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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
QERB
• Measure of “sharpness” of tuning based on critical bandwidth
• QERB(CF) = CF/ERB(CF)
Smaller bandwidth = higher QERB
Frequency
Le
vel (
dB
SP
L)
SignalMasker
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 (NSFOAE)– Negative of slope of emission-phase vs frequency
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
Traveling wave delays
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
Application
• Use measurable SFOAE emissions to estimate NBM
• Use NBM to estimate QERB 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 QERB 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