Program for the Degree of Doctor of Philosophy in

Program for the Degree of

Doctor of Philosophy

in

Multidisciplinary Brain Research

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Introduction

Understanding how the brain works is most probably the greatest unsolved scientific

puzzle of the 21st century. The key issues relate to the ways in which we organize

information provided by the senses into a global picture, how we function successfully in

this world, how we learn and store information, the mechanisms that create and regulate

our feelings and desires, and how we are able to understand and use language. A great

deal is known about these subjects, but very little about the brain mechanisms involved.

Clearly an understanding of these mechanisms can only be acquired through research

associating a broad range of fields including physiology, pharmacology, psychology,

linguistics, mathematics, theoretical physics and computer science. Multidisciplinary

research centers and teaching programs in brain sciences have been set up in Israel and

throughout the world for just this purpose.

The aim of these programs is to train the next generation of researchers in brain sciences

to carry out multi-disciplinary research.

The Gonda Center for Multidisciplinary Brain Research at Bar-Ilan University offers

program of studies toward a doctoral degree in brain sciences. The program is geared for

a select group of outstanding students, who receive a basic education in all the areas

connected with brain research and then carry out research work culminating in a Ph.D.

degree. Varied options allow the students to specialize in different areas. The program

encourages multidisciplinary discussions and exchanges between the students and the

teachers. A small number of candidates with B.Sc. and M.Sc. degrees are accepted to the

program annually. Students receive scholarships, enabling them to devote themselves

fulltime to their studies and research.

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Structure of the Study Program:

There are six single-semester core courses in the study program that are compulsory for

all students, and a range of optional courses. In addition, there are a number of multi-

disciplinary activities in which all the students must participate. These activities include:

a weekly seminar, intensive study days, small research projects, and rotations in

laboratories. There are a number of advanced optional courses in the program that enable

the student to specialize in one of the three sub-fields described below.

1. Computational Neuroscience

2. Neurobiology and Behavior

3. Language and Cognition

In addition to the core courses and the shared activities, each student takes 8 credits in

advanced courses

The six core courses are:

1. Neurophysiology

2. The neurochemical bases of normal and pathological brain processes

3. Brain and language

4. Normal and pathological cognitive processes

5. Theory of neural networks and machine learning

6. Signal and Data Analysis

A detailed syllabus for each course can be found in Appendix A.

The program is designed in such a way that a student arriving with the appropriate

background can complete the core courses in the first and second semesters of the first

year and can submit a doctoral proposal at the end of the first semester of the second

year. A student without the appropriate background will complete the background study

requirements by taking existing university courses, designated new courses and guided

reading during the first semester of the first year. This student can complete the six core

courses during the second semester of the first year and the first semester of the second

year. Such a student will submit a doctoral program at the end of Semester B of the

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second year of his/her studies. Successful candidates to the program are awarded a

doctoral scholarship for a period not exceeding four years. The doctoral scholarship is re-

evaluated at the beginning of each year to assess progress made in research in the same

year. Doctoral research proposals with advisors from different disciplines are encouraged.

Core Courses

1. Neurophysiology

Single-semester course, 4 hours

The course deals with current topics in research on the physiology of the brain. The

course combines frontal lectures with reading of articles and reporting on them by the

students. In some of the classes two teachers participate and present different views on

the subject of study (for example, incompatibility between psychophysics of vision and

neurophysiology).

2. The neurochemical basis of normal and pathological brain processes


The course deals with neurochemistry and neuropharmacology of brain processes,

regulation of motivation and emotion, and pathological processes. The course combines

frontal lectures with reading of articles and reporting on them by the students.

In some of the classes two teachers participate and present different views on the subject

of study (for example, the role of dopamine in regulating activity of the basal ganglia).



The course is designed to provide general knowledge on key topics in brain and language

research in linguistic and neuropsychology The course combines frontal teaching of

linguistics and neuropsychology and guest lectures.

