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