America

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[http://dx.doi.org/10.1121/1.4903921]

Published Online 19 December 2014

Amplitude and phase equalization of stimuli for click evoked auditory brainstem responses Rainer Beutelmanna) and Genevie`ve Laumen Cluster of Excellence “Hearing4all,” Animal Physiology and Behavior Group, Department of Neurosciences, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany [email protected], [email protected]

Daniel Tollin Department of Physiology and Biophysics, School of Medicine, University of Colorado, Aurora, Colorado 80045 [email protected]

Georg M. Klump Cluster of Excellence “Hearing4all,” Animal Physiology and Behavior Group, Department of Neurosciences, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany [email protected]

Abstract: Although auditory brainstem responses (ABRs), the soundevoked brain activity in response to transient sounds, are routinely measured in humans and animals there are often differences in ABR waveform morphology across studies. One possible reason may be the method of stimulus calibration. To explore this hypothesis, click-evoked ABRs were measured from seven ears in four Mongolian gerbils (Meriones unguiculatus) using three common spectrum calibration strategies: Minimum phase filter, linear phase filter, and no filter. The results show significantly higher ABR amplitude and signal-to-noise ratio, and better waveform resolution with the minimum phase filtered click than with the other strategies. C 2014 Acoustical Society of America V

[BLM] Date Received: September 3, 2014

Date Accepted: November 25, 2014

1. Introduction Recent investigations into the neuroanatomical bases of so-called “hidden” hearing loss, where hearing thresholds remain normal despite large deafferentation of auditory nerve fibers (Kujawa and Liberman, 2009), and reports of cases of tinnitus and other auditory deficits in subjects with such hearing loss (Schaette and McAlpine, 2011) have reignited an interest in measurements of the auditory brainstem response (ABR) for objective diagnosis. Subjects experiencing these pathologies typically have normal ABR thresholds but vastly reduced wave I amplitudes, or the overt lack of ABRs in cases of auditory neuropathy (Zeng et al., 2005), despite seemingly normal amplitudes of the later ABR peaks. Making such diagnoses on the basis of an objective biomarker such as the ABR waveform morphology relies on obtaining high quality measurements that are consistent not only within but also across clinics and laboratories. As we demonstrate in this study, the quality of ABR measurements, and thus their utility for such diagnoses, depends heavily on the methods by which the sound delivery equipment is calibrated. ABRs, the activity of the brain in response to transient auditory stimuli, can be measured using electrodes on the surface of the head of humans and animals a)

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J. Acoust. Soc. Am. 137 (1), January 2015

C 2014 Acoustical Society of America EL71 V

Beutelmann et al.: JASA Express Letters

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Published Online 19 December 2014

(Jewett and Williston, 1971). ABRs are widely used in auditory research and for clinical screening. Auditory brainstem responses from animals are examined in combination with other electrophysiological measures including cochlear potentials (Koka et al., 2010) for studies of, for example, the development of hearing impairment. When sound stimuli are to be presented to small animals, such as rodents, the acoustical coupling apparatus between transducers and the ear canals usually leads to spectral distortions, which should be equalized for accurate playback. We show that care must be taken when designing a filter for spectral calibration, because the choice of filter design method can have an impact on the quality of the measured ABRs. One widely used stimulus for ABR measurements is the “click,” a sharp transient with a broad spectrum (Durrant and Boston, 2007). For practical reasons, the click is usually one digital sample with non-zero amplitude. Given a specific digital sampling rate, this is the steepest transient possible. The click has a constant spectral density at all frequencies up to the sampling limit, exciting the auditory system strongly at a wide range of frequencies within a very short period of time. In order to achieve a strong response, the onset of the click needs to be as steep as possible. Ideally, the click should be reproduced acoustically at the eardrum, but spectral distortions due to the earphones and coupling method prohibit this without proper acoustic calibration in situ. The purpose of acoustical calibration is to define the relation between a digitally defined stimulus and its representation at the ear of the experimental subject as accurately as possible. For a single frequency, the total sound pressure level of the stimulus can be measured. Changing the digital level of the stimulus leads to an equal change in acoustical stimulus level, assuming that the reproduction system is approximately linear within a certain dynamic range. Broadband signals, such as white noise or transient signals, can generally not be calibrated with a single level measurement or several measurements at a few discrete frequencies (i.e., a “lookup” table), but have to be equalized spectrally using a filter. The choice of equalization filter is not trivial. The filtering is usually done in the digital domain, because analog filters are inflexible and have to be set manually. In the digital domain, infinite impulse response (IIR) filters are computationally efficient, but their design is more complex than that of finite impulse response (FIR) filters, especially when a specific phase response is needed (Oppenheim et al., 1999); additionally, IIR filters can become unstable. FIR filters can have arbitrary phase responses, particularly linear phase, they are always stable, and their design is comparably simple—at the expense of more computational effort for the filtering operation (Oppenheim et al., 1999). This disadvantage for FIR filters is less relevant, if all stimuli can be pre-processed before the measurement starts. Linear phase FIR filters are often used because their constant group delay leaves the general waveform of the input signal intact. In the case of click stimuli, a linear phase filter may not be the optimal choice, because linear phase filters have to be symmetric in the time domain and thus increase the width of the click in the time domain. Another promising alternative are minimum phase FIR filters, because they concentrate the energy of their impulse response at its beginning by definition, which leads to less time domain smearing (Oppenheim et al., 1999). In this paper, we show that the choice of equalization filter has a strong impact on the quality of the ABR measured with filtered clicks which can in turn result in differences in the morphology of the ABR waveforms from study to study. 2. Methods Monaural and binaural click evoked auditory brainstem responses (ABRs) were measured from seven ears in four ketamine (70 mg/kg) and xylazine (3 mg/kg) anesthetized Mongolian gerbils (Meriones unguiculatus) using subcutaneous needle electrodes. The reference electrode was positioned at the vertex and the recording electrode at the

