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A Potential Neurophysiological Correlate of Electric-acoustic Pitch Matching in Adult Cochlear Implant Users: Pilot Data

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A potential neurophysiological correlate of electric-acoustic pitch matching in adult cochlear implant users: Pilot data

The overall goal of this study was to identify an objective physiological correlate of electric-acoustic pitch matching in unilaterally implanted cochlear implant (CI) participants with residual hearing in the non-implanted ear. This study utilized a method of presenting electrical and acoustic stimuli that continuously alternated across ears.  These stimuli were either matched or mismatched in pitch. Auditory Evoked Potentials (AEP) were obtained from 9 CI users.  Results indicated that N1 latency decreases when the acoustic frequency of the tone presented to the non-implanted ear increases. More importantly, there was an additional shortening of N1 latency in the pitch matched condition. These results indicate the potential utility of N1 latency as an index of pitch matching in cochlear implant users. (119 words ; < 250 words)

Keywords: electric-acoustic pitch matching; auditory evoked potential; N1 latency; (8 keywords)

Subject classification codes: include these here if the journal requires them


One fundamental function of cochlear implants (CI) is to mimic the natural tonotopic frequency-position function of a normal hearing cochlea, in which lower frequency sounds stimulate locations closer to the apex and higher frequency sounds stimulate locations closer to the base. Cochlear implant speech processors analyze the incoming acoustic signals into frequency bands and assign them to the implanted electrodes in the form of a frequency allocation table. In the frequency allocation table (FAT), apical electrodes are stimulated in response to low frequency sounds and basal electrodes are stimulated in response to high frequency sounds in an attempt to mimic the tonotopicity of a normal cochlea.  Implanted electrodes are activated in response to acoustic energy within the passband of each filter (as specified in the FAT). However, the characteristic frequency of the spiral ganglion neurons that are stimulated (which can be estimated using the spiral ganglion frequency-position function, Stakhovskaya et al. 2007) may not align with the acoustic stimulus frequency.  Therefore, in postlingually deaf patients there is likely a mismatch between the pitch percept elicited by the cochlear implant electrode in response to a given acoustic stimulus and the pitch percept elicited by the same acoustic stimulus in an ear with normal hearing.  The characteristic frequency of the stimulated neurons could be higher, similar, or lower than the frequency of the acoustic stimulus, depending on the FAT, the size of the cochlea and the location of each electrode in the cochlea.

As a result of this position-frequency mismatch, unilateral CI users with residual hearing in the non-implanted ear need to both adapt to the frequency mismatch in the implanted ear and integrate the acoustic information from the non-implanted ear when they listen. The existence of this group of CI users permits direct matching of the pitch perceived in response to stimulation of intracochlear electrodes to the pitch elicited by an acoustic frequency. This measure (electric-acoustic pitch matching) can be useful to determine whether listeners show adaptation to the frequency mismatch described above after different amounts of listening experience with the cochlear implant (Francart et al., 2008; McDermott et al., 2009; Reiss et al. 2007, 2008, 2014, 2015; Svirsky et al., 2012; Tan et al., 2012; Vermeire et al. 2015). The neural basis for this type of adaptation may involve a combination of basic neural encoding in the auditory system and additional higher level processing. In a previous study (Tan et al., 2017) we showed that the pitch matching functions obtained in 16 CI subjects were generally 0.9 to 1.2 octaves lower than the spiral ganglion functions and 0.2 to 0.27 octaves higher than the frequency allocation table functions, much closer to the frequency allocation table functions than the spiral ganglion functions. These findings are consistent with the possibility that adaptation to the frequency-position function imposed by cochlear implants is not always complete. The present study examines a potential neurophysiological correlate of electric-acoustic pitch matching by examining scalp-recorded auditory evoked potentials in unilateral CI subjects when they are presented with alternating stimulation to one intracochlear electrode and different acoustic tones, some of which were pitch matched to the stimulation electrode while other tones were not.

P1-N1-P2 is an ‘obligatory’ or ‘sensory’ evoked potential complex that is commonly used to examine sound processing in the central auditory system in normal hearing (NH) listeners (Steinschneider and Dunn, 2002; Naatanen and Picton, 1987). In recent years, this auditory evoked potential complex has been applied to CI users (e.g., Beynon et al., 2005; Dorman et al., 2007; Eggermont et al., 2003; Firszt et al., 2002; Jiwani et al., 2013; Kelly et al., 2005; McLaughlin et al., 2013; Ponton et al., 1996; Pantev et al., 2006; Sharma et al., 2014; Thai-Van et al., 2010; Zhang et al. 2009). The P1-N1-P2 complex is sensitive to changes in the physical features of a stimulus in a highly reliable and repeatable manner (Naatanen and Picton, 1987, Stapells, 2002, Martin et al., 2007, Tremblay et al. 2003). For instance, lowering stimulus intensity will result in reduced amplitudes and increased latencies (Hyde, 1997; Lightfoot and Kennedy, 2006; Stapells, 2002). The P1-N1-P2 complex is also sensitive to changes in stimulus frequency (e.g., Martin et al., 2007; Naatanen and Picton, 1987;  Stapells, 2002).  The N1 component of the auditory evoked potential, a prominent negative deflection that peaks at approximately 100 msec after the onset of the stimulus, decreases in latency as the frequency of a tone burst stimulus increases (Pantev et al., 1988; Picton et al., 1978).  N1 amplitude decreases for high frequency tones beyond 2 kHz even for signals of the same intensity (Picton et al., 1978).

