קורסים ומערכת שעות- תארים מתקדמים

Neural Networks (27504)

4+2 hours/week. Teaching staff: Gal Chechik, Uri Shalit, 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.

The Neurochemical Basis of Normal and Pathological Brain Processes (27501)

4 hours/week. Teaching staff: Aron Weller 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, Guy Zurawel, 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.

Mathematics (27506)

6+2 hours/week. Teaching staff: Tomer Gazit, Lior Kirsch, 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: Izhar Bar-Gad, Noa Liscovitch, 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.

Introduction to Cell Biology (27212)

2 hours/week. Teaching staff: Zvi Malik, Class site

This course is intended for students with no background in biology. The course aims to introduce essential topics in cell biology. The following topics will be discussed: The cellular membrane and transport across the membrane, ATP generation, DNA transcription and regulation, Protein synthesis and regulation. Textbook: "The cell: Structure and Function" (An Open University book series).

Neuroanatomy (27312)

4+1 hours/week. Teaching staff: Assaf Marom, Nadav Stoppelman, Idan Tal, Edna Litmanovitch

The course begins with a survey of all components of the central nervous system, on a microscopic level (histology) and also on a macroscopic one. We will describe the main events during neural development and learn about the anatomy (and functional anatomy) of adult brain structures arising from the 5 embryonic vesicles. Examining adult brain anatomy, we will trace the morphological changes of the neural tube during development. We will also study various subjects such as hemispheral white matter organization, structure of the brain chambers, the meninges, blood supply and drainage, the peripheral nervous system, cranial nerves and the autonomic nervous system. We will conduct dissections of human brains in the lab, following the main course topics.

Cellular Neurophysiology (80338)

4 hours/week. Teaching staff: Alon Korngreen

In this course we will study the following subjects: movement of ions through the membrane, electrical properties of neuronal membranes, passive cable theory and linear electrical properties of neurons, non-linear properties of neural membranes, Hodgkin-Huxley model, biophysics of voltage-dependent ion channels, structure and function of ion channels, basic analysis of single-channel recordings, pre- and post-synaptic mechanisms of synaptic transmission, role of calcium in synaptic transmission, methods of recording neuronal activity, cellular neurophysiology of learning and memory, functional properties of dendrites.