Towards understanding
information transmission
in the auditory periphery –
A modeling approach
Stefan Stenfelt
A hearing impairment is primarily determined
and judged by the audiogram. Additional test
(discrimination etc) helps with the diagnosis.
However, hearing aid fitting is largely based
solely on the audiogram. This means that
patients with identical auditory thresholds but
different origins of the impairment receives
the same fitting of the hearing aid, which is
most likely suboptimal.
Hearing level (dB HL)
Background
0
20
40
60
80
125 250 500 1k 2k 4k
Frequency (Hz)
8k
Linköping University
2008-09-24
The hearing function
Sid 2
Linköpings universitet
Hearing impairment
PERCEPTION / COMPREHENSION
Bottom-up
processing
A hearing impairment affects the bottom-up
information transmission. This information
degradation can in part be compensated by topdown processes. However, even if compensated
by amplification (hearing aid), almost all hearing
impairments result in an effective information
degradation.
Top-down
processing
To understand how a hearing loss affects the
information transmission, we need first to
understand the processes involved in normal
hearing.
SOUND
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Sid 3
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The normal peripheral hearing function
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Linköpings universitet
The outer ear
GOE(f,R)
Sound
Neural pulses
Sound
pressure
Outer
ear
Sid 5
Vibration
The subjective specific filtering of the
outer ear provides space perception of
the auditory scene (individual HRTFs).
Signal oriented
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Outer ear
scalar
scalar
Anatomical
Linköpings universitet
Middle
ear
Inner
ear
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Sid 6
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array
The inner ear
GIE(f,A(f),S1)
scalar
scalar
Middle ear
Inner ear
scalar
The middle ear
Stapes
Basilar membrane
GME(f)
Vibration
Round
window
Sound
pressure/
vibration
Fluid at rest
The sound transmission through the middle ear can
be approximated by a second order filter (band pass)
Tectorial membrane
Hensen cells
C
OH
C
IH
Basilar membrane
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Sid 7
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Modeling approaches of the inner ear
Sid 8
Linköpings universitet
Simplified coupled-oscillator model
Tectorial membrane
Tectorial membrane
C
IH
¾ Coupled resonator systems
Hensen cells
Steriocilia
C
OH
¾ Physical (mechanical) models
¾ Finite Element models
Reticular lamina
Outer
hair cells
Dieters’
cells
Basilar membrane
¾ Computational models
Equation
∑ (G
N
¾ Input/output models
i
j =1
¾ Non-linear multiple filter models
j
+ miδ ij
Basilar membrane
2
) ddtx
i
2
+ hi
dxi
dx ⎞
⎛ dx dx
+ U i ( yi ) + si ⎜ 2 i − i −1 − i +1 ⎟ + ki x = −Gi as (t )
dt
dt
dt ⎠
⎝ dt
¾ Black-box models
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Sid 9
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Finite-element model of organ of Corti
Structure motion
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Linköpings universitet
Nonlinear multiple filter model
Fluid motion
Filter structure
nth order BP
nth order LP
Linear path
G
Stapes
velocity
BM
velocity
nth order BP
Nonlinear block
nth order BP
nth order LP
Nonlinear path
e.g. Lopez-Poveda, Meddis JASA 2001:110;3107-17
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Sid 11
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Sid 12
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Black-box (data driven) model
Interpretation
The general model
Sound source
Auditory processing
Model structure ?