Adaptation to the frequency-position relationship imposed by cochlear implants is not always complete in CI users as previously shown in our electric-acoustic pitch matching study (Tan et al., 2017).  Comparison of AEP responses to electrical and acoustic stimuli that are either matched or mismatched in pitch might provide insight into the neural mechanisms underlying the adaptation process. The aim of this study is to investigate whether N1 latency can serve as a possible objective index of electroacoustic pitch matching in CI users. In this initial look, N1 latency was chosen based on pilot data indicating that it was less variable than N1 amplitude in CI users.  The hypothesis is that the N1 latencies recorded with pitch matched and mismatched stimuli will be different. Thus, this study will determine whether N1 latency can index pitch-matching of electrical and acoustic stimulation, and be considered as a possible metric to track the adaptation process of CI users over time after cochlear implantation.



Nine postlingually deafened adults participated. Each used a cochlear implant in one ear and had useable residual hearing in the non-implanted ear. Eight of these subjects were implanted with Cochlear devices and the remaining two participants were implanted with Advanced Bionics Corp. (AB) devices. All intracochlear electrodes in the devices were active. Participants were implanted at the Cochlear Implant Center in the Department of Otolaryngology at New York University. The degree of functional hearing in the non-implanted ear as well as additional demographic information is shown in Table 1. An electrode with reliable behavioral pitch matching for each individual was selected for the experiment.  Most subjects had much better residual hearing in the low frequencies (particularly in the vicinity of 500 Hz) than in the high frequencies and therefore the third most apical electrode was selected.  This electrode was pitch matched between 217 Hz and 830 Hz by different subjects (Tan et al., 2017).

Experimental setup : Behavioral pitch matching

Before AEP testing was performed, pitch matching data were obtained in each participant by presenting pure tones to the non-implanted ear via a headphone and electrical stimulation of a single electrode in the implanted ear. Electrical stimulation of the single electrode was accomplished via streaming hardware for Cochlear devices and direct audio connection for AB devices. To present electrical stimulation centered at the single electrode for AB devices, a pure tone set to a frequency equivalent to the center frequency of the analysis band associated with the electrode was presented to the speech processor via direct audio connection. We have previously shown that this results in stimulation of the desired electrode with very little stimulation delivered to adjacent electrodes (Tan et al., 2017).  Five hundred msec bursts of electrical stimulation delivered to the CI ear were interspersed with 500 msec of acoustic stimulation to the non-implanted ear. In other words, acoustic and electrical stimulation were alternated using a 500 msec duty cycle across two ears (see Fig 1). The acoustic frequency was adjusted by the listener until it was perceived as matched in pitch to the electrical stimulation.  This setup was implemented in C++ for both Cochlear and AB devices. Under this setup, one intracochlear electrode was electrically stimulated at the participant’s maximum comfortable level (MCL) with the desired rate and pulse width. For Cochlear devices, a single electrode was electrically stimulated at a rate and pulse width as specified in the participant’s clinical map using our program via the Nucleus Implant Communicator (NIC) research software library provided by Cochlear Ltd. The stimulation pulses were sent via a standard FreedomTM speech processor. For AB devices, the electrical stimulation was delivered by streaming a 500 msec tone whose frequency was the same as the center frequency of the analysis band associated with the electrode of interest.  The tone was delivered to the implanted ear using a direct audio interface cable via a Harmony speech processor. The speech processor was fitted with the participant’s latest clinical map by SoundWave 2.1™. The speech processor was switched to auxiliary input only mode.

The acoustic tones for the non-implanted ear were amplified using the gain function prescribed using the NAL-RP fitting formula based on the participant’s pure tone audiogram (Byrne et al., 1986, 1990). All acoustic stimuli were sampled at 22.05 kHz with 16-bit resolution using a Sound Blaster Audigy SZ soundcard and amplified by a Sony amplifier, before being presented to patients via a Sennheiser HD580 headphone. The acoustic tone was weighted by a trapezoidal window with a rise/fall of 20 msec to prevent spectral splatter. Prior to testing, the participant was asked to confirm that they could hear the test tones.