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Topics include the fundamentals of the normal (attention, perception, memory) and

pathological (agnosia, amnesia, attention deficits and frontal syndrome) mental processes.



Introduction to different models of neural networks and their characteristics, learning

processes in neural networks as developed in theoretical physics and computer sciences.

Emphasis is on use of these models in biology and psychology. Topics are presented

without proofs or complicated mathematical solutions. The course provides tutorials for

students with weak mathematical backgrounds and exercises in which students apply the

theory. At every opportunity, two teachers teach each topic: one presents theories and the

other the experimental viewpoint (for example, rules of learning in networks versus

synaptic changes in biology).

6. Signal and Data Analysis


The course deals with techniques for signal analysis (such as spectral analysis),

information theory and advanced statistical techniques for data analysis. The course

emphasizes the practicality of applying the techniques. Teaching is mostly from examples

from biological and psychological research. Students coming from a non-mathematical

background are required to take two additional hours of tutorials.

Joint compulsory activities

In addition to these core courses the students take a number of activities to widen their

horizons and encourage thinking and multidisciplinary exchange:

1. Weekly seminar

2. Intensive Study Days

3. Small research project

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4. Research issues

1. Weekly seminar

Lecturers in the weekly seminar include guest lecturers from the university staff, invited

lecturers, post-doctoral fellows currently studying at the university, and research students

about to submit their theses. The students are required to participate in this seminar for

the entire duration of their studies in the program.

2. Intensive Study days

There are three study days each year. Teachers from the Center for Brain Research, their

research students and students in the program travel to a special venue. Advanced

research students give lectures followed by a general discussion. Teachers and students

are encouraged to interact as they would at a real conference. Students are required to

take part in these study days for the entire duration of their studies in the program.

3. Small research project

The student joins one research group for one day a week and carries out a small project

under the direction of the group leader. The project may be experimental, an analysis of

existing results, development of a method or theoretical model, or writing of a critical

overview on a circumscribed topic. Each student completes two such projects.

4. Research issues

Group visits to researchers’ laboratories. During these visits the students hear about

typical research methods in the laboratory and view an experiment or a demonstration

characteristic of that laboratory.

5. Discussion of research problems

Students at advanced stages of their work present their research to the group.

Presentations are something between a journal report and a description of the student’s

research project.

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Preparatory courses for students lacking appropriate backgrounds

Preparatory courses are guided courses of study for small groups of students. The

program advisor determines those areas in which each student needs preparatory work.

Students take the preparatory courses during the first semester. The following preparatory

courses are given:

Mathematics

Scientific computer programming

Cell biology

Neuroanatomy

Neurophysiology of the neuron

Basic neurophysiology

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Appendix A

Core courses

1. Neurophysiology


The course presents current topics in research on the physiology of the brain. The course

combines frontal lectures with reading of articles and reporting on them by the students.

In some of the classes two teachers participate and present different views on the subject

of study (for example, psychophysics of vision and neurophysiology).

Topics include:

Secondary visual areas

Neurophysiology of attention

Motor planning and execution, the cerebellum, basal ganglia

Learning and memory

The hippocampus

The limbic system

The relationship between psychophysics and physiology

Coding in the nervous system

Neurophysiology of sleep and alertness

Current research results in classical fields of neurophysiology

The general information is based on: Kandel, Schwartz and Jessel: Principles of Neural

Science, although a large part of the material is based on recent original research papers

chosen each year by the teachers.

2. The neurochemical basis of normal and pathological brain processes


The course deals with neurochemistry and neuropharmacology of brain processes,

regulation of motivation and emotion and pathological processes. The course combines

frontal lectures with reading of articles and reporting on them by the students.

In some of the classes two teachers participate and present different views on the subject.

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Topics:

Neurochemistry and neuropharmacology of brain functions (neurotransmitters,

neuropeptides, neurohormones, receptors and secondary messengers).

