Suchergebnis: Katalogdaten im Frühjahrssemester 2019

Biologie Master Information
Wahlvertiefungen
Wahlvertiefung: Neurowissenschaften
Wahlpflicht Masterkurse
NummerTitelTypECTSUmfangDozierende
227-1034-00LComputational Vision (University of Zurich) Information
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:
Link
W6 KP2V + 1UD. Kiper
KurzbeschreibungThis 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.
LernzielThis 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.
InhaltThis 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.
LiteraturBooks: (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.
227-1046-00LComputer Simulations of Sensory Systems Information W3 KP2V + 1UT. Haslwanter
KurzbeschreibungThis 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 (or Matlab). The simulations will be such that their output could be used as input for actual neuro-sensory prostheses.
LernzielOur 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!!
InhaltThe 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).
SkriptFor 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 Link
LiteraturOpen source information is available as wikibook Link

For good overviews I recommend:
• 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.

• 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.

• P Wallisch, M Lusignan, M. Benayoun, T. I. Baker, A. S. Dickey, and N. G. Hatsopoulos. MATLAB for Neuroscientists, Academic Press, 2009.
Compactly written, it provides a short introduction to MATLAB, as well as a very good overview of MATLAB’s functionality, focusing on applications in different areas of neuroscience.

• 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.
Voraussetzungen / BesonderesSince I have to gravel from Linz, Austria, to Zurich to give this lecture, I plan to hold this lecture in blocks (every 2nd week).
227-0390-00LElements of MicroscopyW4 KP3GM. Stampanoni, G. Csúcs, A. Sologubenko
KurzbeschreibungThe 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.
LernzielSolid introduction to the basics of microscopy, either with visible light, electrons or X-rays.
InhaltIt 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.
LiteraturAvailable Online.
376-1306-00LClinical Neuroscience Information W3 KP3GG. Schratt, Uni-Dozierende
KurzbeschreibungThe 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.
LernzielBy 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
376-1414-01LCurrent Topics in Brain Research (FS)W1 KP1.5KI. Mansuy, F. Helmchen, weitere Dozierende
KurzbeschreibungEs werden verschiedene wissenschaftliche Gäste aus dem In-und Ausland eingeladen, um ihre aktuellen Forschungsdaten zu präsentieren und diskutieren.
LernzielEs soll der Austausch von wissenschaftlichen Erkenntnissen und Daten sowie die Kommunikation und Zusammenarbeit zwischen den Forschenden gefördert werden. Studierende, welche den Kurs belegen, besuchen während eines Semesters alle Seminare und schreiben einen kritischen Report über ein Seminar ihrer Wahl. Die Anleitung dazu erhalten eingeschriebene Studierende von Prof. Isabelle Mansuy / Dr. Silvia Schelbert.
InhaltVerschiedene wissenschaftliche Gäste aus den Bereichen Molekulares Bewusstsein, Neurochemie, Neuromorphologie und Neurophysiologie berichten über ihre neuesten wissenschaftlichen Erkenntnisse.
Skriptkein Skript
Literaturkeine Literatur
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