PROCEEDINGS of the23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Tonotopic Sensitivity to Supra-threshold Hearing Deficits of theEnvelope Following Response Evoked by Broadband Stimuli
Sarineh KESHISHZADEH1; Viacheslav VASILKOV2; Sarah VERHULST3Hearing Technology @WAVES, Dept. of Information Technology, Ghent University, Belgium

ABSTRACTScalp-recorded electrophysiological Envelope Following Responses (EFRs) have recently gained popularity
as an objective measure of supra-threshold hearing deficits (e.g., as caused by cochlear synaptopathy). To
explore the frequency specificity of EFRs in diagnosing deficits, we recorded EFRs to sinusoidally
amplitude-modulated (AM) white noise carriers with different bandwidths in two participant groups: young
normal-hearing control group and a group self-reported hearing difficulties in noisy listening environments.
Despite individual variability in EFR strength, the group-means revealed minor response differences instimuli with different low-frequency content. The limited contribution of auditory frequency channels below
2 kHz to the EFR was confirmed through EFR simulations from a biophysically-inspired model of the human
auditory periphery. Further investigation showed that the minor low-frequency contribution stems from thelack of AM coding in individual low-frequency channels, although the overall spike-rate increases forstimulation with wider carrier bands. In conclusion, despite the broadband cochlear excitation, the broadband
EFR mostly reflects summed AM coding strength in frequency channels above 2 kHz. To increase thefrequency sensitivity of the EFRs it is necessary to carefully investigate the bandwidth and modulation
frequency of the stimulus.
Keywords: Envelope Following Responses, Frequency sensitivity, Broadband modulated stimuli

1. INTRODUCTION
Threshold audiometry at frequencies between 250-8000Hz does not quantify the possible suprathreshold hearing deficits in listeners with normal hearing thresholds. One of the possible sources ofsupra-threshold hearing deficits is loss of auditory nerve (AN) fibers (i.e., cochlear synaptopathy) as
a result of noise exposure or aging. The synaptopathy leaves the outer-hair-cells intact and does notaffect the audiometric thresholds. Recently, auditory evoked potentials such as Auditory Brainstem
Responses (ABRs) and Envelope Following Responses (EFRs) have been proposed to quantify thesesupra-threshold hearing deficits. EFRs reflect the phase-locking strength to the modulated sounds (1)and are sensitive to synaptopathy in animals (2). Hence, EFRs could be more robust metric to measurethese types of fibers synchrony to the modulated stimulus. However, EFRs are confounded by stimulus
and subject-specific factors (3, 4) as well as the spread of the basilar-membrane excitation (5).
To evaluate the diagnostic power and tonotopy of frequency-specific EFRs in humans, weinvestigated which cochlear frequency regions contribute to the scalp-recorded population response.
Therefore, we took an experimental approach in which we adopted, (i) white-noise carriers of various
bandwidths with different low cut-off frequencies, (ii) stimuli with a modulation frequency (MF) of
120 Hz to avoid cortical contributions to the response and (iii) a stimulus level of 70-dB-SPL toencompass the contribution of a range of low and high-threshold AN fibers to the EFR. We recorded
EFRs in groups with normal audiograms but with or without self-reported hearing difficulties in noisy
environments. The former group might be representative of the target synaptopathy expected group
without hearing thresholds deficits.
To further investigate the origin of the experimental EFRs differences to noise carriers of different
bandwidths, we adopted a model-based approach (6). The model offers a promising way to further
explore the influence of different stimuli characteristics on the frequency sensitivity along the1Sarineh.Keshishzadeh@ugent.be
Viacheslav.Vasilkov@ugent.be
3S.Verhulst@ugent.be265131

different processing levels of the auditory periphery (i.e., cochlea, AN and brainstem). Given that
previous studies have shown that increasing the MF of a broadband noise, increases the behavioral
AM detection thresholds (7) and decreases the EFR amplitudes (8), we focused on investigating theeffect of different modulation frequencies in encoding the stimulus envelope in basilar membrane(BM) velocity and AN spike rates.
First, the experimental stimuli and the participated groups are described. After which Sections 2and 3 detail the implemented methods and show comparisons between experimental and simulated
EFRs. Finally, the discussion states possible reasons for the lack of AM coding in the experimental
data at lower frequencies and make suggestions to improve the broadband EFRs frequency sens itivity
based on the model simulations.

