Search result: Catalogue data in Autumn Semester 2022

Health Sciences and Technology Master Information
Major in Neurosciences
Elective Courses
NumberTitleTypeECTSHoursLecturers
227-0447-00LImage Analysis and Computer Vision Information W6 credits3V + 1UE. Konukoglu, F. Yu
AbstractLight and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition. Deep learning and Convolutional Neural Networks.
ObjectiveOverview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.
ContentThis course aims at offering a self-contained account of computer vision and its underlying concepts, including the recent use of deep learning.
The first part starts with an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First the interaction of light with matter is considered. The most important hardware components such as cameras and illumination sources are also discussed. The course then turns to image discretization, necessary to process images by computer.
The next part describes necessary pre-processing steps, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and 3D shape as two important examples. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed. A major part at the end is devoted to deep learning and AI-based approaches to image analysis. Its main focus is on object recognition, but also other examples of image processing using deep neural nets are given.
Lecture notesCourse material Script, computer demonstrations, exercises and problem solutions
Prerequisites / NoticePrerequisites:
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Python and Linux.
The course language is English.
227-1037-00LIntroduction to Neuroinformatics Information W6 credits2V + 1U + 1AV. Mante, M. Cook, B. Grewe, G. Indiveri, D. Kiper, W. von der Behrens
AbstractThe 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.
ObjectiveUnderstanding 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.
ContentThis 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.
227-1047-00LConsciousness: From Philosophy to Neuroscience (University of Zurich) Information
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student.
UZH Module Code: INI410

Mind the enrolment deadlines at UZH:
Link
W3 credits2VD. Kiper
AbstractThis seminar reviews the philosophical and phenomenological as well as the neurobiological aspects of consciousness. The subjective features of consciousness are explored, and modern research into its neural substrate, particularly in the visual domain, is explained. Emphasis is placed on students developing their own thinking through a discussion-centered course structure.
ObjectiveThe course's goal is to give an overview of the contemporary state of consciousness research, with emphasis on the contributions brought by modern cognitive neuroscience. We aim to clarify concepts, explain their philosophical and scientific backgrounds, and to present experimental protocols that shed light on on a variety of consciousness related issues.
ContentThe course includes discussions of scientific as well as philosophical articles. We review current schools of thought, models of consciousness, and proposals for the neural correlate of consciousness (NCC).
Lecture notesNone
LiteratureWe display articles pertaining to the issues we cover in the class on the course's webpage.
Prerequisites / NoticeSince we are all experts on consciousness, we expect active participation and discussions!
327-2125-00LMicroscopy Training SEM I - Introduction to SEM Restricted registration - show details
The number of participants is limited. In case of overbooking, the course will be repeated once. All registrations will be recorded on the waiting list.

For PhD students, postdocs and others, a fee will be charged (Link).

All applicants must additionally register on this form: (link will follow)
The selected applicants will be contacted and asked for confirmation a few weeks before the course date.
W2 credits3PP. Zeng, A. G. Bittermann, S. Gerstl, L. Grafulha Morales, K. Kunze, F. Lucas, J. Reuteler
AbstractThis introductory course on Scanning Electron Microscopy (SEM) emphasizes hands-on learning. Using ScopeM SEMs, students have the opportunity to study their own samples (or samples provided) and solve practical problems by applying knowledge acquired during the lectures. At the end of the course, students will be able to apply SEM for their (future) research projects.
Objective- Set-up, align and operate a SEM successfully and safely.
- Understand important operational parameters of SEM and optimize microscope performance.
- Explain different signals in SEM and obtain secondary electron (SE) and backscatter electron (BSE) images.
- Operate the SEM in low-vacuum mode.
- Make use of EDX for semi-quantitative elemental analysis.
- Prepare samples with different techniques and equipment for imaging and analysis by SEM.
ContentDuring the course, students learn through lectures, demonstrations, and hands-on sessions how to setup and operate SEM instruments, including low-vacuum and low-voltage applications.
This course gives basic skills for students new to SEM. At the end of the course, students are able to align an SEM, to obtain secondary electron (SE) and backscatter electron (BSE) images and to perform energy dispersive X-ray spectroscopy (EDX) semi-quantitative analysis. Emphasis is put on procedures to optimize SEM parameters in order to best solve practical problems and deal with a wide range of materials.

