Abdala, Carolina

Guerit, Francois Marie Louis Paul

Luo, Ping

Shera, Christopher A.

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Dec 19, 2017Estimates of human cochlear tuning derived from DPOAE reflection-component delaysAbdala, Carolina; Guérit, François; Luo, Ping; Shera, Christopher A.Publication date:2013Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Abdala, C., Guerit, F. M. L. P., Luo, P., & Shera, C. A. (2013). Estimates of human cochlear tuning derived fromDPOAE reflection-component delays. Poster session presented at 36th Annual Midwinter Meeting of theAssociation for Research in Otolaryngology, Baltimore, MD, United States.INTRODUCTIONESTIMATES OF HUMAN COCHLEAR TUNING DERIVED FROM DPOAE REFLECTION-COMPONENT DELAYSCarolina Abdala1,2,  François Guérit3, Ping Luo1 and Christopher A. Shera4,51House Research Institute;  2University of Southern California, Los Angeles, CA   3Technical University of Denmark, Lyngby, Denmark;   4Eaton-Peabody Laboratories,  5Harvard Medical School, Boston, MADISCUSSIONMETHODS0.7 1 1.5 2 3 3.6123510203050Frequency (kHz)  −40−30−20−100100.7 1 2 3.6 6 8123510203050Frequency (kHz)  −40−30−20−10010200.7 1 1.5 2 3 3.6123510203050Frequency (kHz)  −40−30−20−10010200.7 1 1.5 2 3 3.6123510203050Frequency (kHz)  0.7 1 1.5 2 3 3.6123510203050Frequency (kHz)  0.7 1 1.5 2 3 3.6123510203050Frequency (kHz)    5 6 81.20.80.40Tuning ratioTuning ratio used for QERB calculationI. Calculating Delays III. Estimating TuningII. Modeling Delay TrendFigs. 2-4. Calculating delay in three subjects.Panel A - DPOAE level (black) and noise (gray).Panel B - IFFT-separated reflection or “R-component” level (blue) and reflection-specific noise floor (gray). To be accepted, data points were at least 6 dB above both DPOAE and R-component noise floor. The red points are ac-cepted values; segments where the blue line is visible did not meet this SNR criteria. Panel C - R-component delay normalized in pe-riods as NR. Only data points shown in red were used in estimating the delay trend.Fig. 5. Data from the young-adult subject shown in Fig. 3. Delay values are weighted by R-compo-nent energy, applying |PR/Pref|2. The blue line and red points denote reflection level, PR.   Pref  in cyan is a  local estimate of mean R-component level. The green points (re: right axis) display the weighting assigned each delay value.Figs. 6-8. Energy-weighted loess fit (black line) and individual delay values (colored points) for three age groups. Weighting is denoted by color (re: right axis). NOTE: Because weighting was calculated locally, it cannot be precisely equated across frequency. Fig. 9. R-component delay data from one young adult calculated at peaks in fine struc-ture only. (A) A peak-picking algorithm was ap-plied to mildly smoothed R-component level (blue line) and peaks were defined by three fre-quencies (red points); (B) Peak frequencies represented on corresponding delay data.   Figs. 10-12.  Loess trend line fit to R-compo-nent delay data in three age groups. Delays were taken at peaks in  fine structure only. Energy Weighting Peak PickingFig. 17. The loess fit from energy weighting (EW) versus peak picking (PP) differed slightly, espe-cially at high frequencies. A loess fit was calcu-lated as the mean of trend lines derived from the two strategies and is shown here for the young-adult group. 95% CIs (   ) were calculated as sqrt(CIEW2 + CIPP2). The mean trend line was used in estimates of tuning.Fig. 18.  Mean loess trend lines for seven age groups. There is a general increase in delay with increasing frequency and a downward bend in delay at ~1  kHz for all age groups; this bend de-notes a putative apical-basal (a|b) transition and a break in cochlear scaling.    QERB(CF) = r(CF/CFa|b)NR(f)|f=CF  *METHODSFig. 19 (left). The tuning ratio, r, depicts the covaria-tion between cochlear tuning and emission delay [rspecies = QERB/NSFOAE] calcu-lated from cat, guinea pig and chinchilla. We assume r is species invariant and apply an approximate fit to our human OAE delays.0.7 1 1.5 2 3 3.6−40−20020R-componentLevel (dB SPL)  −40−20020Weighting (dB)0.7 1 1.5 2 3 3.6−20020  0.7 1.5 3.6−40−20020  1 2 30.7 1 1.5 2 3 3.6125102050Frequency (kHz)  RABC0.7 1 1.5 2 3 3.6−20020  0.7 3.6−40−20020  0.7 1 1.5 2 3 3.6125102050Frequency (kHz)  1 2 3R1.5ABCFig. 