Procedure for behavioural matching pitch between electric and acoustic stimuli

CI participants were instructed to adjust the intensity of the acoustic tone (presented to the non-implanted ear) to a level perceived as ‘loud, but comfortable’ and close to the perceived loudness elicited by the electrode stimulation. They were then instructed to adjust the frequency of that tone until it matched the pitch elicited by electrical stimulation of the single electrode in the contralateral ear.  All adjustments of the acoustic tone were either self-driven by the participant or by the experimenter under the participant’s verbal instruction via a slider on a computer screen. CI participants were also instructed to listen to acoustic tones that were higher or lower than the electrical stimulation in pitch percept, before they decided upon the pitch-matched tone.

As described in (Tan et al., 2017), CI participants were required to complete six pitch-matching trials for one single electrode stimulation. The starting frequency of the acoustic tone was randomized over a range of 20 Hz to 10000 Hz for each trial to assess the presence of non-sensory bias effects using the two “checks” proposed by Carlyon et al. (2010).  Frequency values obtained from trials were also fit to a standard normal distribution and values outside a 99.5% confidence interval were discarded. The final pitch-matched value to be used in the pitch matched condition for AEP testing was the average of the remaining trials. At the 99.5% confidence level, 8 out of 9 participants did not have any outliers. For the remaining 1 participant, 1 to 3 trials were discarded.

Experimental setup: Auditory evoked potential recording

The same experimental setup used for behavioral pitch matching was used to present both acoustic and electric stimuli for AEP recording (Fig. 2). The acoustic stimulus was amplified in the same manner used in behavioral pitch-matching with an input level of 70 dB SPL. In addition, CI participants confirmed that both the acoustic and electric stimuli were audible prior to each test condition. AEPs from all CI participants were obtained with electrical stimulation at the third most apical electrode of the implanted electrode array as shown in Table 3. Please note that to be consistent across different brands of cochlear implants, and to be consistent with Tan et al. (2017), electrodes were numbered from apex to base even though Cochlear Ltd. manuals use the opposite order (base to apex).  The center frequency of the analysis band allocated to the electrode selected for electrical stimulation and the corresponding average pitch matched frequency are included in Table 3. All participants watched a muted video during the recordings.

Cochlear device users

The center frequency of the analysis band associated with electrode 3 was 500 Hz for all Cochlear CI participants in this study in accordance to their clinical FATs. All AEP recordings for Cochlear CI participants were obtained with electrical stimulation of Electrode 3 and an acoustic tone was presented sequentially to the contralateral ear in 6 test conditions listed as follows:

  1. 250 Hz – one octave below the target 500 Hz tone,
  2. 375 Hz – center frequency of analysis band associated with the adjacent apical electrode; 2,
  3. 500 Hz – center frequency of analysis band associated with electrode 3,
  4. 625 Hz – center frequency of analysis band associated with the adjacent basal electrode; 4,
  5. 1000 Hz – one octave higher than the target 500 Hz tone, and
  6. pitch-matched condition – the average pitch matched frequency of the electrode obtained from the behavioral pitch-matching experiment.

CI 4 had a steep sloping hearing loss and was not able to hear the tones at 250 Hz and 1000 Hz. Hence, Conditions 1 and 5 were changed to 300Hz and 800Hz for CI 4.

AB device users

For the two CI participants using AB devices, electrode 3 was stimulated. The acoustic tones were presented to the non-implanted ear as listed in the following 6 test conditions:

  1. 270 Hz – center frequency of the analysis band associated with electrode 1,
  2. 385 Hz – center frequency of the analysis band associated with electrode 2,
  3. 540 Hz – center frequency of the analysis band associated with electrode 3,
  4. 642 Hz – center frequency of the analysis band associated with electrode 4,
  5. 906 Hz –center frequency of the analysis band associated with electrode 5, and
  6. pitch-matched condition – the average pitch matched frequency of the electrode obtained from the behavioral pitch-matching experiment.

All AEPs were recorded using a Neuroscan system with continuous, interleaved presentation of single-electrode electrical stimulation followed by contralateral acoustic tone.  Thus, auditory stimulation was continuous and alternated between ears.  Each pair of electric and acoustic stimuli was presented 500 times, and the AEP in response to the onset of the tone was recorded. Acoustic signals were presented to the patient via an ER2 insert earphone. The maximum output level did not exceed 93.6 dB, which is well within the range that these earphones can deliver without distortion. Again, it was confirmed that the participant was able to hear the tones before the recording was started.  The trigger was inserted at the onset of the acoustic stimulus (the offset of the electrical stimulation). The onset and offset of the acoustic stimuli were enveloped using a trapezoidal weighting window of 20-ms.  The decay of the electrical stimulus after turn-off did not aggressively affect the cortical evoked potentials at some midline-central electrodes. Further re-referencing to the contralateral mastoid helped to reveal the physiological response.