Lectures:
- Introduction on Electron Microscopy and instrumentation
- electron sources, electron lenses and probe formation
- beam/specimen interaction, image formation, image contrast and imaging modes.
- sample preparation techniques for EM
- X-ray micro-analysis (theory and detection), qualitative and semi-quantitative EDX and point analysis, linescan and spectral mapping

Practicals:
- Brief description and demonstration of the SEM microscope
- Practice on image formation, image contrast (and image processing)
- Student participation on sample preparation techniques
- Scanning Electron Microscopy lab exercises: setup and operate the instrument under various imaging modalities
- Practice on real-world samples and report results
Lecture notesLecture notes will be distributed.
Literature- Peter Goodhew, John Humphreys, Richard Beanland: Electron Microscopy and Analysis, 3rd ed., CRC Press, 2000
- Joseph Goldstein, et al, Scanning Electron Microscopy and X-Ray Microanalysis, 4th ed, Srpinger US, 2018
- Egerton: Physical Principles of Electron Microscopy: an introduction to TEM, SEM and AEM, Springer Verlag, 2007
Prerequisites / NoticeNo mandatory prerequisites.
327-2126-00LMicroscopy Training TEM I - Introduction to TEM Restricted registration - show details
The number of participants is limited. In case of overbooking, the course will be repeated once. All registrations will be recorded on the waiting list.

For PhD students, postdocs and others, a fee will be charged (Link).

All applicants must additionally register on this form: (link will follow)
The selected applicants will be contacted and asked for confirmation a few weeks before the course date.
W2 credits3PP. Zeng, E. J. Barthazy Meier, A. G. Bittermann, F. Gramm, A. Sologubenko
AbstractThe introductory course on Transmission Electron Microscopy (TEM) provides theoretical and hands-on learning for beginners who are interested in using TEM for their Master or PhD thesis. TEM sample preparation techniques are also discussed. During hands-on sessions at different TEM instruments, students will have the opportunity to examine their own samples if time allows.
ObjectiveUnderstanding of
1. the set-up and individual components of a TEM
2. the basics of electron optics and image formation
3. the basics of electron beam – sample interactions
4. the contrast mechanism
5. various sample preparation techniques
Learning how to
1. align and operate a TEM
2. acquire data using different operation modes of a TEM instrument, i.e. Bright-field and Dark-field imaging
3. record electron diffraction patterns and index diffraction patterns
4. interpret TEM data
ContentLectures:
- basics of electron optics and the TEM instrument set-up
- TEM imaging modes and image contrast
- STEM operation mode
- Sample preparation techniques for hard and soft materials

Practicals:
- Demo, practical demonstration of a TEM: instrument components, alignment, etc.
- Hands-on training for students: sample loading, instrument alignment and data acquisition.
- Sample preparation for different types of materials
- Practical work with TEMs
- Demonstration of advanced Transmission Electron Microscopy techniques
Lecture notesLecture notes will be distributed.
Literature- Williams, Carter: Transmission Electron Microscopy, Plenum Press, 1996
- Hawkes, Valdre: Biophysical Electron Microscopy, Academic Press, 1990
- Egerton: Physical Principles of Electron Microscopy: an introduction to TEM, SEM and AEM, Springer Verlag, 2007
Prerequisites / NoticeNo mandatory prerequisites. Please consider the prior attendance to EM Basic lectures (551-1618-00V; 227-0390-00L; 327-0703-00L) as suggested prerequisite.
376-0221-00LMethods and Concepts in Human Systems Neuroscience and Motor Control Restricted registration - show details
Does not take place this semester.
Number of participants limited to 12
W4 credits3P
AbstractThis course provides hands-on experience with measurement and analysis methods relevant for Humans Systems Neuroscience and Motor control (nerve/brain stimulation, EMG, EEG, psycho-physical paradigms etc). Students read scientific material, set up experiments, perform measurements in the lab, analyse data, apply statistics and write short reports or essays.