3  Young AdultDPOAE Level (dB SPL)R-componentLevel (dB SPL)DPOAE Level (dB SPL) R-componentLevel (dB SPL)|PR/Pref|2Frequency (kHz)Fig. 6  Term-Newborn GroupFig. 7  Young-Adult GroupFig. 10  Term-Newborn GroupACKNOWLEDGEMENTSThis research was supported by the National Institutes of Health R01 DC003552 (CA), DC003687 (CAS) and the House Research Institute.  Weighted DataLoess Fitting95% CIFig. 11  Young-Adult GroupFig. 12  Older-Adult GroupPick pickingEnergy weightingMean of EW and PPFig. 4  Older AdultFig. 8  Older-Adult Group−40−30−20−100102030  131030 NR (periods)NR (periods)NR (periods)NR (periods)NR (periods)NR (periods)NR (periods)Level (dB SPL)Frequency (kHz)0.7 1 1.5 2 3 3.6 0.7 1 1.5 2 3 3.6 NR (periods)81015205Frequency (kHz)0.7 1 1.5 2 3 3.6Center Frequency/fab0.7 1 1.5 2 321.6Delay NR (periods)Delay NR (periods)Weighted DataLoess Fitting95% CI  NR (periods)Frequency (kHz)0.7 1 52 3 6 8810152025512PrematureTerm newbornSix month oldTeenYoung adultMiddle ageOlder adultSubjects - 186 subjects: 15 premature (mean = 34 wks PCA) and 30 term newborns; 19 six-month-old infants, 26 teens (13-16 yrs), 43 young adults (18-30 yrs), 21 middle-aged (40 - 57 yrs) and 32 older adults (68-75 yrs).DPOAE (2f1-f2) - f1, f2 swept logarithmically at 8 s/oct for DPOAEs from 0.5 – 4 kHz, and 24 s/oct for DPOAEs from 4 – 8 kHz; 65 (L1) – 55 (L2) dB SPL; f2/f1 = 1.22.  Least-squares fit method used to estimate DPOAE level and phase from averages of 6 to 8 sweeps.Inverse FFT - MATLAB-based software was used to sepa-rate DPOAE distortion- and reflection-source components based on their respective phase-gradient delays. (DPOAE  and IFFT software developed by C. Talmadge, adapted by P. Luo; See Abdala and Dhar, 2012.) Loess - Simple models of linear and nonlinear least squares regression are fitted to localized subsets of the data and adjacent fits are joined to create the overall fit. Loess fits were conducted using two strategies: energy weighting and peak picking (Shera and Bergevin, 2012). ABCFig. 1. Reflection-component data from one young-adult sub-ject.  (A) phase versus frequency; (B) phase-gradient delay and (C) NR  -  delay in periods.delay = - dϕ(f)/df  NR(fCF) = fCF • τR(fCF) NR (periods)Delay (ms)Phase (cycles)Frequency (kHz)0.7 1.0 1.5 2.0 3.0 3.60-10-206020-20502052Final Parameters: Two-pass “cleaning” with 6 dB SNR; Pref window = 1 octave; loess window = 0.6 octave; final loess fit is the mean of energy-weighting and peak-picking fits.Fig. 2  Term Newborn20AB   SNR 6 dB  SNR 9   SNR 12Frequency (kHz)     Frequency (kHz) Energy weightingNo weightingDependence on energy weightingDependence on size of loess smoothing windowDependence on SNR Fig. 13. Energy-weighted loess lines from the young-adult group, fit to delay data using three different SNR criteria. Increasing criterion SNR did not impact fit.Fig. 14. Pref (estimate of local R-compo-nent level for weighting) calculated with four windows in the young-adult group.  Local versus more global window size did not alter the fit greatly though smaller windows produced smoother trend lines.Fig. 15. Loess fit calculated using four  window sizes in the young-adult group. Changing the loess window from local (0.2 octave) to more global (0.8 octave) had a strong effect on the trend line and its smoothness. Fig. 16. With ideal (i.e., adult) data and good SNR, a weighted fit may not have a strong impact; however, with noisier data from a premature newborn, the dif-ference is more apparent.ParametersLoess 0.2Loess 0.4Loess 0.8NR (periods)NR (periods)NR (periods)0.7 1 1.5 2 3 3.6 0.7 1 1.5 2 3 3.60.7 1 1.5 2 3 3.60.7 1 1.5 2 3 3.60.7 1 1.5 2 3 3.681015205810152058101520581015205NR (periods)81015205  Pref  0.4 octavePref  0.6 octavePref  0.8 octavePref   1 octaveDependence on Pref  window sizeFrequency (kHz)Frequency (kHz)Loess 0.6AdultPrematureCochlear delay and cochlear tuning are linked through filter theory, which holds that sharper tuning requires longer delays. Likewise, cochlear delays have been linked to re-flection source OAE delays via the theory of coherent re-flection (Zweig and Shera, 1995). [Reflection-source emis-sions denote those OAEs arising from backscattering of energy off of micromechanical irregularities along the co-chlea, i.e., stimulus-frequency and click-evoked OAEs, and the reflection component of the DPOAE.]  