EL72 J. Acoust. Soc. Am. 137 (1), January 2015

Beutelmann et al.: Stimulus equalization for brainstem responses

Beutelmann et al.: JASA Express Letters

[http://dx.doi.org/10.1121/1.4903921]

Published Online 19 December 2014

neck. Low impedance was ensured by wetting the electrodes with saline solution if necessary. The electrode signal was amplified by a World Precision Instruments ISO-80 Bio-amplifier, and recorded on hard disk using an RME Hammerfall Multiface II sound card, which also delivered the stimuli. The playback and recording rate was 48 kHz. The stimuli were amplified by a Harman-Kardon HK6350 amplifier and played back by Vifa XT300/K4 speakers. The speakers (diaphragm diameter 25 mm) were snugly coupled to the ear canal of the gerbil by a custom built combination of exponential (100 mm length) and conical (20 mm length) horns. The horns were internally damped with a piece of sound absorbing foam in order to attenuate resonances due to non-optimal acoustic coupling of the horn mouths to speaker and ear canal, respectively. Animals were maintained at normal physiological temperature by an electronically controlled heating blanket. The care and treatment of the gerbils were in accordance with the procedures of animal experimentation approved by the Government of Lower Saxony, Germany. All procedures were performed in compliance with the NIH Guide on Methods and Welfare Considerations in Behavioral Research with Animals (National Institute of Mental Health, 2002). In order to equalize the sound spectrum at the gerbil’s ear canal entrance, the impulse response of the system was measured with a logarithmic chirp (200 Hz to 24 kHz at 1 octave per second) using Etymotic ER-7C probe microphones placed approximately 2 mm into the ear canal. The microphones were kept in place during the experiment and their output was recorded simultaneously with the ABR signal. Calibration filters were generated from the impulse responses using two different methods. In both cases the absolute sound pressure level was referenced to a 1 kHz tone. One filter was generated with linear phase using the windowing method (i.e., the fir2 MATLAB function). The other filter was generated with minimum phase by inverting an autoregressive estimate of the unequalized spectrum (i.e., arburg MATLAB function). Both filters had a length of 129 samples, or “taps,” at a sampling rate of 48 kHz. The stimuli were additionally played without a spectral filter, using only the reference level [i.e., sound pressure level (SPL) re: 1 kHz tone]. All stimuli were played at 60 and at 80 dB SPL. Linear operation of the sound reproduction system was controlled by checking the peak amplitude ratio between 60 and 80 dB SPL clicks, which was 20 dB with a standard deviation of 0.3 dB. Recording and playback were controlled by custom-built software using MATLAB (The Mathworks, Inc., Natick, MA). The stimuli were pre-generated, filtered and scaled for spectral and level calibration, and played with randomized interstimulus time intervals. The average inter-stimulus interval was 30 ms, with a standard deviation of 10 ms. The stimuli were played with alternating signs (condensation and rarefaction clicks) in order to cancel out the stimulus artifact in the recording. Intervals with maximal amplitude less than 20 lV were considered artifact-free (e.g., heart beat or breathing muscle potentials). All intervals were recorded, regardless of their maximal amplitude. Each stimulus was repeated until at least 1000 of the corresponding recorded intervals were artifact-free. The raw recordings were averaged using the procedure proposed by Riedel et al. (2001) and Granzow et al. (2001). The mean was removed from each raw interval recording before it was band pass filtered (linear phase FIR, 201 taps) between 50 and 3000 Hz (Thornton, 2007). Each interval was weighted by the inverse of its power divided by the sum of all weights in the first average. This average was subtracted from each interval before calculating the weight for the average in a second iteration step. This procedure results in a better signal-to-noise ratio than a simple artifact thresholding procedure (Riedel et al., 2001). The signal-to-noise ratio was calculated according to Granzow et al. (2001) as SNR ¼ 20 log10 ½rmsðsÞ=rmsðrÞ, where s denotes the averaged ABR signal, r denotes the corresponding standard error of the mean, and rmsðÞ denotes the root-mean-squared value across time. The level of significance for all statistical tests was p < 0.05.

