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
Single-semester course, 4 hours
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).
3. Brain and language
Single-semester course, 4 hours
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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4. Normal and pathological cognitive processes
Single-semester course, 4 hours
Topics include the fundamentals of the normal (attention, perception, memory) and
pathological (agnosia, amnesia, attention deficits and frontal syndrome) mental processes.
5. Theory of neural networks and machine learning
Single-semester course, 6 hours
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
Single-semester course, 6 hours
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
Single-semester course, 4 hours
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
Single-semester course, 4 hours
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
3. Brain and language
Single-semester course, 4 hours
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
4. Normal and pathological cognitive processes
Single-semester course, 4 hours
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
5. Theory of neural networks and machine learning
Single-semester course, 6 hours
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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
9. Brain and language
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