2. Methods
EFRs were recorded to five filtered white-noise carriers in [0.25-22], [0.5-22], [1-22], [2-22] and[4-22] kHz frequency bands and were 100% modulated with a 120 Hz pure tone. The spectrally widest
stimulus was presented at 70-dB-SPL and the other bandwidth stimuli had lower level to maintain asimilar spectral level in all filtered stimuli. The stimulus epochs were 1.25-s long and repeated 370times. EFRs were recorded with a 64-channel Biosemi EEG system. Details of the experimental setup
were described elsewhere (9). Sixteen normal-hearing (NH) subjects aged 18-30 years (24.21±4.10
years, six female) and nine audiometric normal hearing subjects with self-reported hearing difficulties
in noisy environments (NHSR) aged 23-49 (33.78±8.57 years, three female) participated in theexperiment. All participants had hearing thresholds below 25 dB-HL, except for one participant who
had 30 dB-HL loss at 250 Hz. The best audiometric ear at 4 kHz was chosen for the monaural
stimulation. During the recording, the subjects were seated in a comfortable chair in an acousticallyand electrically shielded sound booth watching silent movies with subtitles to keep them awake. All
participants were informed about the experimental procedure according to the ethical procedure at
Ghent University and an informed consent was received.
2.1 Experimental Data Analysis
For each condition, the responses from the Cz channel were filtered between 60 and 600 Hz witha 800th order Blackman window-based band-pass FIR filter in MATLAB using the filtfilt function.
Then, the signals were epoched in 1-s long blocks starting 0.25 after the stimulus onset to focus on
the steady state part of the response. A baseline correction was applied by subtracting the average ofeach epoch, before averaging across trials. Thirty epochs with the highest peak-to-trough absolutevalues were removed to drop noisiest epochs and keep an equal number of epochs to average for allconditions and subjects. We adopted a bootstrapping method to identify the EFR strength and signalto-noise ratio in the frequency domain (10): First, the Fast Fourier Transform (FFT) of each epoch
was computed. Then, an averaged FFT over 340 epochs randomly drawn with replacement out of total
epochs was calculated. This procedure was repeated 200 times and resulted in a nearly Gaussian
distribution of mean spectra of the responses. The absolute value of the mean of 200 averaged epochs,
yielded the EFRs in the frequency domain. Secondly, the same procedure was followed with 1000 (ofwhich half were phase-flipped) repeated averages to estimate the noise-floor. Finally, the subtraction
between the absolute values of the signal and noise-floor averages resulted in the stimulus-driven EFR
spectrum. To calculate the EFR strength, we included the magnitude of fundamental MF and any
visible harmonics. Only two harmonics were visible in our data, we hence considered the magnitudeof the fundamental frequency of the modulator (i.e., f0 =120 Hz) and two harmonics:‫ܴܨܧ‬௦௧௥௘௡௚௧௛ ൌ σଶ௜ୀ଴ห‫݁݀ݑݐ݅݊݃ܽܯ‬௙೔ ห(1)2.2 Modelling Approach
We simulated EFRs using a biophysically-inspired model of the human auditory periphery (6). The
same stimuli as were adopted in the experiment presented to the model, but with a total duration of600 ms. The last 400 ms of the simulated responses were used for the EFR calculation. Further analysis
steps were identical to the experimental data analysis. Given that the stimulus was noise, simulated
responses were averaged 100 times before calculating the EFR. The modelling approach, brings thebenefit of allowing a frequency-specific investigation of the sources contributing to the EFRs to26514

modulated broadband stimuli at both the BM and AN processing levels. To this end, we explored theenergy, i.e., the root-mean-square (RMS), and modulation strength at each simulated characteristicfrequency (CF) channel. We calculated the modulation strength at both BM and AN levels in the time
domain by averaging the BM velocity and AN spike rates across all cycles for each epoch. For a MFof 120 Hz, each epoch encompasses 48 cycles and taking into account the 100 repet itions of thestimulus representation, the half of the peak-to-peak amplitude of the 4800 averages were defined as
the modulation strength of each CF channel. We followed the same procedure to calculate themodulation strength for the AN simulations to keep a fair comparison with the BM simulations.