AEP responses were recorded from 64 channels referenced to electrode Cz.  Vertical and horizontal EOG channels were used to monitor eye movements and eliminate eye blinks. The ongoing EEG was digitized at 1000 Hz, amplified 1000 times, and filtered between 0.15 and 200 Hz. The AEP responses were processed offline into 991msec epochs after ocular artifact reduction. The responses in each epoch were baseline corrected and filtered using a low delay, zero phase-shift filter between 1 and 30 Hz at 24 dB/octave. After artifact rejection (+100 microvolts) and averaging, a minimum of 97.4% (487/500) sweeps were accepted for computation of the averaged waveform in each condition for each participant. To minimize the artifact introduced by the CI stimulation, the recordings were re-referenced to the mastoid electrode (M1/M2) contralateral to the implanted ear.


Pitch matching

The reliability of the pitch matched frequencies at the selected electrode in Table 3 for each CI participant were checked by subjecting them to the non-sensory bias checks proposed by Carlyon et al. (2010) presented in Table 2. None of the p-std values was lower the 0.05, suggesting that the standard deviation of starting frequencies is significantly greater than that of the final pitch matched frequencies. Overall reliability was good.

As shown in Table 4, all participants, other than CI 1, and CI 9, perceived a higher pitch than the frequencies imposed by the FAT function at the electrode. In other words, six participants experienced a ‘basalward shift’ in pitch percept and two participants experienced a ‘apicalward shift’ at the selected electrode. CI 5 experienced a ‘no shift’ in pitch percept. On average, the pitch percept is consistent with the results reported in our previous study (Tan et al. 2017).

Auditory evoked potentials

Typical AEP waveforms at electrode site Cz are shown for CI 3 in each of the six test conditions (Fig. 3). The P1-N1-P2 complex was clearly evoked by the onset of acoustic stimulation. In this study, the focus was on the latency of N1, the most prominent negative peak in the P1-N1-P2 complex. The latency of N1 was measured at the center of the peak relative to acoustic stimulus onset (i.e., 0 msec). For bifurcated or distorted peaks, the centroid of the peak was estimated after the AEP response was smoothed, but the measure was made using the original (non-smoothed) waveform.

 Two patterns in N1 latency

Table 4 presents the N1 latencies in the CI participants at Cz for all six test conditions. Grand mean N1 latencies and corresponding standard errors as a function of frequency are shown in Fig. 4.  A regression line was fitted to the grand mean N1 latencies from the first five test conditions (without the pitch-matched condition) to highlight two general patterns. First, grand mean N1 latencies decreased as the frequency of the acoustic tone increased, as would be expected (Picton et al., 1978). Second, N1 latency in the pitch-matched condition was shorter than predicted by the linear regression of the data from the other five conditions. Table 4 shows that the pattern of N1 latencies decrease with increasing frequency also occurs in individual participants. With near-normal hearing, CI 5 should have N1 latencies comparable with those typically obtained in normal-hearing listeners; however, this was not found for this particular participant. CI 5 had the longest duration of deafness of all 9 subjects in the implanted ear (43 years) and was implanted for less than a year at the time of testing.  Further, the non-implanted ear was not “normal” and had hearing loss above 1000 Hz.  It is unclear that typical characteristic N1 latencies can be fully restored in every individual by electrical stimulation in the implanted ear after a period of listening with one ear.  There is an emerging literature indicating that aided auditory evoked potentials do not always show the patterns one might expect and it is likely that similar interactions with device will be present for CIs (e.g., Billings et al., 2011); Chun et al., 2016; Tremblay & Miller, 2011).

In the individual participants, the first pattern of decreasing N1 latency with increasing acoustic frequency was  observed with 8 of 9 CI participants. The two exceptions were CI 8, who had a longer than expected N1 latency in test condition 5 (1080 Hz), and CI 4, with a longer than expected N1 latency in test conditions 4 (625 Hz) and 5 (1080 Hz). The frequency-N1 latency data from each individual CI participant was fitted to a non-linear, 3-parameter exponential function.  The data from CI 7, however, did not converge and was fitted with a 2-parameter exponential function instead. The last column of Table 5 shows that, even though the exact pitch matched frequency differed across the CI participants, N1 latency for every participant was shorter in the pitch matched condition than predicted by the nonlinear regression estimate.  These difference values (from the predictions) averaged -5.3 ms for the pitch matched frequencies and close to zero for non-pitch matched frequencies.  This effect was statistically significant, as confirmed by a two-way analysis of variance that was carried out on the data shown in Table 5.   The two factors were subject and frequency (which could assume two values: pitch matched or non-pitch matched).  The difference in N1 latency regression residuals was significantly shorter for pitch matched frequencies (p=0.029). This shortening of N1 latency in the pitch-matched condition (see Fig. 4 and Table 5) is superimposed on the first N1 latency pattern, which generally decreased in value as frequency increased.