-NL ARMA
-State-space
-etc
Input
EC sound pressure
Stapes velocity
Auditory
signal
processing,
coding and
decoding
Output
Sound
pressure
information
Neural spike pattern
BM velocity
Perception
Neural
information
High-order control
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Sid 13
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Auditory
signal
processing,
coding and
decoding
Auditory processing model
- a physical based approach
Sid 14
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Parts of the inner ear: the basilar
membrane – a spectrum analyzer
GOE(f,R)
Inner ear
GME(f)
Brainstem
GIE(f,A(f),S1)
array
Middle ear
array
Outer ear
Basilar membrane
Non-linear
Non-linear
scalar
Linear
scalar
scalar
Stapes
Linear
Round
window
Fluid at rest
GBS(I(n),S2)
Level
Sound
pressure
Simplifications:
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Sid 15
Auditory filter
Sound
pressure/
vibration
Vibration
Neural
impulses
Neural
impulses
Passive basilar membrane
Traveling wave filter
No binaural interaction
No auditory reflex
No general efferent control
Frequency
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Linköpings universitet
BM displacement
Parts of the inner ear: the outer hair cells
– an active non-linear amplifier
Gain function
Compression
Linear
Linköpings universitet
Parts of the inner ear: the inner hair cells
– a rectifier
Synapse output (spikes/sec)
60 dB
Linear
Sid 16
Stimulus
Compression
0 dB
Sound pressure level
Sound pressure level
IHC
IHC filter
BM vibration
IHC rectifier
OHC
Modeled by a
positive feedback
loop
BM vibration
Feedback filter OHC nonlinearity
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Sid 17
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Sid 18
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Inner ear
Different impairments
array
scalar
Conceptual model of the inner ear
¾ Conductive (transmission to the cochlea)
GIE(f,A(f),S1)
¾ Sensorineural (within the cochlea)
Passive basilar membrane
IHC
IHC filter
Traveling wave filter
¾ Outer hair cell problem
IHC rectifier
¾ Inner hair cell problem
BM vibration
¾ Endocochlear potentials
¾ Retrocochlear (auditory nerve & brainstem)
Cascade of
sequentially
tuned LP filters
¾ Central (brain)
Feedback filter
OHC nonlinearity
OHC
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Sid 19
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Cochlear pathology according to
Schuknecht and Gacek (presbycusis)
Sid 20
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Stria vascularis – the battery of the inner ear
Schuknecht and Gacek devided inner ear hearing losses as belonging
to one of the four following based on examination of temporal bones.
¾ Sensory (hair cells)
¾ Neural (neurons attaching to the hair cells)
¾ Strial (pathological stria vascularis)
¾ Cochlear conductive (change of mechanical parameters of
basilar membrane?)
Ann Otol Rhinol Laryngol 1993:102(1pt2);1-16
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Sid 21
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Linköpings universitet
The modeling approach
array
scalar
The model incorporating endocochlear
Inner ear
potentials
Sid 22
Segments of the BM/organ of Corti
GIE(f,A(f),S1)
Passive basilar membrane
IHC
IHC filter
Traveling wave filter
IHC rectifier
BM vibration
Cascade of
sequentially
tuned LP filters
Endocochlear
Potential
Feedback filter
OHC nonlinearity
Auditory nerve pattern
OHC
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Sid 23
Linköpings universitet
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Sid 24
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What happens with the different types of
lesions in terms of signal transmission
Inner hair cells
No output signal –
Dead regions?
¾ IHC
¾ OHC
Tectorial membrane
¾ Endocochlear potentials
Hensen cells
C
OH
C
IH
Basilar membrane
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Sid 25
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Inner hair cell lesion
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Outer hair cells
No feedback –
no gain control
Tectorial membrane
Hensen cells
C
OH
C
IH
Basilar membrane
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Sid 27
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Outer hair cell lesion
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Endocochlear potentials - IHC
Lower potentials result in worse
transduction (gating) and worse
sensitivity for neural activation (less
dynamic range)
Frequency specificity
Stria
vascularis
Amplitude dynamics
Gating
- 60 mV
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Sid 29
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Sid 30
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Endocochlear potentials - OHC
How can the different cochlear lesions be
estimated within the patient?
Output
Sound
pressure
Neural activity
The output depends of the
driving voltage
(endocochlear potential)
Input
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Sid 31
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Electrophysiological measurements
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Distortion-product oto-acoustic emissions
Cochlear microphonic
Compound action potential
Primarily generated by IHC
Primarily generated by OHC
From Neely et al JASA 2003, 114:1499
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Sid 33
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Estimation of endocochlear potentials
Sid 34
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DPOAE-ABR thresholds
From Mills, E&H 2006
Cohlear
microphonics
measurement
Saturation
lin
Pre
c
DPOAE threshold
Acoustic/OHC
Strial/EP
Normal
Neural/IHC
Slope
ABR threshold
Low-frequency stimulation
(200-300 Hz)
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Sid 35
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Sid 36
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