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 –Filter bandwidth 1/ sharpness of tuning

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

Downfalls 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 Humans –Psychophysical measures Masking procedures Pure tone detection in background noise Authors believe that human cochlear tuning has been underestimated

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

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

Determination of bandwidth Q ERB Measure of sharpness of tuning based on critical bandwidth Q ERB (CF) = CF/ERB(CF) Smaller bandwidth = higher Q ERB Frequency Level (dB SPL) Signal Masker Auditory filter 2 kHz

Results Genuine species differences or erroneous human data?

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

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 (N SFOAE ) –Negative of slope of emission-phase vs frequency

Theory N SFOAE = 2(N BM ) Normalized emitted wave delay is double the normalized BM transfer function delay N BM = delay of BM transfer function N SFOAE = emission group delay Can use measurable N SFOAE group delays to estimate N BM

Traveling wave delays

Theory II At low levels, smaller bandwidths (larger Q ERB ) correspond to steeper phase slopes (longer delays) BM tuning at low levels nearly identical to ANF tuning so: Q ERB N BM ==> Q ERB = kN BM Where k is a measure of filter shape

Application Use measurable SFOAE emissions to estimate N BM Use N BM to estimate Q ERB using known k values from other species

Results

If this is right, it suggests: 1)Human k is a factor of 3 larger than in animals 2)Human Q ERB is very different from cats and guinea pigs

If this is right, it suggests: 1)Previous measures underestimate human filter sharpness 2)Such sharp tuning may facilitate speech communication

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

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

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

Results

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