ObjectiveThis course will prepare students for experimental work as it is typically done during the master thesis. The goal is to gain hands-on experience with measurement and analysis methods relevant for Humans Systems Neuroscience and Motor control (ifor example peripheral nerve stimulation, electrical and magnetic brain stimulation, EMG, EEG, psycho-physical paradigms etc). Students will learn how to perform small scientific projects in this area. Students will work individually or in small groups and solve scientific problems which require them to perform measurements in human participants, extract relevant readouts from the data, apply appropriate statistics and interpret the results. They will also be required to write small essays and reports and they will get feedback on their writing throughout the course.
Prerequisites / NoticeStudents are required to have successfully completed the course "Neural control of movement and motor learning" and to have basic knowledge of applied statistics.
376-0816-00LApplied Human Research Project Management Restricted registration - show details
Number of participants limited to 30.
W4 credits3GC. Lustenberger, M. Altermatt
AbstractThis course equips the students with several key principles such as good clinical practice, ethical study requirements, reproducible data management and effective oral, graphical, and written communication to design and manage good quality, ethically sound human research studies and represents a 101-toolkit of transferable research management skills/digital tools.
ObjectiveThe overall goal of this course is to integrate transferable principles of human research project management into preparation, conduction, and dissemination of own/future research projects and beyond. The following objectives are part of this course:
• Create/select well-founded research hypothesis and study designs for a specific research topic
• Apply universal good clinical practice guidelines in future research projects
• Integrate well-documented data management and open science principles into future research projects
• Integrate principles of effective communication in speaking, writing and graphical illustrations of future research idea/output
ContentThe course will cover the following topics:
• Introduction to different study designs and ethical requirements thereof in Switzerland
• Introduction to literature search and searching platforms
• How to collect and sort publications/ keep up to date on research topic
• Inputs on critically evaluating papers
• How to pre-define study requirements to "future-proof" the research (hypothesis, sample size definition, pre-registration)
• Correct conduction of fundamental human research procedures (e.g., screening, consent process, CRF) and identification/prevention of deviations and emergencies (e.g., SAE/AE, protocol violation, research misconduct)
• Principles of reproducible and integral study documentation and data management (e.g., definition of source files, SOP/WI, Master Trial File, metafiles)
• FAIR principles and open science
• Design principles and free digital tools for graphical illustrations
• Effective summarizing of research output/topic in an abstract and pitch presentation
376-1151-00LTranslation of Basic Research Findings from Genetics and Molecular Mechanisms of Aging Restricted registration - show details
Number of participants limited to 30.
W3 credits2VC. Ewald
AbstractRecently, several start-up companies are aiming to translate basic molecular findings into new drugs/therapeutic interventions to slow aging or post-pone age-related diseases (e.g., Google founded Calico or Craig Venter's Human Longevity, Inc.). This course will teach students the basic skill sets to formulate their own ideas, design experiments to test them and explains the next steps to translat
ObjectiveThe overall goal of this course is to be able to analyse current therapeutic interventions to identify an unmet need in molecular biology of aging and apply scientific thinking to discover new mechanisms that could be used as a novel therapeutic intervention.
Learning objectives include:
1. Evaluate the current problem of our aging population, the impact of age-dependent diseases and current strategies to prevent these age-dependent diseases.
2. Analyse/compare current molecular/genetic strategies that address these aging problems.
3. Analyse case studies about biotech companies in the aging sector. Apply the scientific methods to formulate basic research questions to address these problems.
4. Generate own hypotheses (educated guess/idea), design experiments to test them, and map out the next steps to translate them.
ContentOverview of aging and age-related diseases. Key discoveries in molecular biology of aging. Case studies of biotech companies addressing age-related complications. Brief introduction from bench to bedside with focus on start-up companies.
Prerequisites / NoticeNo compulsory prerequisites, but student should have basic knowledge about genetics and molecular biology.
376-1177-00LHuman Factors IW3 credits2VM. Menozzi Jäckli, R. Huang, M. Siegrist
AbstractStrategies of human-system-interaction, individual needs, physical & mental abilities, and system properties are key factors affecting the quality and performance in interaction processes. In the lecture, factors are investigated by basic scientific approaches. Discussed topics are important for optimizing people's health, well-being, and satisfaction as well as the overall system performance.