3. Results
3.1 EFR Magnitudes Evoked by Broadband Stimuli
Figure 1, shows the EFR magnitudes for the different stimulus conditions and groups (i.e., NH andNHSR). Even though the data points for each condition show individual variabilities, the group-means
were constant across conditions for stimuli of low cut-off frequencies up to 2 kHz. A decrement wasobserved for the last condition with the stimulus bandwidth of [4-22] kHz. The normal-hearing modelpredicted EFRs (diamonds in Figure 1), reveals the same trend as the experimental group-means acrossconditions. The NHSR group-mean EFRs of the participants were lower than the EFRs of the NH
participants in each condition. This finding is consistent with the idea that NHSR listeners may sufferfrom supra-threshold hearing deficits.
3.2 CF Contributions to the EFR
To explore the origin of the frequency-dependent behavior of the EFRs, we studied the contributionof different CF channels for different stimulus conditions to population responses at BM and AN
levels of the model. Figure 2 shows simulated excitation patterns and modulation responses to theexperimental stimuli of BM velocity (Figure 2a and 2b) and AN responses (Figure 2c and 2d). The
excitation pattern shows increased velocity at CF channels corresponding to those contained in thestimulus frequency, while the BM modulation response, shows a sloping response starting one octave
below the excited CF channels, and a constant behavior at CF channels above the 4 kHz. A similar
pattern can be observed at the AN level, where a sharp increase in spike rate is observed forfrequencies contained in the stimulus in the excitation pattern. A sloping spike rate increment inmodulation response was again observed when evaluating the modulated response at AN. Since theEFR is a population response across the CF channels, the overlapping modulation response for thefirst three conditions, explain the equal group-means observed in the experimental data in Figure 1.

Figure 1 – Recorded EFR magnitudes in NH (circles) and NHSR (squares) listeners. The corresponding
group-means are shown with left pointing triangles. Simulated EFRs for a normal-hearing model are shownby black diamonds.

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Figure 2 – Simulated excitation patterns and modulation responses calculated for each CF channel to theexperimental stimuli from the BM (a and b) and AN (c and d) processing levels of the model.
To investigate the absence of AM coding at low CFs for 120 Hz modulator, we further evaluatedthe effect of MF and CF contributions to the modulated response in the broadest bandwidth condition,i.e., [0.25-22] kHz. First, a time domain visualization from two CF channels is shown in Figure 3, for
MFs of 20 and 120 Hz. CF channels of 500 and 4000 Hz are shown and evaluated for their AM content
at the BM velocity (Figure 3a) and AN spike rate (Figure 3b). Both responses to non-modulated andmodulated broadband stimuli are shown and the response from CF=500 Hz shows no noticeable
difference between non-modulated and 120 Hz modulated noise at both BM and AN processing levels.
However at the CF=4000Hz the effect of MF can be observed. A more direct comparison of themodulation strength at two CF channels was made in Figures 3c and d at BM and AN levels, where
the 4800 averaged cycles at 120 Hz MF and 8×100=800 averaged cycles at 20 Hz MF are shown.
These figures reveal the lack of modulation response at 120 Hz MF in low CF channel (500 Hz) at
both BM and AN levels, which are in agreement with Figure 2b and c, where no modulation response
can be seen at low CFs.

