Search result: Catalogue data in Spring Semester 2020
Biology Master | ||||||
Elective Major Subject Areas | ||||||
Elective Major: Neurosciences The major in Neurosciences in the Master program Biology ETHZ will no longer be offered from autumn 2019 onwards. | ||||||
Elective Compulsory Master Courses | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
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227-1034-00L | Computational Vision (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI402 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/mobilitaet.html | W | 6 credits | 2V + 1U | D. Kiper | |
Abstract | This course focuses on neural computations that underlie visual perception. We study how visual signals are processed in the retina, LGN and visual cortex. We study the morpholgy and functional architecture of cortical circuits responsible for pattern, motion, color, and three-dimensional vision. | |||||
Learning objective | This course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed. The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered. | |||||
Content | This course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed. The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered. | |||||
Literature | Books: (recommended references, not required) 1. An Introduction to Natural Computation, D. Ballard (Bradford Books, MIT Press) 1997. 2. The Handbook of Brain Theorie and Neural Networks, M. Arbib (editor), (MIT Press) 1995. | |||||
227-1046-00L | Computer Simulations of Sensory Systems Does not take place this semester. | W | 3 credits | 3G | ||
Abstract | This course deals with computer simulations of the human auditory, visual, and balance system. The lecture will cover the physiological and mechanical mechanisms of these sensory systems. And in the exercises, the simulations will be implemented with Python. The simulations will be such that their output could be used as input for actual neuro-sensory prostheses. | |||||
Learning objective | Our sensory systems provide us with information about what is happening in the world surrounding us. Thereby they transform incoming mechanical, electromagnetic, and chemical signals into “action potentials”, the language of the central nervous system. The main goal of this lecture is to describe how our sensors achieve these transformations, how they can be reproduced with computational tools. For example, our auditory system performs approximately a “Fourier transformation” of the incoming sound waves; our early visual system is optimized for finding edges in images that are projected onto our retina; and our balance system can be well described with a “control system” that transforms linear and rotational movements into nerve impulses. In the exercises that go with this lecture, we will use Python to reproduce the transformations achieved by our sensory systems. The goal is to write programs whose output could be used as input for actual neurosensory prostheses: such prostheses have become commonplace for the auditory system, and are under development for the visual and the balance system. For the corresponding exercises, at least some basic programing experience is required!! | |||||
Content | The following topics will be covered: • Introduction into the signal processing in nerve cells. • Introduction into Python. • Simplified simulation of nerve cells (Hodgkins-Huxley model). • Description of the auditory system, including the application of Fourier transforms on recorded sounds. • Description of the visual system, including the retina and the information processing in the visual cortex. The corresponding exercises will provide an introduction to digital image processing. • Description of the mechanics of our balance system, and the “Control System”-language that can be used for an efficient description of the corresponding signal processing (essentially Laplace transforms and control systems). | |||||
Lecture notes | For each module additional material will be provided on the e-learning platform "moodle". The main content of the lecture is also available as a wikibook, under http://en.wikibooks.org/wiki/Sensory_Systems | |||||
Literature | Open source information is available as wikibook http://en.wikibooks.org/wiki/Sensory_Systems For good overviews I recommend: • Principles of Neural Science (5th Ed, 2012), by Eric Kandel, James Schwartz, Thomas Jessell, Steven Siegelbaum, A.J. Hudspeth ISBN 0071390111 / 9780071390118 THE standard textbook on neuroscience. • L. R. Squire, D. Berg, F. E. Bloom, Lac S. du, A. Ghosh, and N. C. Spitzer. Fundamental Neuroscience, Academic Press - Elsevier, 2012 [ISBN: 9780123858702]. This book covers the biological components, from the functioning of an individual ion channels through the various senses, all the way to consciousness. And while it does not cover the computational aspects, it nevertheless provides an excellent overview of the underlying neural processes of sensory systems. • G. Mather. Foundations of Sensation and Perception, 2nd Ed Psychology Press, 2009 [ISBN: 978-1-84169-698-0 (hardcover), oder 978-1-84169-699-7 (paperback)] A coherent, up-to-date introduction to the basic facts and theories concerning human sensory perception. • The best place to get started with Python programming are the https://scipy-lectures.org/ | |||||
Prerequisites / Notice | • Since I have to gravel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture in blocks (every 2nd week). • In addition to the lectures, this course includes external lab visits to institutes actively involved in research on the relevant sensory systems. | |||||
227-0390-00L | Elements of Microscopy | W | 4 credits | 3G | M. Stampanoni, G. Csúcs, A. Sologubenko | |
Abstract | The lecture reviews the basics of microscopy by discussing wave propagation, diffraction phenomena and aberrations. It gives the basics of light microscopy, introducing fluorescence, wide-field, confocal and multiphoton imaging. It further covers 3D electron microscopy and 3D X-ray tomographic micro and nanoimaging. | |||||
Learning objective | Solid introduction to the basics of microscopy, either with visible light, electrons or X-rays. | |||||
Content | It would be impossible to imagine any scientific activities without the help of microscopy. Nowadays, scientists can count on very powerful instruments that allow investigating sample down to the atomic level. The lecture includes a general introduction to the principles of microscopy, from wave physics to image formation. It provides the physical and engineering basics to understand visible light, electron and X-ray microscopy. During selected exercises in the lab, several sophisticated instrument will be explained and their capabilities demonstrated. | |||||
Literature | Available Online. | |||||
376-1306-00L | Clinical Neuroscience More information at:https://studentservices.uzh.ch/uzh/anonym/vvz/index.html#/details/2019/004/P/01106803 | W | 3 credits | 3V | G. Schratt, University lecturers | |
Abstract | The lecture series "Clinical Neuroscience" presents a comprehensive, condensed overview of the most important neurological diseases, their clinical presentation, diagnosis, therapy options and possible causes. Patient demonstrations (Übungen) follow every lecture that is dedicated to a particular disease. | |||||
Learning objective | By the end of this module students should be able to: - demonstrate their understanding and deep knowledge concerning the main neurological diseases - identify and explain the different clinical presentation of these diseases, the methodology of diagnosis and the current therapies available - summarize and critically review scientific literature efficiently and effectively | |||||
376-1414-01L | Current Topics in Brain Research (FS) | W | 1 credit | 1.5K | I. Mansuy, F. Helmchen, further lecturers | |
Abstract | Different national and international scientific guests are invited to present and discuss their most recent scientific results. | |||||
Learning objective | The aim is to exchange scientific knowledge and data as well as to promote communication and collaboration among researchers. Students taking the course participate in all seminars within one semester and write a critical report about one seminar of their choice. Prof. Isabelle / Dr. Alberto Corcoba will send instructions for this report to students who have registered for the course one week before the start of the semester. | |||||
Content | Various scientific guests from the fields of neuroepigenetics, neurochemistry, neuromorphology and neurophysiology will report on their latest scientific findings. | |||||
Lecture notes | no handout | |||||
Literature | no literature |
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