ObjectiveThe goal of the lecture is to empower students in better understanding the applied theories, principles, and methods in various applications. Students are expected to learn about how to enable an efficient and qualitatively high standing interaction between human and the environment, considering costs, benefits, health, and safety as well. Thus, an ergonomic design and evaluation process of products, tasks, and environments may be promoted in different disciplines. The goal is achieved in addressing a broad variety of topics and embedding the discussion in macroscopic factors such as the behavior of consumers and objectives of economy.
Content- Physiological, physical, and cognitive factors in sensation, perception, and action
- Body spaces and functional anthropometry, Digital Human Models
- Experimental techniques in assessing human performance, well-being, and comfort
- Usability engineering in system designs, product development, and innovation
- Human information processing and biological cybernetics
- Interaction among consumers, environments, behavior, and tasks
Literature- Gavriel Salvendy, Handbook of Human Factors and Ergonomics, 4th edition (2012), is available on NEBIS as electronic version and for free to ETH students
- Further textbooks are introduced in the lecture
- Brouchures, checklists, key articles etc. are uploaded in ILIAS
376-1179-00LApplications of Cybernetics in ErgonomicsW1 credit1UM. Menozzi Jäckli, Y.‑Y. Hedinger Huang, R. Huang
AbstractCybernetics systems have been studied and applied in various research fields, such as for applications in ergonomics. Topics discussed in this lecture (man-machine-interaction, performance in multi-modal interactions, quantification in gestalt principles for the use in product development, information processing) are deepened with exercises conducted at our labs.
ObjectiveTo learn and practice cybernetics principles in interface designs and product development.
Content- Fitt's law applied in manipulation tasks
- Hick-Hyman law applied in design of the driver assistance systems - Vigilance applied in quality inspection
- Accommodation/vergence crosslink function
- Cross-link models in neurobiology- the ocular motor control system
- Human performance in optimization of production lines
LiteratureGavriel Salvendy, Handbook of Human Factors and Ergonomics, 4th edition (2012)
376-1305-00LDevelopment of the Nervous System (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: BIO344

Mind the enrolment deadlines at UZH:
Link
W3 credits2VUniversity lecturers
AbstractThe lecture will cover molecular and cellular processes underlying the development of the nervous system (neurogenesis, cell death, cell migration and differentiation, axon guidance and synapse formation). The importance of these processes in the context of developmental diseases is discussed.
ObjectiveOn successful completion of the module the student should be able to
- relate structure and function of the nervous system to its development - apply principles of molecular, cellular, and developmental biology to the development of the nervous system
- identify key steps in development underlying neurological syndromes and diseases

Key skills
On successful completion of the module the student should be able to
- interpret and critically evaluate original research reports
- apply knowledge and relate experimental approaches from molecular, cellular and developmental biology to the developing nervous system.
ContentThe lecture will cover molecular and cellular processes underlying the development of the nervous system. After an introduction to structure and function of the nervous system, we will discuss neurogenesis, cell death, cell migration and differentiation, axon guidance and synapse formation. The importance of these processes in the context of developmental diseases will be discussed.
Lecture notesMust be downloaded from OLAT: Link
as BIO344
LiteratureThe lecture requires reading of book chapters, handouts and original scientific papers. Further information will be given in the individual lectures and are mentioned on OLAT.
Prerequisites / NoticeBIO142 Developmental Biology, BIO143 Neurobiology
376-1305-01LNeural 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
W3 credits2VG. Schratt, J. Bohacek, R. Fiore, R. Polania, W. von der Behrens, J. Winterer, further lecturers
AbstractThe course covers the structure, plasticity and regeneration 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.
ObjectiveThe aim is to give a deepened insight into the structure, plasticity and regeneration of the nervous system based on molecular, cellular and biochemical approaches.
ContentThe main focus is on the structure, plasticity and regeneration of the NS: biology of the adult nervous system; structural plasticity of the adult nervous system, regeneration and repair: networks and nerve fibers, regeneration, pathological loss of cells.
LiteratureThe 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 / OLAT.
376-1414-00LCurrent Topics in Brain Research (HS)W1 credit1.5KI. Mansuy, further lecturers
AbstractDifferent national and international scientific guests are invited to present and discuss their actual scientific results.