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Beutelmann et al.: JASA Express Letters

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3. Results Results are presented for ABRs measured in seven ears of four gerbils. Figure 1 shows waveforms [Fig. 1(a)] and corresponding magnitude [Fig. 1(b)] and phase [Fig. 1(c)] spectra of the stimuli recorded in the ear canal at a stimulus level of 80 dB SPL. Each panel contains an overlay of all waveforms from left and right ears and each animal (n ¼ 7). The waveforms are averaged over the corresponding recording session. The average across-animal deviation of the magnitude spectra from their mean across the frequency range from 500 Hz to 20 kHz was 68.5 dB for the minimum phase (mp) filter, 610.9 dB for the linear phase (lp) filter, and 624.7 dB for the click without filter (nf). The corresponding average standard deviations of the magnitude spectra from the means in the same frequency range are as follows: mp, 4.2 dB; lp, 4.4 dB; and nf, 8.9 dB. The average deviation of the phase spectra from zero in cycles was mp, 0.11; lp, 0.24; and nf, 0.51; the average standard deviation was mp, 0.05; lp, 0.09; and nf, 0.17. The minimum phase filter clearly leads to a concentration of the click energy within the smallest time window compared to the other types and is also the most consistent across animals [Fig. 1(a)]. This is supported quantitatively using the correlation coefficient between click waveforms as a measure of consistency. The correlation coefficients between clicks averaged across all combinations of ears are higher for the minimum phase filter than for both other filter types at 80 dB SPL (mp, 0.98 vs lp, 0.95 and nf, 0.94) and higher for both filters than for the unfiltered click at 60 dB SPL (mp, 0.79 and lp, 0.79 vs nf, 0.68). For binaural ABR measurements it is important to note that the mean correlation coefficients between clicks from corresponding left and right ears show the same dependence on filter type with even larger differences between filter types: mp, 0.94; lp, 0.89; and nf, 0.84 (at 80 dB SPL) and mp, 0.82; lp 0.79; and nf, 0.67 (at 60 dB SPL). The high across-animal, and across-ear within animal, consistency in both the spectral [Fig. 1(b)] and temporal [Fig. 1(a)] outputs of the minimum phase filter relative to the other filter types suggests that there might be less variability in acrossanimal ABR morphology simply because of less stimulus-related variability. To test this hypothesis, ABRs were measured in each animal with each of the three filter settings for 60 and 80 dB SPL stimuli. Figure 2 shows the ABR waveforms at 60 dB [Fig. 2(a)] and 80 dB [Fig. 2(b)] stimulus level. Each panel contains an overlay of all monaural ABR recordings (n ¼ 7 ears) at the corresponding level and with the corresponding

Fig. 1. Stimulus (a) waveforms, (b) magnitude, and (c) phase spectra recorded at the ear canal entrance of the subjects, with different calibration filters. Each subpanel contains an overlay of separate waveforms and spectra, respectively, for each ear. All signals were averaged over one recording session. Constant group delay was removed from the phase spectra.

