Aditya P. Mathur

1
Aditya P. Mathur
CS Department Colloquium
March 26, 2007
Segment I Past work impact
Segment II Modeling the Auditory Pathway
Segment III future.cs_at_purdue a personal view
Segment IV QA
2
Research Impact

• Coverage principle and the saturation effect
  Horgan.Mathur96
• Microsoft quality gate criteria. Pioneered by
  Praerit Garg MS95
• Guidant test quality assessment for medical
  devices recommendation accepted yet to be
  implemented

• Software reliability estimation Chen.Mathur.Rego
  95 Krishnamurthy.Mathur 97
• Led to new approaches to software reliability
  modeling. Gokhale.Trivedi 98 Singpurwalla.Wilson
  99 Goševa-Popstojanova.Trivedi 01 Yacoub et
  al. 99 Cortellessa et al. 02 Mao.Deng 04

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Research firsts with No impact (so far!)

• Testing on SIMD, Vector, MIMD architectures
  joint with Choi, Galiano, Krauser, Rego. 88--92

• LSL A language for the specification of program
  auralization Boardman.Mathur 94, 94-04

• Feedback control of software test processes
  joint with Cangussu, DeCarlo, Miller. 00--06

4
Education Impact

• Introduction to Microprocessors 80, 85, 89
• Drove curricula in almost every engineering
  college in India (including all the IITs).
• Continues to be recommended mostly as a reference
  text in many Indian universities.
• Over 100,000 students benefited from this book.

• Foundations of Software Testing, Vol 1 07, Vol
  2 08
• First comprehensive (text) book to present
  software testing and reliability as an integrated
  discipline with algorithms for test generation,
  assessment, and enhancement. Is driving testing
  curricula in CS/ECE departments.

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Service Impact

• Educational Information Processing System BITS,
  Pilani 85
• Led a team of four faculty to design, develop,
  and deploy from scratch. In use even now(06)
  (code changed from Fortran IV to C!)

• Software Engineering Research Center (SERC)
  94-00
• Started by Conte/Demillo 86-87.
• Led SERC recovery from six industrial members to
  13 and from two university members to four. Over
  1.5 Million in research funds awarded to faculty.

• Purdue University Research Expertise (PURE)
  database 06
• Original idea Dean Vitter. My contribution
  Requirements analysis, design, testing, and
  management interaction with all 10 colleges.
• Over 85 of Purdue (WL) faculty in PURE.
  Expansion planned to other state universities
  enhancement of feature set with Luo Si

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Aditya P. Mathur
CS Department Colloquium
March 26, 2007
Segment I Past work impact
Segment II Modeling the Auditory Pathway
Segment III future.cs_at_purdue a personal view
Segment IV QA
7
Modeling the Auditory Pathway
Sponsor National Science Foundation
Principle Investigator Aditya Mathur
Graduate Student Alok Bakshi, Industrial
Engineering
Collaborators Nina Kraus Hugh Knowles
Professor Sumit Dhar Assistant Professor,
Department of Neurobiology and Physiology,
Northwestern Michael Heinz Assistant Professor,
Speech, Language, and Hearing Sciences and
Biomedical Engineering, Purdue
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Objective

• To construct and validate a model of the
  auditory pathway that enables us to understand
  the impact of defects and auditory plasticity
  along the pathway in children with learning
  disabilities.

9
Trail
Progress so far and the future
Existing modeling approaches versus our approach
BAEP and children with learning disabilities
What is Brainstem Auditory Evoked Potential
(BAEP)?

• What is auditory pathway?

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What is (ascending) auditory pathway?
Comparison across sounds
Medial geniculate body
Gateway for AC
Sensory integration (e.g. head movement)
Pitch discrimination (VCN)
Range,timing, intervals
Input for sound localization
Spatial map?, Spectral analysis
Onset neurons
Azimuth, integration from both ears ITD and ILD
computation
Transport frequency, intensity Information rate
encoding/temporal encoding
http//www.iurc.montp.inserm.fr/cric/audition/engl
ish/audiometry/ex_ptw/voies_potentiel.jpg
http//www.iurc.montp.inserm.fr/cric/audition/engl
ish/audiometry/ex_ptw/e_pea2_ok.gif
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What is Brainstem Auditory Evoked Potential
(BAEP)?
ABR 1.5-15ms Brainstem
Q What is the effect of learning disability on
ABR?
MLR 25-50ms Upper brainstem and/or Auditory
Cortex
ABR Auditory Brainstem Response
MLR Middle Latency Response
Source http//www.audiospeech.ubc.ca/haplab/aep.h
tm
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BAEP for normal and language impaired children
Stimulus Synthesized /da/
6.2ms
7.2ms
V lateral lemniscal input to inferior colliculus
Vn dendritic processing in the inferior
colliculus
Normal children
Language impaired children
Observation Duration of V-Vn found to be more
prolonged for children with learning problems
than for normal children. Notice also the
difference in the slope of V-Vn.
Source Wible, Nicol, Kraus Brain 2005.
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BAEP for normal and language impaired
children Onset and formant structure of speech
sounds in children
Stimulus Train of /da/
FFR Frequency Following Response
Normal children
Language impaired children
Observation Mean V-Vn slope was smaller for
children with language-based learning problems.
Source Wible, Nicol, Kraus Biological
Psychology, 2004.
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FFR for Musicians and Non-musicians
Stimulus /mi1/, /mi2/, /mi3/ F0 Stimulus
fundamental frequency
Observation Musicians showed more faithful
representation of the f0 contour than
non-musicians.
Source Wong, Skoe, Russo, Dees, Kraus Nature
Neuroscience, 2007.
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Importance of the BAEP