ObjectiveTo exchange scientific knowledge and data and to promote communication and collaborations among researchers.
For students: Critical discussion of current research. Students aiming at getting a credit point for this colloquium choose one topic and write a critical essay on the presented research topic.
ContentDifferent scientific guests working in the field of molecular cognition, neurochemistry, neuromorphology and neurophysiology present their latest scientific results.
Lecture notesno handout
Literatureno literature
Prerequisites / NoticeSome of the seminars will be shared with the Institute of Neuroinformatics (INI) of UZH.
376-1504-00LPhysical Human Robot Interaction (pHRI) Restricted registration - show details W4 credits2V + 2UO. Lambercy
AbstractThis course focuses on the emerging, interdisciplinary field of physical human-robot interaction, bringing together themes from robotics, real-time control, human factors, haptics, virtual environments, interaction design and other fields to enable the development of human-oriented robotic systems.
ObjectiveThe objective of this course is to give an introduction to the fundamentals of physical human robot interaction, through lectures on the underlying theoretical/mechatronics aspects and application fields, in combination with a hands-on lab tutorial. The course will guide students through the design and evaluation process of such systems.

By the end of this course, you should understand the critical elements in human-robot interactions - both in terms of engineering and human factors - and use these to evaluate and de- sign safe and efficient assistive and rehabilitative robotic systems. Specifically, you should be able to:

1) identify critical human factors in physical human-robot interaction and use these to derive design requirements;
2) compare and select mechatronic components that optimally fulfill the defined design requirements;
3) derive a model of the device dynamics to guide and optimize the selection and integration of selected components into a functional system;
4) design control hardware and software and implement and test human-interactive control strategies on the physical setup;
5) characterize and optimize such systems using both engineering and psychophysical evaluation metrics;
6) investigate and optimize one aspect of the physical setup and convey and defend the gained insights in a technical presentation.
ContentThis course provides an introduction to fundamental aspects of physical human-robot interaction. After an overview of human haptic, visual and auditory sensing, neurophysiology and psychophysics, principles of human-robot interaction systems (kinematics, mechanical transmissions, robot sensors and actuators used in these systems) will be introduced. Throughout the course, students will gain knowledge of interaction control strategies including impedance/admittance and force control, haptic rendering basics and issues in device design for humans such as transparency and stability analysis, safety hardware and procedures. The course is organized into lectures that aim to bring students up to speed with the basics of these systems, readings on classical and current topics in physical human-robot interaction, laboratory sessions and lab visits.
Students will attend periodic laboratory sessions where they will implement the theoretical aspects learned during the lectures. Here the salient features of haptic device design will be identified and theoretical aspects will be implemented in a haptic system based on the haptic paddle (Link), by creating simple dynamic haptic virtual environments and understanding the performance limitations and causes of instabilities (direct/virtual coupling, friction, damping, time delays, sampling rate, sensor quantization, etc.) during rendering of different mechanical properties.
Lecture notesWill be distributed on Moodle before the lectures.
LiteratureAbbott, J. and Okamura, A. (2005). Effects of position quantization and sampling rate on virtual-wall passivity. Robotics, IEEE Transactions on, 21(5):952 - 964.
Adams, R. and Hannaford, B. (1999). Stable haptic interaction with virtual environments. Robotics and Automation, IEEE Transactions on, 15(3):465 - 474.
Buerger, S. and Hogan, N. (2007). Complementary stability and loop shaping for improved human-robot interaction. Robotics, IEEE Transactions on, 23(2):232 - 244.
Burdea, G. and Brooks, F. (1996). Force and touch feedback for virtual reality. John Wiley & Sons New York NY.
Colgate, J. and Brown, J. (1994). Factors affecting the z-width of a haptic display. In Robotics and Automation, 1994. Proceedings., 1994 IEEE International Conference on, pages 3205 -3210 vol. 4.
Diolaiti, N., Niemeyer, G., Barbagli, F., and Salisbury, J. (2006). Stability of haptic rendering: Discretization, quantization, time delay, and coulomb effects. Robotics, IEEE Transactions on, 22(2):256 - 268.
