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Modeling the Auditory Pathway
Research Advisor:
Aditya Mathur
School of Industrial Engineering
Department of Computer Science
Purdue University
Graduate Student:
Alok Bakshi
Humans Simulator ProjectDecember 3, 2007
Sponsor: National Science Foundation
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Objective
To construct and validate a model of the
auditory pathway to understand the effect of various treatments on children with auditory disorders.
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Background and Problem
Children with some forms of auditory disorders are unable to discriminate rapid acoustic changes in speech.
It has been observed that “auditory training” improves the ability
to discriminate and identify an unfamiliar sound. Computational model desired to reproduce this observation.
A validated model would assist in assessing the impact of disorders in the auditory pathway on brainstem potential. This would be useful for diagnosis. [This appears related to fault diagnosis and tolerance in software systems. It might have an impact on the design of redundant software systems.]
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Methodology
Study physiology of the auditory system. Simulate the auditory pathway by constructing new models,
or using existing models, of individual components along the auditory pathway.
Validate the model against experimental results pertaining to the auditory system.
Mimic experimental results of auditory processing tasks in children with disabilities and gain insight into the causes of malfunction.
Experiment with the validated model to assess the effects of treatments on children with auditory/learning disabilities.
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Characteristics of our approach
Systems, holistic, approach. Detailed versus aggregate models. Explicit modeling of inherent anatomical and
physiological parallelism.
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Progress
Synaptic model is implemented for connection between two neurons
Following (existing) models incorporated for the simulation of the Auditory pathway
Phenomenological model for the response of Auditory nerve fibers
Computational model of the Cochlear Nucleus Octopus Cell
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Brainstem Evoked Auditory Potential
http://www.iurc.montp.inserm.fr/cric/audition/english/audiometry/ex_ptw/e_pea2_ok.gif
http://www.iurc.montp.inserm.fr/cric/audition/english/audiometry/ex_ptw/voies_potentiel.jpg
Normal children
Language impaired children
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Auditory Pathway Modeling
Auditory Nerve fiber model by Zhang et. al.
•Octopus Cell model by Levy et. al.
•Models of other cells being implemented
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Auditory Neuron Model
(Zhang et al., 2001)(Heinz et al., 2001)(Bruce et al., 2003)
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Cochlear Nucleus
Consists of (at least) 13 types of cells Single cell responses differ based on
# of excitatory/inhibitory inputs Input waveform pattern
Onset response
Buildup response
Input tone
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Octopus Cell
Octopus Cell
Receives excitatory input from 60-120 AN
fibers
AN discharge
rate
Time
Octopus Cell
discharge
rate
TimeLatent period
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Schematic of a typical Octopus Cell
http://www.ship.edu/~cgboeree/neuron.gif
Representative Cell• Has four dendrites
• Receives 60 AN fibers with 1.4 - 4 kHz CF
•Majority of input from high SA fibers, medium SA fibers denoted
by superscript ‘m’
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Octopus Cell Model Simplifications
Four dendrites replaced by a single cylinder Active axon lumped into soma Synaptic transmission delay taken as constant 0.5 ms Compartmental model employed with
15 equal length dendritic compartments 2 equal length somatic compartments
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Octopus Cell Model
2 somatic compartments and 15 dendritic compartments modeled by the same circuit with different parameters
Different number of dendritic compartments depending on number of synapses with AN fibers
Soma Dendrite
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Octopus Cell - Output
The output of the model implemented by Levy et. al. is compared against our model on the right side of the figure for a tone given at CF in figure A
Same comparison is made in figure B but with a tone of different intensity
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Bushy Cell
Bushy Cell
Receives excitatory input from 1-20 AN
fibers
AN spikes
Time
Bushy Cell spikes
TimeLatent period
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Bushy Cell Model
Representative Cell• Has no dendrites and axon
• The soma is equipotential
• Receives 1-20 AN fibers with different characteristic frequency
•Inhibitory inputs ignored in the model
Soma
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Bushy Cell Model Characteristics
As the number and conductance of inputs is varied, the
full range of response seen in VCN Bushy cell are
reproduced
For inputs with low frequency(< 1 kHz), the model
shows stronger phase locking than AN fibers, thus
preserving the precise temporal information about the
acoustic stimuli
The model simulates the spherical bushy cell, but
doesn’t reproduce all characteristics of globular bushy
cell
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Bushy Cell Model - Output
Response of Bushy cell for different number of input AN fibers (N), and synaptic conductance (A)
Fig. A shows the response of our implemented model for N=1 and A= 9.1, while the output obtained by Rothman et. al. is shown in D for same parameter.
