Search result: Catalogue data in Autumn Semester 2016

Number	Title	Type	ECTS	Hours	Lecturers
MAS in Medical Physics
Specialization: General Medical Physics and Biomedical Engineering
Major in Neuroinformatics
Core Courses
227-1037-00L	Introduction to Neuroinformatics	W	6 credits	2V + 1U	K. A. Martin, M. Cook, V. Mante, M. Pfeiffer
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.
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, the neural architectures of feedforward and recurrent networks will be discussed in the context of co-ordination, control, and integration of sensory and motor information in neural networks.
551-1295-00L	Introduction to Bioinformatics: Concepts and Applications	W	6 credits	4G	W. Gruissem, K. Bärenfaller, A. Caflisch, G. Capitani, J. Fütterer, M. Robinson, A. Wagner
Abstract	Storage, handling and analysis of large datasets have become essential in biological research. The course will introduce students to a number of applications of bioinformatics in biology. Freely accessible software tools and databases will be explained and explored in theory and praxis.
Objective	Introduction to Bioinformatics I: Concepts and Applications (formerly Bioinformatics I) will provide students with the theoretical background of approaches to store and retrieve information from large databases. Concepts will be developed how DNA sequence information can be used to understand phylogentic relationships, how RNA sequence relates to structure, and how protein sequence information can be used for genome annotation and to predict protein folding and structure. Students will be introduced to quantitative methods for measuring gene expression and how this information can be used to model gene networks. Methods will be discussed to construct protein interaction maps and how this information can be used to simulate dynamic molecular networks. In addition to the theoretical background, the students will develop hands-on experiences with the bioinformatics methods through guided exercises. The course provides students from different backgrounds with basic training in bioinformatics approaches that have impact on biological, chemical and physics experimentation. Bioinformatics approaches draw significant expertise from mathematics, statistics and computational science. Although "Intoduction to Bioinformatics I" will focus on theory and praxis of bioinformatics approaches, the course provides an important foundation for the course "Introduction to Bioinformatics II: Fundamentals of computer science, modeling and algorithms" that will be offered in the following semester.
Content	Bioinformatics I will cover the following topics: From genes to databases and information BLAST searches Prediction of gene function and regulation RNA structure prediction Gene expression analysis using microarrays Protein sequence and structure databases WWW for bioinformatics Protein sequence comparisons Proteomics and de novo protein sequencing Protein structure prediction Cellular and protein interaction networks Molecular dynamics simulation

Practical Work
Number	Title	Type	ECTS	Hours	Lecturers
465-0800-00L	Practical Work Only for MAS in Medical Physics	O	4 credits		external organisers
Abstract	The practical work is designed to train the students in the solution of a specific problem and provides insights in the field of the selected MAS specialization. Tutors propose the subject of the project, the project plan, and the roadmap together with the student, as well as monitor the overall execution.
Objective	The practical work is aimed at training the student’s capability to apply and connect specific skills acquired during the MAS specialization program towards the solution of a focused problem.

Electives
Number	Title	Type	ECTS	Hours	Lecturers
227-1033-00L	Neuromorphic Engineering I 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.	W	6 credits	2V + 3U	T. Delbrück, G. Indiveri, S.‑C. Liu
Abstract	This course covers analog circuits with emphasis on neuromorphic engineering: MOS transistors in CMOS technology, static circuits, dynamic circuits, systems (silicon neuron, silicon retina, silicon cochlea) with an introduction to multi-chip systems. The lectures are accompanied by weekly laboratory sessions.
Objective	Understanding of the characteristics of neuromorphic circuit elements.
Content	Neuromorphic circuits are inspired by the organizing principles of biological neural circuits. Their computational primitives are based on physics of semiconductor devices. Neuromorphic architectures often rely on collective computation in parallel networks. Adaptation, learning and memory are implemented locally within the individual computational elements. Transistors are often operated in weak inversion (below threshold), where they exhibit exponential I-V characteristics and low currents. These properties lead to the feasibility of high-density, low-power implementations of functions that are computationally intensive in other paradigms. Application domains of neuromorphic circuits include silicon retinas and cochleas for machine vision and audition, real-time emulations of networks of biological neurons, and the development of autonomous robotic systems. This course covers devices in CMOS technology (MOS transistor below and above threshold, floating-gate MOS transistor, phototransducers), static circuits (differential pair, current mirror, transconductance amplifiers, etc.), dynamic circuits (linear and nonlinear filters, adaptive circuits), systems (silicon neuron, silicon retina and cochlea) and an introduction to multi-chip systems that communicate events analogous to spikes. The lectures are accompanied by weekly laboratory sessions on the characterization of neuromorphic circuits, from elementary devices to systems.
Literature	S.-C. Liu et al.: Analog VLSI Circuits and Principles; various publications.
Prerequisites / Notice	Particular: The course is highly recommended for those who intend to take the spring semester course 'Neuromorphic Engineering II', that teaches the conception, simulation, and physical layout of such circuits with chip design tools. Prerequisites: Background in basics of semiconductor physics helpful, but not required.
376-1795-00L	Advanced Course in Neurobiology I (Functional Anatomy of the Rodent Brain) (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: SPV0Y009 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html	W	2 credits	2V	J.‑M. Fritschy, H. U. Zeilhofer
Abstract	The goal of this Advanced Course in Neurobiology is to provide students with a broader knowledge in several important areas of neurobiology. The course consists of four parts: Part I deals with various topics in developmental neurobiology. Part II is devoted to aspects of signal transduction. Part III focuses on synaptic transmission. Part IV gives deeper insights into systems neuroscience.
Objective	This credit point course is designed for doctoral students who have successfully completed the Introductory Course in Neuroscience at the Neuroscience Center Zürich. The goal is to provide students with a broader and deeper knowledge in several important areas of neurobiology.
Prerequisites / Notice	Für Doktorierende des Zentrums für Neurowissenschaften Zürich. Nicht für Master-Studierende geeignet.
376-1791-00L	Introductory Course in Neuroscience I (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: SPV0Y005 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html	W	2 credits	2V	J.‑M. Fritschy, W. Knecht
Abstract	The course gives an introduction to human and comparative neuroanatomy, molecular, cellular and systems neuroscience.
Objective	The course gives an introduction to human and comparative neuroanatomy, molecular, cellular and systems neuroscience.
Content	1) Human Neuroanatomy I&II 2) Comparative Neuroanatomy 3) Development I&II 4) Membran and Action Potential 5) Synaptic Transmission & Plasticity I&II 6) Glia and Blodd-Brain-Barrier 7) Somatosensory and Motor System 8) Visual System 9) Auditory System 10) Circuits underlying Emotion 11) Modeling of Neural Circuits
Prerequisites / Notice	For doctoral students of the Neuroscience Center Zurich (ZNZ).

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