Gillespie, R. and Cutkosky, M. (1996). Stable user-specific haptic rendering of the virtual wall. In Proceedings of the ASME International Mechanical Engineering Congress and Exhibition, volume 58, pages 397 - 406.
Hannaford, B. and Ryu, J.-H. (2002). Time-domain passivity control of haptic interfaces. Robotics and Automation, IEEE Transactions on, 18(1):1 - 10.
Hashtrudi-Zaad, K. and Salcudean, S. (2001). Analysis of control architectures for teleoperation systems with impedance/admittance master and slave manipulators. The International Journal of Robotics Research, 20(6):419.
Hayward, V. and Astley, O. (1996). Performance measures for haptic interfaces. In ROBOTICS RESEARCH-INTERNATIONAL SYMPOSIUM, volume 7, pages 195-206. Citeseer.
Hayward, V. and Maclean, K. (2007). Do it yourself haptics: part i. Robotics Automation Magazine, IEEE, 14(4):88 - 104.
Leskovsky, P., Harders, M., and Szeekely, G. (2006). Assessing the fidelity of haptically rendered deformable objects. In Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium on, pages 19 - 25.
MacLean, K. and Hayward, V. (2008). Do it yourself haptics: Part ii [tutorial]. Robotics Automation Magazine, IEEE, 15(1):104 - 119.
Mahvash, M. and Hayward, V. (2003). Passivity-based high-fidelity haptic rendering of contact. In Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on, volume 3, pages 3722 - 3728.
Mehling, J., Colgate, J., and Peshkin, M. (2005). Increasing the impedance range of a haptic display by adding electrical damping. In Eurohaptics Conference, 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2005. World Haptics 2005. First Joint, pages 257 - 262.
Okamura, A., Richard, C., and Cutkosky, M. (2002). Feeling is believing: Using a force-feedback joystick to teach dynamic systems. JOURNAL OF ENGINEERING EDUCATION-WASHINGTON, 91(3):345 - 350.
O'Malley, M. and Goldfarb, M. (2004). The effect of virtual surface stiffness on the haptic perception of detail. Mechatronics, IEEE/ASME Transactions on, 9(2):448 - 454.
Richard, C. and Cutkosky, M. (2000). The effects of real and computer generated friction on human performance in a targeting task. In Proceedings of the ASME Dynamic Systems and Control Division, volume 69, page 2.
Salisbury, K., Conti, F., and Barbagli, F. (2004). Haptic rendering: Introductory concepts. Computer Graphics and Applications, IEEE, 24(2):24 - 32.
Weir, D., Colgate, J., and Peshkin, M. (2008). Measuring and increasing z-width with active electrical damping. In Haptic interfaces for virtual environment and teleoperator systems, 2008. haptics 2008. symposium on, pages 169 - 175.
Yasrebi, N. and Constantinescu, D. (2008). Extending the z-width of a haptic device using acceleration feedback. Haptics: Perception, Devices and Scenarios, pages 157-162.
Prerequisites / NoticeNotice:
The registration is limited to 26 students
There are 4 credit points for this lecture.
The lecture will be held in English.
The students are expected to have basic control knowledge from previous classes.
Link
376-1661-00LEthics of Life Sciences and Biotechnology Restricted registration - show details
Number of participants limited to 100
W3 credits2VA. Blasimme, E. Vayena
AbstractThis semester course enables students to recognize, anticipate and address ethical issues in the domain of health sciences and their technological application. The students will acquire the necessary theoretical and analytic resources to develop critical thinking skills in the field of applied ethics and will practice how to use such resources to address concrete ethical issues in health sciences
ObjectiveThis course is tailored to students who want to become familiar with the analysis of ethical issues in all the different domains of life sciences and biotechnology. The course aims at equipping students with the necessary knowledge and analytic skills to understand, discuss and address the ethical aspects of science and technology in the domain of human health. The specific learning objectives of this course are:

A. Identify ethical issues in in life sciences and biotechnology.
B. Analyze and critically discuss ethical issues in life sciences and biotechnology.
C. Become aware of relevant legal and public policy frameworks.
D. Distinguish different ethical approaches and argumentative strategies in applied ethics.
E. Recognize how ethical issues relate to different accounts of technology and innovation.
F. Develop a personal and critical attitude towards the ethical aspects of life sciences and their technological application.