Grand mean AEP waveforms for the pitch matched condition and for condition 3

Grand mean AEP waveforms across Cochlear CI participants (except CI 3, who was evaluated using a different intracochlear electrode) were computed for the pitch matched condition and test condition 3 and are shown in Fig. 5. In this figure, N1 latencies are 105 msec and 108 msec in the pitch matched condition and test condition 3, respectively. The N1 latency in the pitch matched condition was indeed shorter than the N1 latency in test condition 3, the center frequency of the analysis band associated with the stimulating electrode. This provides some support for the hypothesis that N1 latency may be a correlate of behavioral pitch matching.

Responses obtained from odd and even trials

To provide a sense of within-subject repeatability in the pitch matched condition we examined responses to odd and even numbered trials.  Figure 6 shows results from all CI participants.  N1 latency was reasonably stable, more so than N1 amplitude.  This provides some support for our selection of N1 latency as the metric for the study.  Table 6 shows values of N1 latency for all subjects based on odd- and even-numbered trials.  The results were satisfactory in that test-retest reliability was high (2 ms or better, as indicated in Table 6) and the effect size was clearly greater than that (5.3 ms on average, as indicated in Table 5).


This study presents a novel application of the acoustic change complex (ACC) (Ostroff et al., 1998; Martin & Boothroyd, 1999, 2000).  ACC N1 latency served as a correlate of pitch matching and was elicited in response to a stimulus that continuously alternated between ears that were either matched or mismatched in pitch. In this study, the change is both across the two ears (acoustic and implanted) and across modality (electric and acoustic).  N1 latency was elicited by the onset of the tones in this study, in the context of a change from preceding stimulation of a single electrode in the cochlear implant.  In general, N1 latencies decreased as the acoustic tone increased in frequency, which is consistent with observations reported in studies of normal hearing listeners (Pantev et al., 1988, 1989; Woods et al., 1993, 1995; Picton, 1978).  The additional N1 shortening in the pitch matched condition suggests that a binaural electric-acoustic integration process was involved, because a strictly monaural process should have shown results that were independent from the stimulus previously provided to the implanted ear.  In other words, if the process had been strictly monaural, N1 latency values for the pitch matched condition should have fallen squarely on the nonlinear regression line as a function of frequency rather than being significantly below it (see Table 5 and Figure 4).  Integration across ears has been shown to occur in the superior olivary complex (e.g., Moore, 1991).  In this study, this integration was reflected centrally at the level of auditory cortex.  This study demonstrated that N1 latency, which showed shortening in the pitch matched condition, has potential utility as an objective physiological correlate of electroacoustic pitch matching in CI users.  For the types of simple stimulation used in this study, it is likely that the inputs to the two ears are integrated.  This may not apply for more complex stimuli, such as speech (Reiss et al., 2016).

A reduction in ACC N1 latency in the pitch-matched condition was clearly present, on average, but the magnitude of this reduction was small and there was considerable variability across subjects.  If this small effect (reduction of N1 latency at pitch matched stimuli) holds in a larger dataset, this would be an interesting and novel finding with potential clinical application. Further work will be conducted to expand this initial, exploratory study to seek ways to better assess the magnitude of this reduction.  In addition, the search for relevant physiological correlates of pitch matching will not be restricted solely to the N1 component.  Future studies will examine amplitude, latency and topography of N1 alone and in combination with other AEPs in response to each stimulus separately, together, and sequentially.  This may present an opportunity to further validate that the current AEP is not solely evoked by onset of stimulus in the non-implanted ear but by stimulus change across the ears.

The finding of a useful, objective correlate of pitch matching has potential utility for understanding the mechanisms underlying pitch matching and may provide a means to constrain hypotheses about the neurophysiological mechanisms underlying pitch matching changes over time. It will be of interest to determine whether the behavioral changes that have been observed over time in electroacoustic pitch matching correlate with concomitant changes in this novel neurophysiological correlate. In addition, the technique developed could be used to investigate how the processing of sounds is altered when the context in which they are presented changes.  For example, how is processing affected by monaural versus binaural versus sequential processing across ears?    If the technique can be optimized, it might have utility in the future to monitor the adaptation process in CI users who cannot provide a reliable behavioral index (for instance, young children).

This study marks the first attempt at finding a neurophysiological correlate of electroacoustic pitch matching in cochlear implant users with residual hearing in the non-implanted ear. N1 latency is identified as a potential candidate as a neurophysiological correlate of electroacoustic pitch matching.  The two unique patterns in N1 latency observed in pitch matched and mismatched conditions were clear in the majority of the participants in this study. Despite some individual differences, this neurophysiological phenomenon appears to merit attention and further exploration. Previous studies on electroacoustic pitch matching (e.g., Reiss et al., 2007, 2008; Tan et al., 2017) have shown that many CI users do not completely adapt to the frequency-place function imposed by their devices and continue to perceive higher pitched sounds despite years of listening experience after cochlear implantation. Further research is needed to compare N1 latency patterns in CI users with complete and incomplete adaptation.

