Wolfger von der Behrens: Catalogue data in Autumn Semester 2023 |
| Name | Dr. Wolfger von der Behrens |
| Address | Professur für Neurotechnologie ETH Zürich, Y55 G 54 Winterthurerstrasse 190 8057 Zürich SWITZERLAND |
| Telephone | +41 44 633 80 82 |
| vwolfger@ethz.ch | |
| URL | https://services.ini.uzh.ch/people/wolfger |
| Department | Information Technology and Electrical Engineering |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||
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| 227-1037-00L | Introduction to Neuroinformatics  | 6 credits | 2V + 1U + 1A | V. Mante, M. Cook, B. Grewe, G. Indiveri, D. Kiper, W. von der Behrens | ||||||||||||||||||||
| Abstract | The course provides an introduction to the functional properties of neurons. Particularly the description of membrane electrical properties (action potentials, channels), neuronal anatomy, synaptic structures, and neuronal networks. Simple models of computation, learning, and behavior will be explained. Some artificial systems (robot, chip) are presented. | |||||||||||||||||||||||
| Learning objective | Understanding computation by neurons and neuronal circuits is one of the great challenges of science. Many different disciplines can contribute their tools and concepts to solving mysteries of neural computation. The goal of this introductory course is to introduce the monocultures of physics, maths, computer science, engineering, biology, psychology, and even philosophy and history, to discover the enchantments and challenges that we all face in taking on this major 21st century problem and how each discipline can contribute to discovering solutions. | |||||||||||||||||||||||
| Content | This course considers the structure and function of biological neural networks at different levels. The function of neural networks lies fundamentally in their wiring and in the electro-chemical properties of nerve cell membranes. Thus, the biological structure of the nerve cell needs to be understood if biologically-realistic models are to be constructed. These simpler models are used to estimate the electrical current flow through dendritic cables and explore how a more complex geometry of neurons influences this current flow. The active properties of nerves are studied to understand both sensory transduction and the generation and transmission of nerve impulses along axons. The concept of local neuronal circuits arises in the context of the rules governing the formation of nerve connections and topographic projections within the nervous system. Communication between neurons in the network can be thought of as information flow across synapses, which can be modified by experience. We need an understanding of the action of inhibitory and excitatory neurotransmitters and neuromodulators, so that the dynamics and logic of synapses can be interpreted. Finally, simple neural architectures of feedforward and recurrent networks are discussed in the context of co-ordination, control, and integration of sensory and motor information. Connections to computer science and artificial intelligence are discussed, but the main focus of the course is on establishing the biological basis of computations in neurons. | |||||||||||||||||||||||
| 227-1039-00L | Basics of Instrumentation, Measurement, and Analysis (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: INI502 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html Registration in this class requires the permission of the instructors. Class size will be limited to available lab spots. Preference is given to students that require this class as part of their major. | 4 credits | 9S | S.‑C. Liu, T. Delbrück, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens | ||||||||||||||||||||
| Abstract | Experimental data are always as good as the instrumentation and measurement, but never any better. This course provides the very basics of instrumentation relevant to neurophysiology and neuromorphic engineering, it consists of two parts: a common introductory part involving analog signals and their acquisition (Part I), and a more specialized second part (Part II). | |||||||||||||||||||||||
| Learning objective | The goal of Part I is to provide a general introduction to the signal acquisition process. Students are familiarized with basic lab equipment such as oscilloscopes, function generators, and data acquisition devices. Different electrical signals are generated, visualized, filtered, digitized, and analyzed using Matlab (Mathworks Inc.) or Labview (National Instruments). In Part II, the students are divided into small groups to work on individual measurement projects according to availability and interest. Students single-handedly solve a measurement task, making use of their basic knowledge acquired in the first part. Various signal sources will be provided. | |||||||||||||||||||||||
| Prerequisites / Notice | For each part, students must hand in a written report and present a live demonstration of their measurement setup to the respective supervisor. The supervisor of Part I is the teaching assistant, and the supervisor of Part II is task specific. Admission to Part II is conditional on completion of Part I (report + live demonstration). Reports must contain detailed descriptions of the measurement goal, the measurement procedure, and the measurement outcome. Either confidence or significance of measurements must be provided. Acquisition and analysis software must be documented. | |||||||||||||||||||||||
| 227-1045-00L | Readings in Neuroinformatics (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: INI431 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html | 3 credits | 1S | W. von der Behrens, R. Hahnloser, S.‑C. Liu, V. Mante | ||||||||||||||||||||