G. Autonomously anticipate ethical issues.
H. Propose and communicate solutions to ethical challenges and dilemmas.
ContentThe course starts off with an introductory lecture on ethics as a discipline and an overview of the most relevant approaches in the domain of applied ethics. The students will also be introduced to current theoretical accounts of technology and will start to appreciate the relevance of ethics especially with respect to new and emerging technologies. Usable analytic tools will also be provided, thus enabling the students to engage with the discipline in a practical way from the very onset of the semester.
The course will continue with thematic sessions covering a broad variety of topics all of which are relevant to the different study tracks offered by the department. In particular, the course will cover the following domains: digital health technologies and medical AI; food, nutrition and healthy longevity; biomedical engineering; genetics; neuroscience and Neurotechnologies; medical robotics; disability and rehabilitation; environmental ethics. The course will also include sessions on cross-cutting ethically relevant aspects of health sciences and technologies, namely: access to innovation, translational research, and the relation between science and public policy.
All the topics of the course will be illustrated and interactively discussed through many case studies, offering the students the opportunity to prepare and present them, and to use them in individual as well as group exercises. Throughout the course, the students will have multiple opportunities to experiment with ethical argumentation and to practice their evolving skills.
376-1723-00LBig Data Analysis in Biomedical Research Restricted registration - show details
Number of participants limited to 20.
W4 credits2V + 2UE. Araldi, M. Ristow
AbstractBiomedical datasets are increasing in size and complexity, and discoveries arising from their analysis have important implications in human health and biotechnological advances. While the potential of biomedical dataset analysis is considerable, preclinical researchers often lack the computational tools to analyze them. This course will provide the basis of data analysis of large biomedical data
ObjectiveThis course aims to provide practical tools to analyze large biomedical datasets, and it is tailored towards experimental researchers in the life sciences with minimal prior programming experience, but with a strong interest in exploring big data to solve own research problems. Through theoretical classes, practical demonstrations, in class exercises and homework, the participants will master computational methods to independently manipulate large datasets, effectively visualize big data, and analyze it with appropriate statistical tools and machine learning approaches. For the final assessment, students will conduct an independent data analysis project based on a biomedical problem of their choosing and using publicly available population-based biomedical datasets.
ContentWhile learning the programming skills needed to manipulate and visualize the data, participants will learn the statistical and modeling approaches for big data analysis. The course will cover:
•Basis of Python programming and UNIX;
•High performance computing;
•Manipulation and cleaning of large datasets with Pandas;
•Visualization tools (Matplotlib, Seaborn);
•Machine learning and numerical libraries (SciPy, NumPy, Statsmodels, Scikit-Learn).
•Statistical analysis and modeling of big data, and applications to biomedical datasets (statistical learning, distributions, linear and logistic regressions, principal component analysis, clustering, classification, time series analysis, tree-based methods, predictive models).
Prerequisites / NoticeBasic understanding of mathematics and statistics, as taught in basic courses at the Bachelor`s level.
551-0309-00LConcepts in Modern Genetics
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module BIO348 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
W6 credits4VY. Barral, D. Bopp, A. Hajnal, O. Voinnet
AbstractConcepts of modern genetics and genomics, including principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
ObjectiveThis course focuses on the concepts of classical and modern genetics and genomics.
ContentThe topics include principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
Lecture notesScripts and additional material will be provided during the semester.
551-0317-00LImmunology IW3 credits2VM. Kopf, A. Oxenius
AbstractIntroduction into structural and functional aspects of the immune system.
Basic knowledge of the mechanisms and the regulation of an immune response.
ObjectiveIntroduction into structural and functional aspects of the immune system.
Basic knowledge of the mechanisms and the regulation of an immune response.
