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קורסי ליבה

 

Neural Networks (27504)

4+2 hours/week. Teaching staff: Gal Chechik, Class site


How can neural systems learn and compute? This course covers the theory and algorithms that allow networks of model neurons to compute, learn and remember. The course focuses on three topics: (1) Modeling neurons and neural networks as dynamical systems; (2) Theory of information processing and plasticity; (3) Theory and algorithms of learning from examples. The course provides rigorous analysis for some of the theory and algorithm, but also emphasizes the intuition behind them, and their potential implications for perception, and cognitive processing. Students are expected to have good foundations in algebra and applied probability. Course requirements: home assignments, mid-term exam and final exam.

 

Brain and Language (27503)

4 hours/week Teaching staff: Michal Ben-Shachar


Topics include the fundamentals of the normal (attention, perception, memory) and pathological (agnosia, amnesia, attention deficits and frontal syndrome) mental processes.

 

Synaptic Neurochemistry (27595)

4 hours/week. Teaching staff: Ed Stern Class site


The course deals with neurochemistry and neuropharmacology of brain processes, regulation of motivation and emotion, and pathological processes. The course combines frontal lectures with student presentations of relevant articles.

 

Neurophysiology (27502)

4 hours/week. Teaching staff: Hamutal Slovin, Class site


The course deals with current topics in research on the physiology of the brain. The course combines frontal lectures with student presentations. 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).

 

Signal and Data Analysis in Neuroscience (27505)

2+4 hours/week. Teaching staff: Izhar Bar-Gad, Ayala Matzner Class site


The course encompasses various topics in signal analysis and advanced statistical techniques for data analysis used in neuroscience such as neural encoding/decoding, information theory, dimensionality reduction and spectral 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.

קורסי השלמה

 

Mathematics (27506)

6+2 hours/week. Teaching staff: Sarit Nathanv Vadim Axelrod, Roy Oz Class site


The course provides an introduction to three topics: (1) Linear Algebra (2) Calculus and (3) Probability. The goal of the course is to provide graduate students with the necessary mathematical tools for the following courses at our center: signal analysis and neural networks, as well as providing basic mathematics tools for research. Therefore, the focus of this course is on applicable fields of mathematics. By the end of the course the students will achieve a fundamental understanding of these aspects along with their implementation.


Specifically, The course covers topics in Linear Algebra (including matrix manipulations, vector spaces, linear transforms, eigen-vectors and eigen-values, matrix diagonalization, orthogonality), in Calculus (including multivariate functions and gradients, differential equations, Taylor and Fourier series) and in Probability (including Bayes rules, single and multivariate random variables, probability density function, expectancy, variance and covariance, uniform, Poisson, exponential and Gaussian distributions).

 

Scientific Programming Using MATLAB (27521)

2+2 hours/week. Teaching staff:  Class site


In this course the students learn to use the MATLAB programming environment and language, starting with basic programming concepts such as variables and flow control and moving on to advanced topics such as designing GUI in MATLAB and using specialized toolboxes.

 

Neurophysiology of the Systems (27512)

4 hours/week. Teaching staff: Hamutal Slovin, Class site


The course aims to establish a solid background in system Neuroscience. The main topics are: chemical senses: taste and smell, vision, the auditory and vestibualr systems, the somatic sensory system, spinal and brain control of movement, the autonomic system, memory, attention and sleep.