Transcript Interaural Phase Difference (degree)

Compartmental Model for
Binaural Coincidence Detector
Neurons
Bertrand Delgutte
Zachary Smith and Leonardo Cedolin, SHBT
Jonathan Simon, University of Maryland
Motivation
• Provide understanding of how neurons work, and
how their structure defines their informationprocessing capabilities.
• Traditional teaching formats such as lectures and
discussion of literature papers do not give sufficient
intuition.
Specific Goals
• Provide hands-on experience with modern
compartmental model of a neuron.
• Experiment with model parameters and learn their
role in neural signal processing.
Model System
• Binaural coincidence detector neurons in the auditory
brainstem.
Interaural time difference is a cue to
sound source azimuth
Binaural Coincidence Detector Neurons
High Frequencies
Low Frequencies
Axons from left ear
Axons from
right ear
Smith & Rubel, 1979
The Model
• Developed by Jonathan Simon at University of
Maryland
• Based on coincidence detector neurons in the chick
• Compartmental model: Neuron geometry is explicitly
represented
• Includes known membrane channels (HodgkinHuxley, synaptic, low-threshold K+, etc…)
• All model parameters easily manipulated with GUI
• Implemented in NEURON, a general, high-level
language for neural modeling
Building a compartmental model
C. Circuit model for small length of
passive cable
-> Also need active membrane
channels
Compartmental Model of
Coincidence Detector Neuron
Soma
Left Dendrite
Synaptic Inputs
from Left Ear
Right Dendrite
Hillock
Axon
Synaptic Inputs
from Right Ear
Dendritic filtering and attenuation
Space Constant
c 
a
2 iGm
• Transient response of linear cable to impulse of current at different distances
from the current source.
• Both latency and temporal spread increase with distance (lowpass filtering).
Peak amplitude decreases (attenuation).
Point vs. compartmental neuron models
Point neuron
3-compartment model
Gd
Gl
Gm Cm
Es
Gr
Gm
Es
Gl  Gr
V
Es
Gm  Gl  Gr
Gl
V
Gd
Cm
Es
Gr
Es
Gl  Gr  2Gl Gr Gd
Es
Gm  (Gl  Gr )(1  Gm Gd )  Gl Gr (2  Gm Gd ) Gd
• Synaptic potential depends only on sum Gl+Gr for point-neuron model, but
also depends on product GlGr for 3-compartment model.
• Point neuron does not distinguish between monaural and binaural
coincidences.
Better coincidence detection for 3compartment model
• Binaural:
Gl=Gr=Gb
• Monaural: Gl=0,
Gr=2Gb
• Fixed Parameters:
Es=100mV,
Gm=100, Gd=20
Extra slides
Binaural coincidence mechanism for
coding interaural time differences (ITD)
IPSI
EAR
ITD
COCHLEAR
FILTER
SOUND
COINCIDENCE
DETECTOR
CONTRA
EAR
COCHLEAR
FILTER
INTERNAL
DELAY
X
NEURAL
RESPONSE
User Interface
Result: ITD tuning improves as synaptic inputs
get farther from soma along dendrites
1
Distance
from Soma
10%
Normalized Discharge Rate
0.9
0.8
30%
0.7
90%
0.6
0.5
0.4
0.3
0.2
0.1
0
-180
-135
-90
-45
0
45
90
Interaural Phase Difference (degree)
135
180
Result: There is an optimal frequency for
every dendritic length
Discharge Rate (spikes/sec)
400
Frequency (Hz)
300
500
800
1250
300
200
100
0
-180
-90
0
90
Interaural Phase Difference (degree)
180
Student Feedback
Pros
•
•
•
•
•
The lab provides the basic understanding of a compartmental model
I am happy to work with a full-blown model and not a baby version
We had the opportunity to be creative and try different parameters
It was very user friendly
The simulations really drove home the reasons for using a
compartmental model in the first place
Cons
•
•
•
This lab was a little too complicated… I prefer something more
straightforward.
All we did was load the configuration file and press `Init & Run’.
I must admit that the lab was pretty "dry".
General
•
The labs provide the best available introduction to the field.
What next?
• Improve existing laboratory exercise:
– Make the lab less “cookbook”
– Make user interface less daunting
• Connect neuron model to model of signal
processing by normal and pathological ears
• Develop more challenging simulations for
advanced classes (e.g. requiring
programming in NEURON)
Interaural time difference is a cue to
sound source azimuth
Electrical circuit for small
segment of nerve fiber
Synapse position
Farunge
Basic circuit elements