A relationship be-tween OAE delays and cochlear tuning has been demon-strated in several species (Shera et al., 2002; Oxenham and Shera, 2003; Shera et al., 2010). However, tuning esti-mates derived from OAE delays measured in humans are sharper than tuning recorded in other mammals, leading to some skepticism about the proposed relationships (Siegel et al., 2005; Ruggero and Temchin, 2005, 2007). Here we apply delays derived from the reflection compo-nent of the 2f1-f2 DPOAE to estimate tuning in humans using a species-invariant tuning ratio which defines the co-variation of cochlear tuning and emission delays (Shera et al., 2010).  Our objective was to explore non-invasive meth-ods for obtaining estimates of cochlear tuning and to gener-ate preliminary tuning estimates for age groups represent-ing seven decades of the human lifespan.(1) Consistent with past work (Shera and Bergevin, 2012), these results suggest that peaks in fine structure carry the most important information for estimating delay trends.(2) The loess fits based on energy weighting and peak pick-ing usually agree and have generally overlapping CIs. Slight differences are restricted to the ends of the test frequency range.(3) Consistent with theory (Shera and Guinan, 1999) and empirical observation (Kalluri and Shera, 2001), delays de-rived from the DPOAE reflection component are similar to SFOAE delays. Differences were likely due to methodologi-cal factors: a) The probe strength to the reflection site at 2f1-f2 is un-   controlled in the DPOAE paradigm.  b)  L1 suppresses the 2f1-f2 site in the DPOAE paradigm    thus impacting reflection.(4) The bend in the DPOAE NR delay function was centered around 1 kHz, marking the putative apical-basal transition and a deviation from approximate cochlear scaling. This bend frequency matches nicely with SFOAE delay data.(5) Our tuning estimates are similar to SFOAE-based esti-mates. Shera et al. (2010) reported mean QERB values  rang-ing from ~11 to 19 over a comparable frequency range; these are slightly larger values than those found here (~9 to 16). Tuning generally becomes sharper with increasing fre-quency, most notably in the young-adult group, which had an extended frequency range. (6) Maturation/Aging a) Infants generally had high QERB values, consistent     with sharp DPOAE suppression tuning curves (Abdala,    1998) and steep R-component phase slopes in newborns (Abdala and Dhar, 2012).This sharpened tuning is      likely due to middle-ear inefficiencies in the neonate,     which reduce primary levels driving the cochlea. b) Only adults show a decrease in tuning around 3 kHz.    This may reflect degradations in tuning with age; how-    ever, it effectively disappeared once frequency was ex-   tended in young adults, suggesting an end effect of some sort. c) The bend frequency marking the apical-basal transition   (and  deviations from cochlear scaling) does not vary with   age; this is consistent with studies of cochlear scaling     based on distortion emissions (Abdala and Dhar, 2012).CONCLUSIONSSFOAE delays in humans provide estimates of cochlear tuning (Shera et al., 2010). Our results suggest that the re-flection component of the DPOAE can provide comparable delay data for tuning estimates. Here, loess fits to either energy-weighted delay data or data restricted to peaks in fine structure captured the underlying delay trends, and pro-duced measures of human tuning that are similar to previous reports using reflection-source emissions.  0.7 1 1.5 2 3 3.6−20020DPOAE Level(dB SPL)  0.7 1 1.5−40−20020R-componentLevel (dB SPL)  0.7 1 1.5 2 3 3.6125102050Frequency (kHz)  2 3tABC3.6Delay NR (periods)*The young-adult data are shown over an extended fre-quency range through 8 kHz.The a|b frequency was derived from the bend in the human delay function. The resulting Q values ranged from 9 to ~16.  Infant groups showed high Q values over much of the frequency range. The adult data showed a slight decrease in tuning at the highest frequencies measured (near 3 kHz). Fig. 20.  To derive tuning estimates, we multiplied  tuning ratio by NR to obtain QERBYoung adult HFQERBCenter Frequency (kHz)0.7 1 52 3 6 81.58101518205   PrematureTerm newbornSix month oldTeenYoung adultMiddle ageOlder adult

Estimates of human cochlear tuning derived from DPOAE reflection-component delays

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Estimates of human cochlear tuning derived from DPOAE reflection-component delays

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