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– 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