• Neural activity in the auditory pathway, measured
  via the BAEP, seems to be a strong indicator of
  learning disabilities in children.
• Auditory pathway is tuned by tonal experience.

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Why model the auditory pathway?

• BAEP is an external measurement (black box) of an
  internal activity.
• Direct observation of internal activity is almost
  impossible in humans.
• A validated model will allow direct observation
  of (simulated) internal activity and offer
  insights into the relationship between such
  activity and the BAEP.
• This might lead to better diagnosis.
• Several other advantages too.

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Research questions

• How can neuro-computational models be used to
  encode, and mimic, the auditory neural behavior
  exhibited by children with learning disabilities?
• How can such models be used to accurately predict
  the impact of treatments for learning impairments?

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Existing approaches

• Connectionist models
• Surface and deep dyslexia Hinton.Shallice91,
  Plaut.Shallice93
• Spatial firing patterns Nomoto79
• Phenomenological models P-models
• Sound localization Neti.Young.Schneider93
• Response to amplitude modulated tones
  Nelson.Carney04
• Cochlear model Kates93
• Speech recognition Lee.Kim.Wong.Park03
• Simulation models
• External ear to cochlear nucleus
  Guérin.Bès.Jeannès.03

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Our approach

• Simulation, system of systems, holistic,
  approach.
• Detailed, cellular.
• Explicit modeling of inherent anatomical and
  physiological parallelism.
• Functionality used primarily for validation of
  the simulation

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Our approach
Simulation
.
P-model
P-model
P-model
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Progress
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Bushy Cell (in Anteroventral Cochlear Nucleus)
Preserves timing information for the computation
of ITD.
AN spikes
Bushy Cell
Time
Bushy Cell spikes
Receives excitatory input from 1-20 AN fibers in
the same frequency range
Time
Latent period
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Bushy Cell Model

• Model Rothman93, Spirou05
• Has no dendrites and axon
• The soma is equipotential
• Receives 1-20 AN fibers with different
  characteristic frequency

Soma
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Hodgkin Huxley Model
m, n and h depend on V
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Aditya P. Mathur
CS Department Colloquium
March 26, 2007
Segment I Past work impact
Segment II Modeling the Auditory Pathway
Segment III future.cs_at_purdue a personal view
Segment IV QA
26
Vision as in the Strategic Plan 2003

• The faculty will be preeminent in creating and
  disseminating new knowledge on computing and
  communication. The department will prepare
  students to be leaders in computer science and
  its applications. Multidisciplinary activities
  that strengthen the impact of computation in
  other disciplines will play an essential role. ..

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Vision as in the Strategic Plan 2003

• The department will be known for
• Faculty who are recognized worldwide as leaders.
  They will set and implement the national agenda
  for discovery and education in computer science.
• A superior and diverse student body learning the
  values, vision, knowledge, and skills of computer
  science.
• Graduates who go on to be faculty at highly
  ranked departments, researchers at
  internationally recognized labs, and leaders and
  innovators in industry and government.
• Involvement and leadership in university
  institutes and centers that foster
  multidisciplinary research.
• Collaboration with public and private enterprises
  in Indiana, the nation, and the world.

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Goals

1. Offer a broader set of options to our
   undergraduate students.

2. Strengthen interdisciplinary research and
educational programs.
3. Improve upon the existing research environment
for faculty and students, in particular for
tenure-track assistant professors.
4. Meet our implicit obligations to the state and
the nation, in particular to our customers.
5. Maintain excellence where it already exists.
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Undergraduate Education

• Tackle the declining enrollment problem
• Revisit the undergraduate curriculum should we
  change the core? Should we offer alternate cores
  for different specializations?
• Create specializations such as SE,
  Visualization, Security.
• Offer scoping into the MS program.
• CPC sponsored undergraduate research projects.
  Some may lead to MS thesis.
• Consider formalizing advisory role for the CPC in
  undergraduate curriculum design.
• Strengthen the CS study abroad program.