Homeostatic regulation (eating, drinking, body temperature and the hypothalamus)

Stress, the HPA axis and energy

Brain mechanisms of motivation, reward and addiction

Mental dysfunction (affect disturbances, schizophrenia, PTSD, OCD and others)

Neurodegenerative diseases and stroke (Alzheimer, Parkinson, brain trauma)

Emotion and aggression

Neuroimmunology (neurotrophins, infectious brain diseases, the immune system and

degenerative diseases)

Biological clocks

Developmental psychology and baby-parent interaction

Sleep and sleep disturbances



The aim of this course is to present the students with the main topics in language and

brain research, to open up possibilities for research in this field and to give them a

meaningful introduction to the fundamental literature in the field. The general structure of

the course is a blend of structured teaching and “guest” lectures given by the

departmental staff. An effort is made to present each and every topic from different

points of view: linguistic theory, psycho-linguistic research on adult language,

neuropsychology, developmental research, etc.

Week 1 – Introduction. Changes in language studies from text analysis to linguistic

abilities, or what is linguistic knowledge; competence versus performance; the concept of

universal grammar, principles and parameters; relations between structure and meaning;

language universals.

Week 2– Phonology. The connection between phonology and phonetics. A number of

classic experiments, differential characteristics, inter-linguistic variability.

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Week 3 – (one meeting) – Morphology. Derived morphology. Rule systems; Linguistic

features which support these types of rules: Back derivation, linguistic innovations, etc.

Productive systems; Word identification and experiments.

Weeks 3-4 (two meetings) – Structure of components. Support for the psychological

reality of the syntactic structure. A number of classic experiments.

Weeks 4-5 (three meetings) – Semantic structures. Basic terms in semantics, semantic

fields, etc. Formal semantics; Compositional presentation; Abstract presentation.

Week 6 – Pragmatics. Implications and pre-assumptions. Different types of implications.

Week 7 – Modularity versus non-modularity in linguistic ability. A number of Fodor’s

classic studies.

Weeks 8-9 (three meetings) – Language acquisition

Weeks 9-10 (two meetings) – The psychology of reading

Weeks 10-11 (three meetings) Brain and Language. The hemispheres, etc. Which types

of experiments can be conducted? MRI research.

Week 12 – Speech deficits

Week 13 – Different models of speech ability, for example, connectionism



The course provides an introduction to normal (attention, perception, memory) and

pathological thinking processes (agnosia, amnesia, attention deficits and the frontal

syndrome).

Attention and attention deficits (developmental and acquired)

Perception and agnosia

Processes of memory and forgetting

Performance functions and frontal lobe syndrome

Motor control



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The course provides an introduction to different models of neural networks and their

characteristics, learning processes in neural networks as developed in theoretical physics

and computer sciences. Emphasis is on use of these models in biology and psychology.

Teaching does not involve proofs or complicated mathematical solutions. The course

provides tutorials for students with weak mathematical backgrounds and exercises in

which students apply the theory. At every opportunity, two teachers teach each topic such

that one presents theoretical views and the other the experimental viewpoint (for

example, rules of learning in networks versus synaptic changes in biology).

1. Models of a single nerve cell

Models based on biophysics of the nerve cell

The binary neuron

Sigmoid threshold

The analogue neuron

Integrate and fire

2. Representation and coding

Local and distributed presentation

Coding by time – single units

PCA

ICA

Spike-triggered average

Receptive fields in time and space

Coding by time - populations

Firing rates and correlation

Decoding

Coding capacity

3. Models of plasticity

Synaptic models

Hebbian learning rules

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Time-dependent plasticity

Local learning rules

Back propagation

4. Calculations by simple networks

Competitive networks

Inter-pattern association

Self-association

5. Networks with recurrent connections

Attractor networks (ANN)

ANN with symmetrical connections

ANN with low firing rhythms

Memory capacity of ANN

Point attractors and continuous attractors

Attractor sequences

6. Markov processes

Hidden Markov processes

7. Guided learning

The perceptron

Multilayer perceptron and learning by back propagation of error

PC analysis by networks

Multilayered networks

8. Machine learning (perhaps in an advanced course)

Clustering Genetic algorithms

Decision trees

PAC learning

VC dimensions

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This list contains more topics than can be covered in a single semester. The teacher in

charge chooses topics from the list. Different years cover different topics.