4. Discussion
The simulation results in response to broadband stimuli confirmed that there is a reduced
contribution from lower CF channels and higher modulation frequencies (120 Hz) at the AN level tothe EFR. To study the impact of MF and different cochlea CF regions sensitivity to the EFR, Figure 4
compares the excitation pattern and modulation response of BM velocity and AN spike rates inresponse to a range of modulation frequencies between 20 and 120 Hz. Although there is anapproximately equal excitation pattern in all MFs at both BM and AN levels (Figure 4a and c), themodulation responses show different behavior for different MFs. For a specific MF, the modulation
response at BM and AN increases from the apical end to the base. Decreasing the MF, enhances themodulation response at all CFs, especially at the basal end and at the BM level (Figure 4b). Even
though the AN level largely reflects the response from the cochlea, we observe that the sloping andincreasing modulation response saturates for higher CFs to a fixed MF. Therefore, in spite of anincreased modulation response at BM level with decreasing MF, especially at higher CFs, thesaturation mechanism at the AN level (due to saturating AN fibers) moves the EFR frequency
sensitivity to the lower CFs. One of the possible reasons for the enhanced modulated response oflower MFs at BM, could be the wider filters at higher CFs where more sidebands of the noise -carrier
fall inside the cochlear filters and increase the energy of the modulation resp onse. In this context,increasing the MF moves the sidebands further away from the carrier component and decreases themodulation response within a single CF channel (11).

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CF=500Hz
CF=4000Hz
4000Hz 500Hz

Figure 3 –One hundred averaged simulated time-domain epochs in response to broadband stimuli modulated with different
MFs in two CF channels at the (a) BM and (b) AN levels of the model. The averaged cycles across each epoch at (c) BM and(d) AN levels.

Based on the model simulations, we conclude that the equal magnitude EFRs for the first threeexperimental conditions is a consequence of small differences of the curve area of under MF=120 Hz
AN modulation response at low CFs and the saturation which occurs at about 4 kHz and higher CFs(Figure 4d). The decrement in the EFR for [4-22] kHz experimental condition is caused by the larger
difference between areas under the curves with the previous, broader conditions (shown with dashedlines in Figure 4b and d). The model study suggests that for broadband noise stimuli, modulation
frequencies lower than 120 Hz can provide a better tonotopic-sensitive EFRs for lower CFs. However,there is a possibility of contribution from higher auditory processing levels to be involved in theresponse.

Figure 4 – Excitation patterns and modulation responses at BM (a and b) and AN (c and d) levels for different MFs.

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ACKNOWLEDGEMENTS
Work supported by European Research Council starting grant ERC-StG-678120 (RobSpear).

REFERENCES
1. Shaheen LA, Valero MD, Liberman MC. Towards a diagnosis of cochlear neuropathy with envelope
following responses. Journal of the Association for Research in Otolaryngology. 2015;16(6):727-45.
2. Parthasarathy A, Kujawa SG. Synaptopathy in the aging cochlea: Characterizing early-neural deficits inauditory temporal envelope processing. Journal of Neuroscience. 2018;38(32):7108-19.
3. Trune DR, Mitchell C, Phillips DS. The relative importance of head size, gender and age on the auditory
brainstem response. Hearing research. 1988;32(2-3):165-74.
4. Mitchell C, Phillips DS, Trune DR. Variables affecting the auditory brainstem response: audiogram, age,gender and head size. Hearing research. 1989;40(1-2):75-85.
5. Bharadwaj HM, Masud S, Mehraei G, Verhulst S, Shinn-Cunningham BG. Individual differences reveal
correlates of hidden hearing deficits. Journal of Neuroscience. 2015;35(5):2161-72.
6. Verhulst S, Altoe A, Vasilkov V. Computational modeling of the human auditory periphery: Auditorynerve responses, evoked potentials and hearing loss. Hearing research. 2018;360:55-75.
7. Kohlrausch A, Fassel R, Dau T. The influence of carrier level and frequency on modulation and beatdetection thresholds for sinusoidal carriers. The Journal of the Acoustical Society of America.
2000;108(2):723-34.
8. Purcell DW, John SM, Schneider BA, Picton TW. Human temporal auditory acuity as assessed byenvelope following responses. The Journal of the Acoustical Society of America. 2004;116(6):3581-93.
9. Garrett M, Verhulst S. Applicability of subcortical EEG metrics of synaptopathy to older listeners withimpaired audiograms. bioRxiv. 2018:479246.
10. Zhu L, Bharadwaj H, Xia J, Shinn-Cunningham B. A comparison of spectral magnitude and phase-locking
value analyses of the frequency-following response to complex tones. The Journal of the AcousticalSociety of America. 2013;134(1):384-95.
11. Joris P, Schreiner C, Rees A. Neural processing of amplitude-modulated sounds. Physiological reviews.
2004;84(2):541-77.

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