The existence of a population of unilateral CI users with residual hearing in the nonimplanted ear presents a unique opportunity to explore electroacoustic pitch matching across two ears, and which may shed light on the adaptation process that takes place after cochlear implantation. The neurophysiological correlate of electroacoustic pitch matching identified in this study may provide a metric to evaluate and monitor this process.


This work presents our first attempt to explore the potential relationship between electroacoustic pitch matching and AEPs.  The main findings were that N1 latency in CI participants decreased when the acoustic frequency of tones presented to the non-implanted ear increased, and there was additional shortening of N1 latency in the pitch-matched condition.  Both patterns were statistically significant.   Thus, N1 latency could potentially provide a neurophysiological correlate of pitch matching across ears in CI participants and may serve as a metric to monitor the adaptation process of CI users to their devices.


We are grateful to Drs. Arlene Neuman, Annette Zeman, Ksenia Prosolovich, Elizabeth Glassman, Keena Seward, Ben Guo and Wenjie Wang for their assistance during recruitment and testing of CI participants. This work was supported by NIH/NIDCD grants: DC010834 (CTT), DC03937 (MAS), DC011329 (MAS) and DC05386 (BAM) and PSC-CUNY (BAM). We thank our participants for their help.


Beynon, A.J., Snik, A.F., Stegeman, D.F., van den Broek, P., 2005. Discrimination of speech sound contrasts determined with behavioral tests and event-related potentials in cochlear implant recipients. J. Am. Acad. Audiol. 16, 42-53.

Billings CJ, Tremblay KL, & Miller CW. (2011) Aided cortical auditory evoked potentials in response to changes in hearing aid gain. Int J Audiol.; 50(7):459-67.

Byrne, D.J., and Dillon, H.A. (1986). The National Acoustic Laboratories (NAL) new procedure for selecting the gain and frequency response of a hearing aid. Ear & Hearing, 7, 257-265.

Byrne, D.J., Parkinson, A., and Newall, P. (1990). Hearing aid gain and frequency response requirements for the severely/profoundly hearing impaired. Ear and Hearing, 11(1), 40 – 49.

Carlyon, R.P., Macherey, O., Frijns, J.H., Axon, P.R., Kalkman, R.K., Boyle, P., Baguley, D.M., Briggs, J., Deeks, J.M., Briaire, J.J., Barreau, X., and Dauman, R. (2010) Pitch comparisons between electrical stimulation of a cochlear implant and acoustic stimuli presented to a normal-hearing contralateral ear. J. Assoc. Res. Otolaryngol. 11, 625-640.

Chun I., Billings C.J., Miller C.W., & Tremblay K.L. (2016) Aided Electrophysiology Using Direct Audio Input: Effects of Amplification and Absolute Signal Level. Am J Audiol.; 25(1):14-24.

Dorman, M.F., Spahr, T., Gifford, R., Loiselle, L., McKarns, S., Holden, T., Skinner, M., and Finley, C. (2007) An electric frequency-to-place map for a cochlear implant patient with hearing in the nonimplanted ear. J. Assoc. Res. Otolaryngol. 8, 234-240.

Eggermont, J.J. and Ponton, C.W. (2003) Auditory-evoked potential studies of cortical maturation in normal hearing and implanted children: correlations with changes in structure and speech perception. Acta Otolaryngol. 123(2), 249-52.

Firszt, J.B., Chambers, R.D., Kraus, N., and Reeder, R.M. (2002) Neurophysiology of cochlear implant users I: effects of stimulus current level and electrode site on the electrical ABR, MLR, and N1-P2 response. Ear Hear. 23, 502-515.

Francart‚ T., Jan, B., & Wouters, J. (2008) Sensitivity to interaural level difference and loudness growth with bilateral biomodal stimulation. Audiol. Neurotol. 13, 309-319.

Hyde, M. (1997) The N1 response and its applications. Audiol. Neurotol. 2, 281–307.

Jiwani S.,  Papsin  B.C., and  Gordon  K.A.(2013)  Central  auditory  development  after long-term  cochlear  implant  use.  Clin. Neurophysiol., 124, 9, 1868-1880.

Kelly, A.S., Purdy, S.C., and Thorne, P.R. (2005) Electrophysiological and speech perception measures of auditory processing in experienced adult cochlear implant users. Clin. Neurophysiol. 116, 1235-1246.

Lightfoot, G., and Kennedy, V. (2006) Cortical electric response audiometry hearing threshold estimation: accuracy, speed, and the effects of stimulus presentation features. Ear Hear. 27, 443–456.

Martin, B.A. and Boothroyd, A. (1999) Cortical, auditory, event-related potentials in response to periodic and aperiodic stimuli with the same spectral envelope. Ear Hear. 20(1), 33-44.