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Beutelmann et al.: Stimulus equalization for brainstem responses

Beutelmann et al.: JASA Express Letters

[http://dx.doi.org/10.1121/1.4903921]

Published Online 19 December 2014

Fig. 2. Monaural auditory brainstem responses recorded with different calibration filters (rows) and stimulus level (columns). Each subpanel contains the overlay of separate ABR waveforms for each combination of ear and animal.

filter. Visual inspection of the ABRs reveals some potential filter-related differences in the amplitudes and the waveform morphologies and consistencies of the evoked ABRs. For example, while minimum and linear phase filters give rise to appreciable ABRs at 60 dB SPL, there is little discernable response for the no-filter condition despite the input stimuli having identical stimulus levels. At the higher 80 dB SPL, the minimum phase evoked ABR has a larger amplitude and ABR peaks and dips that are more distinct and more consistent from ear to ear than the ABRs evoked with the linear phase filter or no filter condition. Figure 3 shows the ABR signal-to-noise ratios (Granzow et al., 2001) grouped by stimulus level and stimulation type. A generalized linear mixed model (GLMM) with the fixed factors level (60 and 80 dB SPL), stimulation type (monaural or binaural), and filter type (minimum phase, linear phase, and no filter), as well as animal as a random factor (assuming that animals generally have different hearing thresholds)

Fig. 3. Signal-to-noise ratios of the ABR waveforms in decibels, means (bars) with standard deviations (lines) across animals. Upper row: monaural stimulation; lower row: binaural stimulation.

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shows that all main effects are significant [level: F(1,3) ¼ 75.00, p ¼ 0.003, mon./bin.: F(1,56) ¼ 189.87, p < 0.001, filter type: F(2,56) ¼ 91.75, p < 0.001], as well as the interaction between level and filter type [F(2,56) ¼ 61.68, p < 0.001]. Bonferroni-Holm corrected planned comparisons show a significant difference between all filter types [minimum phase vs linear phase: t(56) ¼ 3.89, p ¼ 0.002, minimum phase vs no filter: t(56) ¼ 13.18, p < 0.001, linear phase vs no filter: t(56) ¼ 9.29, p < 0.001]. All signal-tonoise ratios are significantly different between filter types at 60 dB SPL stimulus level [minimum phase vs linear phase: t(56) ¼ 2.57, p ¼ 0.035, minimum phase vs no filter: t(56) ¼ 16.03, p < 0.001, linear phase vs no filter: t(56) ¼ 13.46, p < 0.001]. At 80 dB SPL stimulus level, the signal-to-noise ratios are significantly different [minimum phase vs linear phase: t(56) ¼ 2.93, p ¼ 0.020, minimum phase vs no filter: t(56) ¼ 2.61, p ¼ 0.035] for all comparisons between filter types except for the no filter vs linear phase filter conditions [t(56) ¼ 0.32, p ¼ 0.752]. In all cases, the minimum phase filter conditions result in the highest signal-to-noise ratio and the no filter conditions in the lowest. 4. Discussion Accurate stimulus reproduction plays an important role in all auditory experiments. The measurement of click evoked auditory brainstem responses is specifically sensitive to distortions in the stimulus at the ear of the subject. This study shows that it is essential to equalize both amplitude and phase spectrum of the acoustic reproduction system, because a system of horns and tubes used in order to transmit the sound to the ear canal of a small animal, such as the gerbils in this study, does not generally have a flat spectrum. A linear phase filter appears to be inferior to a minimum phase filter, although the linear phase filter is often favored for its constant group delay. As can be seen in Fig. 1(a), the linear phase filter results in a less sharp and concentrated click waveform than the minimum phase filter, if the waveform is already smeared by the reproduction system. In addition to that, the amplitude spectrum equalized with the minimum phase filter has less residual variation [Fig. 1(b)] at the same signal processing effort (same number of filter taps) than with the linear phase filter. The steep onset of the minimum phase filtered click and its short ringing lead to higher ABR amplitudes than with the linear phase filtered or the unfiltered click at the same stimulus energy. The symmetric waveform of the click filtered with the linear phase filter already slightly excites the auditory system before the main peak and leads to a smeared ABR signal (Fig. 2) with less pronounced peaks and valleys than with the minimum phase filter and even the unfiltered click. The larger ABR amplitudes also lead to higher ABR signal-to-noise ratios (Fig. 3). Although the overall level of the unfiltered click is the same as the filtered clicks, the unequal distribution of energy between low and high frequencies [up to 10 dB difference, cf. Fig. 1(b)] results in a substantially increased click threshold for the unfiltered click compared to the filtered clicks. The different click peak amplitude between filter types [Fig. 1(a)] might explain the discrepancies in SNR. However, Spearman’s rank correlation coefficient between click peak amplitude and SNR is not significantly different from zero, if the factors level and filter type are partialled out (p > 0.5). If only the factor level is partialled out, the correlation coefficient is significantly different from zero (r ¼ 0.51, p < 0.0006). This underlines the importance of accurate spectral and waveform calibration for comparable ABR recordings. In summary, we recommend equalization of sound reproduction systems (especially for small animals) with a minimum phase filter because it achieves a very good amplitude and phase response at the same time with a smaller filter order compared to a linear phase filter. Unfiltered clicks may be slightly better than linear phase filtered clicks for recording auditory brainstem responses because of their steeper onset, however, they do not generally excite the auditory system equally at all relevant frequencies which, as shown in this report, may lead to considerable across-animal variability in ABR waveform morphology.