Goal Offer a broader set of options to our
undergraduate students. Meet our implicit
obligations to our customers.
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Graduate Education

• Enrollment
• Admissions
• MS and PhD programs.
• Interdisciplinary programs

Goal Meet our implicit obligations to the state
and the nation.
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Faculty Hiring

• Look to the future of CS.
• Continue support for research in core areas but
  aim to establish collaborative groups that are
  radically different in their perspective and
  aspirations.
• Consider CS as a discipline essential to finding
  solutions to problems of key significance to
  humans cancer and other diseases, large scale
  information processing, finance, health care,
  etc.
• Aim at creating strengths in new and challenging
  areas while retaining current strength in core
  areas.

Goal Strengthen interdisciplinary research and
educational programs.
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Faculty Tenure

• Reduce the uncertainty for an Assistant
  Professor.
• Focus (primarily) on scholarship identify
  quantitative and qualitative indicators of
  scholarship. Consider quality as a
  multi-dimensional attribute.
• Identify and communicate ways of measuring
  impact/potential impact.
• Create a Tenure card that aids in (accurate)
  self assessment.
• Strengthen the third year review process.

Goal Improve upon the existing research
environment for faculty and students, in
particular for tenure-track assistant professors.
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Other programs/staff

• Outreach programs
• All staff
• Facilities
• Corporate Partners Program
• Development

Goal Maintain excellence where it exists.
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Aditya P. Mathur
CS Department Colloquium
March 26, 2007
Segment I Past work impact
Segment II Modeling the Auditory Pathway
Segment III future.cs_at_purdue a personal view
Segment IV QA
Thanks!
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Auditory Neuron Model
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Cochlear Nucleus

• Consist of 13 types of cells
• Single cell responses differ based on
• of excitatory/inhibitory inputs
• Input waveform pattern

Input tone
Onset response
Buildup response
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Octopus Cell
Octopus Cell
Receives excitatory input from 60-120 AN fibers
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Schematic of a typical Octopus Cell

• 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

http//www.ship.edu/cgboeree/neuron.gif
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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
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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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Fusiform Cell
AN discharge rate
Fusiform Cell
Time
Fusiform Cell discharge rate
Receives different inhibitory inputs from DCN
Time
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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 doesnt take into account the Calcium
  conductance
• Doesnt model the synaptic input

Electrical 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 doesnt model
  synapse and take direct current as the input
  instead
• Doesnt rule out the possibility of inhibitory
  inputs as the reason for pauser and buildup
  response

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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, 30578587,
  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,
  9615011514, 1994.
• Levy K.L. Kipke D.R. A computational model of
  the cochlear nucleus octopus cell. The Journal of
  the Acoustical Society of America, 102391402,
  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, 7025622583, 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, 109648670, 2001.

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References

• Drawing/image/animation from "Promenade around
  the cochlea" ltwww.cochlea.orggt 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

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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(lt 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
  doesnt reproduce all characteristics of globular
  bushy cell

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Progress
Cochlear Nucleus
49
Progress
Medial Superior Olive
Medial Nucleus of the Trapezoid Body
Lateral Superior Olive
COCHLEAR NUCLEUS
Pyramidal Cell
Stellate Cell
Inter-Neurons
Bushy Cell
Octopus Cell
Fusiform Cell
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Cochlear Nucleus
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Bushy Cell

• Some constants associated with Bushy cell

• Slow low threshold potassium conductance

Fast high threshold potassium conductance
Passive leakage conductance
Inhibitory synaptic conductance
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Bushy Cell

• The cell potential (V) is given by

Where
Reverse potential for corresponding ions
Membrane potential
Leakage potential
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Bushy Cell Model

• Factor to scale rate constants to body
  temperature

General expression for scaling rate constants to
temperature T
The three conductance mentioned earlier are given
as
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Bushy Cell Model

• Here

themselves depend on voltage of soma V
Here
denotes the arrival time for spike and synaptic
Conductance reaches its peak value of
at time
Variation is given as
Here
and
are given as
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Bushy Cell Model
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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 N1 and A 9.1, while the output
  obtained by Rothman et. al. is shown in D for
  same parameter.

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Next Step

• Implement the ILD circuit and find out the
  correlation between neural output and sound
  source (azimuth angle)

LSO
LSO
Cochlear Nucleus
Cochlear Nucleus
SBC
GBC
MNTB
MNTB
GBC
SBC
Cochlea
Cochlea
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Next Step

• Implement the ITD circuit and find out the
  correlation between neural output and sound
  source (azimuth angle)

MSO
MSO
LNTB
LNTB
Cochlear Nucleus
Cochlear Nucleus
SBC
GBC
MNTB
MNTB
GBC
SBC
Cochlea
Cochlea
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Next Step

• Implement the dorsal cochlear nucleus neurons and
  find out the correlation between vertical angle
  and neural output in DCN region