6. Signal and Data Analysis Single-semester course, 6 hours

The course deals with techniques for analyzing signals (such as spectral analysis),

information theory and advanced statistical techniques for data analysis. The course is

given on an intuitive level, with emphasis on the practicality of applying the techniques

studied. The instruction is provided mostly by examples taken from biological and

psychological research. Students coming from a non-mathematical background will take

two additional hours of tutorial.

1. Information Theory

Entropy

Mutual information

Channel capacity

Redundancy

Complexity

2. Methods of data collection

Biology: intra- and extracellular recording, EEG, EMG imaging

Psychology: psychophysics

Parameter estimation

3. Advanced statistical methods

Course analysis

Non-parametric statistics

Large numbers of measurements

Imaging in two- and three-dimensions

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4. Linear and stationary systems

Stationary linear transformation (filter)

Impulse response

Numerical filtering (IIR, FIR)

5. Stochastic processes

Autocorrelation

Cross correlation

Brownian motion and Markov processes

6. Point processes

Poisson processes

Renewal processes

7. Data evaluation

Algorithms for maximum expectation (EM)

Non-parametric methods

8. Analysis in the frequency domain

Spectrum

Power spectrum

Z- transform

Coherence

Analysis with the help of windows (Multi-taper)

Analysis of wave packets (Wavelet)

9. Statistical techniques in imaging

This list contains more topics than it is possible to include in a single semester. The

teacher in charge chooses topics from the list. Different years cover different topics.

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Joint compulsory activities

1. Weekly seminar – 1 credit

Lecturers in the weekly seminar include guest lecturers from the university staff, invited

lecturers, post-doctoral fellows currently studying at the university, and research students

about to submit their theses. The students are required to participate in this seminar for

the entire period of their studies in the program.

2. Intensive Study days – no credits

There are three study days each year. On these days teachers from the Center for Brain

Research, their research students and students of the program travel to a special venue.

Research students who are at advanced stages lecture on these days and each lecture is

accompanied by a general discussion. Teachers and students interact as they would in a

conference setting. The students are required to participate in these study days for the

entire period of their studies in the program.

3. Small research project – 3 credits

Each student joins one research group for one day a week and carries out a small project

under the direction of the group leader. The project may be experimental, an analysis of

existing results, development of a method or theoretical model, or writing of a critical

overview on a circumscribed topic. Each student carries out two such projects.

4. Research issues – 1 credit

The students visit a laboratory once a week for approximately two hours for the entire

first academic year. Group visits in researchers’ laboratories. During these visits the

students hear about typical research methods in the laboratory and view an experiment or

demonstration characteristic of that laboratory.

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5. Discussion of research problems

Students at advanced stages of their work participate in group discussions on their

research problems. Discussions alternate between a journal report and the student’s

research project.

In addition to about 40 specialization courses presently available, 21 new optional

courses geared especially for the program will be offered:

1. Computational techniques in models of neural networks

2. Techniques of data sorting

3. Quantitative models in neurophysiology

4. Exercises in neural networks and machine learning

5. Exercises in signal data analysis

6. Introduction to syntax and semantics

7. Introduction to phonology and morphology

8. Psycholinguistics and bilingualism


10. Language acquisition

11. Optimization of precision

12. Language and cognition

13. Signal transduction – what comes after the receptor? Pharmacology

14. Developmental psychobiology

15. The motor system in mammals

16. Evolutionary biology:

17. Motivation and affect

18. Memory and amnesia: neurophysiological perspective

19. Course in phase transitions

20. Course in processing and analysis of imaging data

21. Mental and brain diseases – advanced psychopathology

Documents

Program for the Degree of Doctor of Philosophy in