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Bushy Cell Model - Output
Similarly for N=5 and A=9.1, our implemented model’s response is shown in B, while response of model by Rothman et. al. is shown in E
Finally, the fig. C shows response of our model for N=1, A=18.2 and the corresponding response of model by Rothman et. al. is shown in fig. F
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Fusiform Cell
Fusiform Cell
Receives different inhibitory inputs from
DCN
AN discharge
rate
Time
Fusiform Cell
discharge
rate
TimeLatent period
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Fusiform Cell Model Exhibit buildup and
pauser response and nonlinear voltage/current relationship
The model simulates the soma of fusiform cell with three K+ and two Na+ voltage dependent ion channels
The model doesn’t take into account the Calcium conductance
Doesn’t model the synaptic inputElectrical model of fusiform
cell
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Fusiform Cell Model Characteristics
Predicts the electrophysiological properties of the fusiform cell by using basic Hodgkin-Huxley equations
Simulates the pauser and buildup response by virtue of intrinsic membrane properties
Synaptic organization of cells in DCN is not understood presently, so this model doesn’t model synapse and take direct current as the input instead
Doesn’t rule out the possibility of inhibitory inputs as the reason for pauser and buildup response
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Next Steps Modify the models if they ignore few inputs for the sake
of simplification, to account for such inputs. Determine the response of the cochlear nucleus as a
whole with different input waveforms. Add models of additional stages (Superior Olive, Lateral
Lemniscus, and Inferior Colliculus) Validate a partial model of the auditory pathway using
sound localization.
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References Hiroyuki M.; Jay T.R.; John A.W. Comparison of algorithms for the
simulation of action potentials with stochastic sodium channels. Annals of Biomedical Engineering, 30:578–587, 2002.
Kim D.O.; Ghoshal S.; Khant S.L.; Parham K. A computational model with ionic conductances for the fusiform cell of the dorsal cochlear nucleus. The Journal of the Acoustical Society of America, 96:1501–1514, 1994.
Levy K.L.; Kipke D.R. A computational model of the cochlear nucleus octopus cell. The Journal of the Acoustical Society of America, 102:391–402, 1997.
Rothman J.S.; Young E.D.; Manis P.B. Convergence of auditory nerve fibers onto bushy cells in the ventral cochlear nucleus: Implications of a computational model. The Journal of Neurophysiology, 70:2562–2583, 1993.
Zhang X.;Heinz M.G.;Bruce I.C.; Carney L.H. A phenomenological model for the responses of auditory-nerve fibers: 1. nonlinear tuning with compression and suppression. The Journal of the Acoustical Society of America, 109:648–670, 2001.
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References
• Drawing/image/animation from "Promenade around the cochlea" <www.cochlea.org> EDU website by R. Pujol et al., INSERM and University Montpellier
• Gunter E. and Raymond R. , The central Auditory System’ 1997
• Kraus N. et. al, 1996 Auditory Neurophysiologic Responses and Discrimination Deficits in Children with Learning Problems. Science Vol. 273. no. 5277, pp. 971 – 973
• Purves et al, Neuroscience 3rd edition• P. O. James, An introduction to physiology of hearing 2nd
edition• Tremblay K., 1997 Central auditory system plasticity:
generalization to novel stimuli following listening training. J Acoust Soc Am. 102(6):3762-73