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Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements

Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements. Christopher A. Shera, John J. Guinan, Jr., and Andrew J. Oxenham. Background. Key characteristic of hearing: frequency tuning of cochlear filters Sensory cells respond to a preferred range of energy

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Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements

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  1. Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements Christopher A. Shera, John J. Guinan, Jr., and Andrew J. Oxenham

  2. Background • Key characteristic of hearing: frequency tuning of cochlear filters • Sensory cells respond to a preferred range of energy • Filter bandwidth  1/ sharpness of tuning

  3. Background Assessments of cochlear tuning • Non-human mammals • ANF recordings in live anesthetized animals • Humans • Psychophysical measures • Masking procedures • Pure tone detection in background noise

  4. Downfalls • Humans • Psychophysical measures • Masking procedures • Pure tone detection in background noise • Assumptions underlying pure tone detection method are uncertain • Physcophysical detection tasks depend on filter characteristics as well as neural processing • No way to validate behavioral measures in humans • Authors believe that human cochlear tuning has been underestimated

  5. Aims • Compare current measures of human cochlear tuning with animal measures • Develop a noninvasive measure of cochlear tuning based on otoacoustic emissions • Test correspondence between physiological and behavioral measures of frequency selectivity

  6. Aims • Compare current measures of human cochlear tuning with animal measures • Develop a noninvasive measure of cochlear tuning based on otoacoustic emissions • Test correspondence between physiological and behavioral measures of frequency selectivity

  7. Masker Signal Auditory filter Level (dB SPL) Frequency 2 kHz Determination of bandwidth QERB • Measure of “sharpness” of tuning based on critical bandwidth • QERB(CF) = CF/ERB(CF) Smaller bandwidth = higher QERB

  8. Results Genuine species differences or erroneous human data?

  9. Aims • Compare current measures of human cochlear tuning with animal measures • Develop a noninvasive measure of cochlear tuning based on otoacoustic emissions • Test correspondence between physiological and behavioral measures of frequency selectivity

  10. Experiment II • Subjects • Guinea pigs (n=9) • Cats (n=7) • Humans (n=9) • Measure stimulus-frequency otoacoustic emissions (SFOAEs) • Cochlear traveling waves scattered by the mechanical properties of the cochlea • Recordable sounds emitted from the ear • Evoked by a pure tone • Calculate SFOAE group delays (NSFOAE) • Negative of slope of emission-phase vs frequency

  11. Theory • NSFOAE = 2(NBM) Normalized emitted wave delay is double the normalized BM transfer function delay • NBM= delay of BM transfer function • NSFOAE = emission group delay Can use measurable NSFOAE group delays to estimate NBM

  12. Traveling wave delays

  13. Theory II • At low levels, smaller bandwidths (larger QERB) correspond to steeper phase slopes (longer delays) • BM tuning at low levels nearly identical to ANF tuning so: QERB  NBM ==> QERB = kNBM Where k is a measure of filter shape

  14. Application • Use measurable SFOAE emissions to estimate NBM • Use NBM to estimate QERB using known k values from other species

  15. Results

  16. If this is right, it suggests: Human k is a factor of 3 larger than in animals Human QERB is very different from cats and guinea pigs

  17. If this is right, it suggests: Previous measures underestimate human filter “sharpness” Such sharp tuning may facilitate speech communication

  18. Aims • Compare current measures of human cochlear tuning with animal measures • Develop a noninvasive measure of cochlear tuning based on otoacoustic emissions • Test correspondence between physiological and behavioral measures of frequency selectivity

  19. Experiment III • 8 Normal-hearing humans • Detection of a sinusoidal signal • 10dB above threshold in quiet • Frequencies: 1,2,4,6,8 kHz • 5ms after offset of burst of masker • Frequencies: 2 .25f wide spectral bands of Gaussian noise placed 0, 0.1, 0.2, 0.3, 0.4 f below signal frequency • gated by 5ms raised-cosine ramps • Measured thresholds using 3-alternative forced-choice procedure • Use mean data to derive cochlear filter magnitude responses

  20. Reasoning behind methodology • Use low, near threshold tuning curves • Avoid compression & non-linear affects • Noise masker extends spectrally above and below signal frequency • avoid off-frequency listening • avoid confusion between masker & signal • Non-simultaneous masking • Minimize suppressive interactions between masker and signal • Constant signal level (instead of masker level) • paradigm used in neural threshold measurements

  21. Results

  22. Conclusions • Human cochlear filters are substantially sharper than commonly believed • Contrary to prior beliefs • Human Q filters are not constant above 500Hz • Human tuning may be sharper than cat • Human and cat tuning may vary similarly with CF • Supports the assumption that k is invariant across species • Suggests revised understanding of the cochlear frequency-position map

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