1

Segment I Past work: Highlights

Segment II Modeling the Auditory Pathway

Segment III future.cs@purdue: a personal view

Segment IV Q&A

Aditya P. MathurResearch, Education, Service, and Vision

CS Department Colloquium

March 26, 2007

2

Research: Empirical Studies

Saturation effect [Horgan.Mathur96]

FUNCTIONAL, DECISION, DATAFLOWAND MUTATION TESTING PROVIDETEST ADEQUACY CRITERIA.

Reliability

Testing EffortTrue reliability (R)Estimated reliability (R’)Saturation region

Mutation

Dataflow

Decision

Functional

RmRdfRdRf

R’f R’d R’df R’m

tfs tfe tds tde tdfs tdfe tms tfe

3

Research: Empirical Studies and Reliability

Saturation effect [Horgan.Mathur96]

– Microsoft quality gate criteria. Pioneered by Praerit Garg [MS’95]

– 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]

4

Research: High Performance Testing

Testing on SIMD, Vector, MIMD architectures [joint with Choi,

Galiano, Krauser, Rego. 88--92]

5

Research: Feedback Control

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

6

Education

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.

7

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--HP1000-- to C (PC)!)

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]

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.

8

Segment I Past work: impact

Segment II Modeling the Auditory Pathway

Segment III future.cs@purdue: a personal view

Segment IV Q&A

Aditya P. MathurCS Department Colloquium

March 26, 2007

9

Modeling the Auditory Pathway

Principle Investigator

Aditya Mathur

Graduate Student

Alok Bakshi, Industrial Engineering

Sponsor: National Science Foundation

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

10

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.

11

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

What is Brainstem Auditory Evoked Potential (BAEP)?

BAEP and children with learning disabilities

Existing modeling approaches versus our approach

Progress so far and the future

What is auditory pathway?

Trail

12

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

What is (ascending) auditory pathway?

Medial geniculate body

42,000

8,800

392,000

100,000,000

570,000

Pitch discrimination (VCN)

Transport frequency, intensityInformation; rate encoding/temporal encoding

Azimuth, integration from both ears;ITD and ILD computation

Range,timing, intervals

Sensory integration(e.g. head movement)

Comparison across sounds

Input for sound localization

Onset neurons

Gateway for AC

Spatial map?, Spectral analysis

13

What is Brainstem Auditory Evoked Potential (BAEP)?

ABR [1.5-15ms]: Brainstem

MLR [25-50ms]: Upper brainstem and/or Auditory Cortex

ABR: Auditory Brainstem ResponseMLR: Middle Latency Response

Source: http://www.audiospeech.ubc.ca/haplab/aep.htm

Q: What is the effect of learning disability on ABR?

Slow AC response

14

BAEP for normal and language impaired children

Normal children

Language impaired children

Source: Wible, Nicol, Kraus; Brain 2005.

6.2ms 7.2ms

V: lateral lemniscal input to inferior colliculus

Vn: dendritic processing in the inferior colliculus

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.

Stimulus: Synthesized /da/

15

BAEP for normal and language impaired children

Onset and formant structure of speech sounds in children

Normal children

Language impaired children

Source: Wible, Nicol, Kraus; Biological Psychology, 2004.

Stimulus: Train of /da/

FFR

FFR: Frequency Following Response

Observation: Mean V-Vn slope was smaller for children with language-based learning problems.

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FFR for Musicians and Non-musicians

Source: Wong, Skoe, Russo, Dees, Kraus; Nature Neuroscience, 2007.

Stimulus: /mi1/, /mi2/, /mi3/ [Mandarin]F0: Stimulus fundamental frequency

Observation: Musicians showed more faithful representation of the F0 contour than non-musicians.

17

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.

19

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.Shallice’91, Plaut.Shallice’93

– Spatial firing patterns: Nomoto’79

• Phenomenological models [P-models]:

– Sound localization: Neti.Young.Schneider’93

– Response to amplitude modulated tones: Nelson.Carney’04

– Cochlear model: Kates’93

– Speech recognition: Lee.Kim.Wong.Park’03

• Simulation models:

– External ear to cochlear nucleus: Guérin.Bès.Jeannès.’03

21

Our approach

P-model P-model P-model…….

Equations

Anatomy

Assumptions

Simulation

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Progress

Medial Superior Olive

Lateral Superior Olive

Medial Nucleus of the

Trapezoid Body

INFERIOR COLLICULUS Not Implemented

Not Implemented

SUPERIOR OLIVARY COMPLEX

COCHLEAR NUCLEUS

Pyramidal Cell

Stellate Cell

Inter-Neurons

Bushy Cell

Octopus Cell

Fusiform Cell

Not Implemented

Implemented

AN Fibres [Zhang et al.] HRTF [Lookup table/person]

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Bushy Cell (in Anteroventral Cochlear Nucleus)

Bushy Cell

Receives excitatory input from 1-20 AN fibers in the same frequency range

AN spikes

Time

Bushy Cell spikes

TimeLatent period

Preserves timing information for the computation of ITD.

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Bushy Cell Model [Rothman ‘93]

Slow low threshold potassium conductance

Some constants associated with Bushy cell:

Fast high threshold potassium conductance

Passive leakage conductance

Inhibitory synaptic conductance

25

Bushy Cell Model

• The cell potential (V) is given by:

Where

Reverse potentials for corresponding ions

Leakage conductance

Membrane capacitance

26

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:

27

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

29

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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Next Step

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

Cochlea

Cochlear Nucleus

SBC GBC MNTB MNTB

LSO

Cochlea

Cochlear Nucleus

GBC SBC

LSO

Zhang et al.

Rothman et al.

Spirou et al.

Constant delay

H&H

Carney et al.

31

Next Step• Implement the ITD circuit and find out the correlation between

neural output and sound source (azimuth angle)

Cochlea

Cochlear Nucleus

SBC GBC MNTB MNTB

MSO

Cochlea

Cochlear Nucleus

GBC SBC

MSO

LNTBLNTB

32

Next Step

• Implement the dorsal cochlear nucleus neurons and

find out the correlation between vertical angle and

neural output in DCN region

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Model Validation

• Interconnected P-models

• Functional– Sound localization; in collaboration with Professor Sumit Dhar,

Northwestern

34

K+ ion channel

http://personal.tmlp.com/Jimr57/textbook/chapter3/images/pro5.gif

Outside

Iext

IK INa IL

gK gNa gL

VK VNa VL

C

Inside

( At potential V ) 4ngg KK =

hmgg NaNa3=

( ) ( ) ( ) ( )tIVVgVVgVVgdt

dVC extLLNaNaKK +−+−+−=

m, n and h depend on V

Hodgkin Huxley Model

35

Segment I Past work: impact

Segment II Modeling the Auditory Pathway

Segment III future.cs@purdue: a personal view

Segment IV Q&A

Aditya P. MathurCS Department Colloquium

March 26, 2007

36

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. …..

37

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.

38

Goals

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.

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

39

Segment I Past work: impact

Segment II Modeling the Auditory Pathway

Segment III future.cs@purdue: a personal view

Segment IV Q&A

Aditya P. MathurCS Department Colloquium

March 26, 2007

Thanks!

40

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.

41

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.

42

Other programs/staff

• Outreach programs

• All staff

• Facilities

• Corporate Partners Program

• Development

Goal: Maintain excellence where it exists.