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Beutelmann et al.: Stimulus equalization for brainstem responses

Beutelmann et al.: JASA Express Letters

[http://dx.doi.org/10.1121/1.4903921]

Published Online 19 December 2014

Acknowledgments This work was supported by the Deutsche Forschungsgemeinschaft, Cluster of Excellence “Hearing4all” (G.M.K.) and NIH NIDCD R01-011555 (D.T.). References and links Durrant, J. D., and Boston, J. R. (2007). “Stimuli for auditory evoked potential assessment,” in Auditory Evoked Potentials, Basic Principle and Clinical Application, edited by R. F. Burkard, J. J. Eggermont, and M. Don (Lippincott Williams and Wilkins, Baltimore, MD). Granzow, M., Riedel, H., and Kollmeier, B. (2001). “Single-sweep-based methods to improve the quality of auditory brain stem responses Part I: Optimized linear filtering,” Z. Audiol. 40(1), 32–44. Jewett, D. L., and Williston, J. S. (1971). “Auditory-evoked far fields averaged from the scalp of humans,” Brain 94, 681–696. Koka, K., Holland, N. J., Lupo, J. E., Jenkins, H. A., and Tollin, D. J. (2010). “Electrocochleographic and mechanical assessment of round window stimulation with an active middle ear prosthesis,” Hear. Res. 263, 128–137. Kujawa, S. G., and Liberman, M. C. (2009). “Adding insult to injury: Cochlear nerve degeneration after “temporary” noise-induced hearing loss,” J. Neurosci. 29(45), 14077–14085. National Institute of Mental Health (2002). Methods and Welfare Considerations in Behavioral Research with Animals: Report of a National Institutes of Health Workshop, edited by A. R. Morrison, H. L. Evans, N. A. Ator, and R. K. Nakamura, NIH Publication No. 02-5083 (U.S. GPO, Washington, DC). Oppenheim, A. V., Schafer, R. W., and Buck, J. R. (1999). Discrete-Time Signal Processing, 2nd ed. (Prentice-Hall, London). Riedel, H., Granzow, M., and Kollmeier, B. (2001). “Single-sweep-based methods to improve the quality of auditory brain stem responses Part II: Averaging methods,” Z. Audiol. 40(2), 62–85. Schaette, R., and McAlpine, D. (2011). “Tinnitus with a normal audiogram: Physiological evidence for hidden hearing loss and computational model,” J. Neurosci. 31(38), 13452–13457. Thornton, A. R. D. (2007). “Instrumentation and recording parameters,” in Auditory Evoked Potentials, Basic Principle and Clinical Application, edited by R. F. Burkard, J. J. Eggermont, and M. Don (Lippincott Williams and Wilkins, Baltimore, MD). Zeng, F. G., Kong, Y. Y., Michalewski, H. J., and Starr, A. (2005). “Perceptual consequences of disrupted auditory nerve activity,” J. Neurophysiol. 93(6), 3050–3063.

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Amplitude and phase equalization of stimuli for click evoked auditory brainstem responses.

Although auditory brainstem responses (ABRs), the sound-evoked brain activity in response to transient sounds, are routinely measured in humans and an...
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