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Program for the Degree of Doctor of Philosophy in ... Program for the Degree of Doctor of Philosophy in ... Document Transcript

  • Program for the Degree of Doctor of Philosophy in Multidisciplinary Brain Research
  • 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. 2
  • 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 3
  • 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. 4
  • 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 5
  • 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. 6
  • 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 7
  • 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. 8
  • 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. 9
  • 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 10
  • 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 11
  • 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 12
  • 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 13
  • 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. 14
  • 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. 15
  • 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 16