Martin, B.A. and Boothroyd, A. (2000) Cortical, auditory, evoked potentials in response to changes of spectrum and amplitude. J Acoust Soc Am. 107(4), 2155-2161.

Martin, B.A., Tremblay, K.L. and Korczak, P. (2008) Speech evoked potentials: from the laboratory to the clinic.  Ear Hear. 29(3), 285-313.

McDermott, H., Sucher, C., and Simpson, A. (2009) Electro-acoustic stimulation. Acoustic and electric pitch comparisons. Audiol. Neurotol., 14 (Suppl. 1), 2-7.

McLaughlin, M., Lopez Valdes, A., Reilly, R.B., and Zeng, F.G. (2013) Cochlear implant artifact attenuation in late auditory evoked potentials: a single channel approach. Hear. Res. 302, 84-95.

Moore, D.R. (1991) Anatomy and physiology of binaural hearing. Audiology 30, 125–134.

Naatanen, R., and Picton, T. (1987) The N1 wave of the human electric and magnetic response to sound: a review and an analysis of the component structure. Psychophysiol. 24(4), 375-425.

Naatanen, R., Sams, M., Alho, K., Paavilainen, P., Reinikainen, K., and Sokolov, E.N. (1988) Frequency and location specificity of the human vertex N1 wave. Electroencephalogr. Clin. Neurophysiol. 69(6), 523-31.

Ostroff JM, Martin BA, and Boothroyd A. (1998) Cortical evoked response to acoustic change within a syllable. Ear Hear., 19, 290-297.

Pantev, C., Hoke M., Lehnertz, K., Lütkenhöner, B., Anogianakis, G., and Wittkowski, W. (1988) Tonotopic organization of the human auditory cortex revealed by transient auditory evoked magnetic fields. Electroencephalogr Clin. Neurophysiol. 69(2), 160-170.

Pantev, C., Hoke, M., Lehnertz, K., and Lutkenhoner, B. (1989). Neuromagnetic evidence of an amplitopic organization of the human auditory cortex. Electroencephalogr. Clin. Neurophysiol. 71, 225–231.

Pantev, C., Dinnesen, A., Ross, B., Wollbrink, A., and Knief, A. (2006) Dynamics of auditory plasticity after cochlear implantation: a longitudinal study. Cereb Cortex. 16(1), 31-36.

Picton, T.W., Woods, D.L., and Proulx, G.B. (1978) Human auditory sustained potentials. II. Stimulus relationships. Electroencephalogr. Clin. Neurophysiol. 45(2), 198-210.

Ponton, C.W., Don, M., Eggermont, J.J., Waring, M.D., and Masuda, A. (1996) Maturation of human cortical auditory function: differences between normal-hearing children and children with cochlear implants. Ear Hear. 17(5), 430–7.

Reiss, L.A., Turner, C.W., Erenberg, S.R., and Gantz, B.J. (2007). Changes in pitch with a cochlear implant over time. J. Assoc. Res. Otolaryngol., 8, 241-257.

Reiss, L.A., Gantz, B. J., and Turner, C. W. (2008) Cochlear implant speech processor frequency allocations may influence pitch perception.  Otol. Neurotol., 29(2), 160-167.

Reiss, L.A., Turner, C.W., Karsten, S.A., & Gantz, B.J. (2014) Plasticity in human pitch perception induced by tonotopically mismatched electro-acoustic stimulation. Neuroscience, 256, 43-52.

Reiss, L.A., Ito, R.A., Eggleston, J.L., Liao, S., Becker, J.J., Lakin, C.E., Warren, F.M., & McMenomey, S.O. (2015) Pitch adaptation patterns in bimodal cochlear implant users: over time and after experience. Ear Hear, 36(2), 23-34.

Reiss, L.A., Eggleston, J.L., Walker, E.P. & Oh, Y. (2016). Two ears are not always better than one: mandatory vowel fusion across spectrally mismatched ears in hearing-impaired listeners. J Assoc Res Otolaryngol., 17(4):341-56.

Sharma, M., Johnson, P.K., Purdy, S.C., and Norman, F. (2014) Effect of interstimulus interval and age on cortical auditory evoked potentials in 10-22-week-old infants. Neuroreport 25, 248-254.

Stakhovskaya, O., Sridhar, D., Bonham, B.H., & Leake, P.A. (2007). Frequency map for the human cochlear spiral ganglion: Implications for cochlear implants. J Assoc Res Otolaryngol, 8, 220–233.

Stapells, D.R. (2002) Cortical event-related potentials to auditory stimuli. In J. Katz, R.F. Burkard, & L. Medwetsky (Eds.), Handbook of clinical audiology, (5th ed., 378–406), Philadelphia, PA: Lippincott, Williams, and Wilkins.