| Abstract | Thirteen major areas of research have been selected, which cover the key concepts that have led to our current ideas of how the nervous system is built and functions. We will read both original papers and explore the conceptual the links between them and discuss the 'sociology' of science, the pursuit of basic science questions over a century of research." | |||||||||||||||||||||||
| Learning objective | It is commonplace that scientists rarely cite literature that is older than 10 years and when they do, they usually cite one paper that serves as the representative for a larger body of work that has long since been incorporated anonymously in textbooks. Even worse, many authors have not even read the papers they cite in their own publications. This course, ‘Foundations of Neuroscience’ is one antidote. Thirteen major areas of research have been selected. They cover the key concepts that have led to our current ideas of how the nervous system is built and functions. Unusually, we will explore these areas of research by reading the original publications, instead of reading a digested summary from a textbook or review. By doing this, we will learn how the discoveries were made, what instrumentation was used, how the scientists interpreted their own findings, and how their work, often over many decades and linked together with related findings from many different scientists, generate the current views of mechanism and structure of the nervous system. We will read different original papers and explore the conceptual links between them and discuss the ‘sociology’ of science. We will also explore the personalities of the scientists and the context in which they made their seminal discoveries. Each week , course members will be given original papers to read for homework and they will write a short abstract for each paper. We will then meet weekly with the course leader and an assistant for an hour-or-so long interactive seminar. An intimate knowledge of the papers will be assumed so that the discussion does not center simply on an explication of the contents of the papers. Assessment will be in the form of assignments throughout the semester. | |||||||||||||||||||||||
| Content | It is commonplace that scientists rarely cite literature that is older than 10 years and when they do, they usually cite one paper that serves as the representative for a larger body of work that has long since been incorporated anonymously in textbooks. Even worse, many authors have not even read the papers they cite in their own publications. This course, ‘Foundations of Neuroscience’ is one antidote. Thirteen major areas of research have been selected. They cover the key concepts that have led to our current ideas of how the nervous system is built and functions. Unusually, we will explore these areas of research by reading the original publications, instead of reading a digested summary from a textbook or review. By doing this, we will learn how the discoveries were made, what instrumentation was used, how the scientists interpreted their own findings, and how their work, often over many decades and linked together with related findings from many different scientists, generate the current views of mechanism and structure of the nervous system. We will read different original papers and explore the conceptual links between them and discuss the ‘sociology’ of science. We will also explore the personalities of the scientists and the context in which they made their seminal discoveries. Each week , course members will be given original papers to read for homework and they will write a short abstract for each paper. We will then meet weekly with the course leader and an assistant for an hour-or-so long interactive seminar. An intimate knowledge of the papers will be assumed so that the discussion does not center simply on an explication of the contents of the papers. Assessment will be in the form of assignments throughout the semester. | |||||||||||||||||||||||
| Prerequisites / Notice | Restricted adminission. Only open for students of the MSc program 'Neural Systems and Computation'. | |||||||||||||||||||||||
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| 376-1305-01L | Neural Systems for Sensory, Motor and Higher Brain Functions Information for UZH students: Enrolment to this course unit only possible at ETH. No enrolment to module BIO343 at UZH. Please mind the ETH enrolment deadlines for UZH students: Link | 3 credits | 2V | G. Schratt, J. Bohacek, R. Fiore, R. Polania, W. von der Behrens, J. Winterer, further lecturers | ||||||||||||||||||||
| Abstract | The course covers the structure of the adult nervous system (NS) with focus on: sensory systems, cognitive functions, learning and memory, molecular and cellular mechanisms, animal models, and diseases of the NS. | |||||||||||||||||||||||
| Learning objective | The aim is to give a deepened insight into the structure of the nervous system based on molecular, cellular and biochemical approaches. | |||||||||||||||||||||||
| Content | The main focus is on the structure of the NS: biology of the adult nervous system; structural plasticity of the adult nervous system, repair of the NS: networks and nerve fibers, pathological loss of cells. | |||||||||||||||||||||||
| Literature | The lecture requires reading of book chapters, handouts and original scientific papers. Further information will be given in the individual lectures and are mentioned on Moodle. | |||||||||||||||||||||||
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