Content- Introduction and historical background
- Innate and adaptive immunity, Cells and organs of the immune system
- B cells and antibodies
- Generation of diversity
- Antigen presentation and Major Histoincompatibility (MHC) antigens
- Thymus and T cell selection
- Autoimmunity
- Cytotoxic T cells and NK cells
- Th1 and Th2 cells, regulatory T cells
- Allergies
- Hypersensitivities
- Vaccines, immune-therapeutic interventions
Lecture notesElectronic access to the documentation will be provided. The link can be found at "Lernmaterialien"
Literature- Kuby, Immunology, 9th edition, Freemen + Co., New York, 2020
Prerequisites / NoticeFor D-BIOL students Immunology I (WS) and Immunology II (SS) will be examined as one learning entity in a "Sessionsprüfung". All other students write separate exams for Immunology I and Immunology II. All exams (combined exam Immunology I and II, individual exams) are offered in each exam session.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesfostered
Decision-makingassessed
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityassessed
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingfostered
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection assessed
Self-direction and Self-management assessed
551-0319-00LCellular Biochemistry (Part I)W3 credits2VU. Kutay, G. Neurohr, M. Peter, I. Zemp
AbstractConcepts and molecular mechanisms underlying the biochemistry of the cell, providing advanced insights into structure, function and regulation of individual cell components. Particular emphasis will be put on the spatial and temporal integration of different molecules and signaling pathways into global cellular processes such as intracellular transport, cell division & growth, and cell migration.
ObjectiveThe full-year course (551-0319-00 & 551-0320-00) focuses on the molecular mechanisms and concepts underlying the biochemistry of cellular physiology, investigating how these processes are integrated to carry out highly coordinated cellular functions. The molecular characterisation of complex cellular functions requires a combination of approaches such as biochemistry, but also cell biology and genetics. This course is therefore the occasion to discuss these techniques and their integration in modern cellular biochemistry.
The students will be able to describe the structural and functional details of individual cell components, and the spatial and temporal regulation of their interactions. In particular, they will learn to explain the integration of different molecules and signaling pathways into complex and highly dynamic cellular processes such as intracellular transport, cytoskeletal rearrangements, cell motility, cell division and cell growth. In addition, they will be able to illustrate the relevance of particular signaling pathways for cellular pathologies such as cancer.
ContentStructural and functional details of individual cell components, regulation of their interactions, and various aspects of the regulation and compartmentalisation of biochemical processes.
Topics include: biophysical and electrical properties of membranes; viral membranes; structural and functional insights into intracellular transport and targeting; vesicular trafficking and phagocytosis; post-transcriptional regulation of gene expression.
Lecture notesScripts and additional material will be provided during the semester. Please contact Dr. Alicia Smith for assistance with the learning materials. (Link)
LiteratureRecommended supplementary literature (review articles and selected primary literature) will be provided during the course.
Prerequisites / NoticeTo attend this course the students must have a solid basic knowledge in chemistry, biochemistry and general biology. The course will be taught in English.
752-4009-00LMolecular Biology of Foodborne PathogensW3 credits2VM. Loessner, M. Schmelcher, M. Schuppler, E. Slack
AbstractThe course offers detailed information on selected foodborne pathogens and toxin producing organisms; the focus lies on relevant molecular biological aspects of pathogenicity and virulence, as well as on the occurrence and survival of these organisms in foods.
ObjectiveDetailed and current status of research and insights into the molecular basis of foodborne diseases, with focus on interactions of the microorganism or the toxins they produce with the human system. Understanding the relationship between specific types of food and the associated pathogens and microbial risks. Another focus lies on the currently available methods and techniques useful for the various purposes, i.e., detection, differentiation (typing), and antimicrobial agents.
ContentMolecular biology of infectious foodborne pathogens (Listeria, E. coli, Campylobacter, Salmonella, etc) and toxin-producing organisms (Bacillus, Clostridium, Staphylococcus). How and under which conditions will toxins and virulence factors be produced, and how do they work? How is the interaction between the human host and the microbial pathogen? What are the roles of food and the environment ? What can be done to interfere with the potential risks? Which methods are best suited for what approach? Last, but not least, the role of bacteriophages in microbial pathogenicity will be highlighted, in addition to various applications of bacteriophage for both diagnostics and antimicrobial intervention.
Lecture notesElectronic copies of the presentation slides (PDF) and additional material will be made available for download to registered students.
LiteratureRecommendations will be given in the first lecture
Prerequisites / NoticeLectures (2 hours) will be held as a single session of approximately 60+ minutes (10:15 until approx. 11:15 h), without a break !
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