Steinschneider, M., and Dunn, M. (2002) Electrophysiology in developmental neuropsychology. In S. Segalowitz, & I. Rapin (Eds.), Handbook of neuropsychology (2nd ed., Vol. 8, Part 1, Chap. 5, 91–146). Amsterdam: Elsevier.

Svirsky, M.A., Fitzgerald, M.B., Neuman, A., Sagi, E., Tan, C.-T., Ketten, D., & Martin, B. (2012). Current and planned cochlear implant research at New York University Laboratory for Translational Auditory Research. J Am Acad Audiol, 23(6), 422-37.

Tan, C.-T., Guo, B., Martin, B.A., & Svirsky, M. (2012). Behavioral and physiological measure for pitch matching between electrical and acoustical stimulation in cochlear implant patients. Proceedings of Meetings on Acoustics, 15, 050003, DOI:

Tan C.-T., Martin, B.A. & Svirsky, M. (2017) Pitch matching between electrical stimulation of a cochlear implant and acoustic stimuli presented to a contralateral ear with residual hearing. J. Am. Acad. Audiol. 28, 187-199.

Thai-Van  H.,  Veuillet  E.,  Norena  A.,  Guiraud  J., and Collet  L. (2010) Plasticity  of  tonotopic  maps  in  humans:  influence  of  hearing  loss,  hearing  aids  and cochlear implants. Acta Otolaryngol., 2010, 130, 3, 333-337.

Tremblay K.L., Friesen L., Martin B.A. & Wright R. (2003) Test-retest reliability of cortical evoked potentials using naturally produced speech sounds. Ear Hear., 24(3), 225-32.

Tremblay KL, & Miller CW. (2014) How neuroscience relates to hearing aid amplification. Int J Otolaryngol.; 641-652.

Vermeire, K., Nobbe, A., Schleich, P., Nopp, P., Voormolen, M.H., and Van de Heyning, P.H. (2008) Neural tonotopy in cochlear implants: an evaluation in unilateral cochlear implant patients with unilateral deafness and tinnitus. Hear. Res., 245, 98-106.

Vermeire, K., Landsberger D.M., Van de Heyning P.H., Voormolen, M., Kleine Punte A., Schatzer R., & Zierhofer, C. (2015) Frequency-place map for electrical stimulation in cochlear implants: Change over time. Hear Res, 326, 8-14.

Woods, D.L., Alain, C., Covarrubias, D., and Zaidel, O. (1993) Frequency-related differences in the speed of human auditory processing. Hear. Res., 66(1), 46-52.

Woods DL. (1995) The component structure of the N1 wave of the human auditory evoked potential. Electroencephalogr Clin Neurophysiol., 44, 102-9.

Zhang F., Samy R.N., Anderson J.M., and Houston L.(2009) Recovery function of the late auditory evoked potential in cochlear implant users and normal-hearing listeners. J Am Acad Audiol., 20, 397-408.

Table 1. Participant demographics.

Table 2.  Non-sensory bias checks for each individual CI participant in the pitch-matching experiment. ‘p-std’ in the second column is the p-value of the difference between the standard deviation of the starting and final match frequencies ‘Corr’ in the third column is the correlation between the starting and final matched frequency and the corresponding ‘pCorr’ in the fourth column is the p-value of the correlation. ‘Corr’ value would only be considered if ‘pCorr’ is < 0.05.

Table 3.  Electrode selected for AEP recording with each CI participant and the corresponding center frequency and pitch matched frequency for the selected electrode.

Table 4. AEP N1 latencies (msec) at electrode site Cz.

Table 5. Differences between AEP N1 latencies (msec) and nonlinear 3-parameter exponential regression estimates are shown. A negative value indicates that the N1 latency is lower than the corresponding linear regression estimate.  In the pitch matched condition, N1 latency values were systematically lower than would be predicted by the linear regression.

Table 6. N1 latencies (msec) obtained from even and odd trials in the pitch-matched condition are shown.

Figure 1. Pitch matching setup for CI participants using Cochlear device. For CI participants using AB device, the electrical stimulation is replaced by acoustic tone at center frequency of the analysis band allocated to the electrode in same duty cycle.

Figure 2. Experimental setup for AEP recordings.

Figure 3. Typical AEP responses recorded at Cz in CI 3. The AEP response recorded in the pitch-matched condition is indicated by the black line.

Figure 4. Mean AEP N1 latencies in CI participants at electrode site Cz. The green solid line indicates the nonlinear regression trend.

Figure 5. Grand mean responses recorded at Cz for all Cochlear CI participants at the pitch matched frequency, along with the center frequency of the analysis band allocated to the electrode. The pitch-matched condition is shown in black and test condition 3 (500 Hz) is shown in red. N1 latency is shorter in the pitch matched condition.

Figure 6. N1 recorded at Cz is shown for each CI participant in response to all trials (black), odd-numbered trials (light gray), and even-numbered trials (dark gray) in the pitch-matched condition.

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