Suchergebnis: Katalogdaten im Herbstsemester 2014
|Biomedical Engineering Master|
|Master-Studium gemäss Studienreglement 2013|
| Wahlfächer der Vertiefung|
Diese Fächer sind für die Vertiefung in Bioelectronics besonders empfohlen. Bei abweichender Fächerwahl konsultieren Sie bitte den Track Adviser.
|636-0003-00L||Biological Engineering and Biotechnology||W||6 KP||3G||M. Fussenegger|
|Kurzbeschreibung||Biological Engineering and Biotechnology will cover the latest biotechnological advances as well as their industrial implementation to engineer mammalian cells for use in human therapy. This lecture will provide forefront insights into key scientific aspects and the main points in industrial decision-making to bring a therapeutic from target to market.|
|Lernziel||1. Insight Into The Mammalian Cell Cycle. Cycling, The Balance Between Proliferation and Cancer - Implications For Biopharmaceutical Manufacturing. 2. The Licence To Kill. Apoptosis Regulatory Networks - Engineering of Survival Pathways To Increase Robustness of Production Cell Lines. 3. Everything Under Control I. Regulated Transgene Expression in Mammalian Cells - Facts and Future. 4. Secretion Engineering. The Traffic Jam getting out of the Cell. 5. From Target To Market. An Antibody's Journey From Cell Culture to The Clinics. 6. Biology and Malign Applications. Do Life Sciences Enable the Development of Biological Weapons? 7. Functional Food. Enjoy your Meal! 8. Industrial Genomics. Getting a Systems View on Nutrition and Health - An Industrial Perspective. 9. IP Management - Food Technology. Protecting Your Knowledge For Business. 10. Biopharmaceutical Manufacturing I. Introduction to Process Development. 11. Biopharmaceutical Manufacturing II. Up- stream Development. 12. Biopharmaceutical Manufacturing III. Downstream Development. 13. Biopharmaceutical Manufacturing IV. Pharma Development.|
|Skript||Handsout during the course.|
|227-0945-00L||Cell and Molecular Biology for Engineers||W||6 KP||4G||C. Frei|
|Kurzbeschreibung||The course gives an introduction into cellular and molecular biology, specifically for students with a background in engineering. The focus will be on the basic organization of eukaryotic cells, molecular mechanisms and cellular functions. Textbook knowledge will be combined with results from recent research and technological innovations in biology.|
|Lernziel||After completing this course, engineering students will be able to apply their previous training in the quantitative and physical sciences to modern biology. Students will also learn the principles how biological models are established, and how these models can be tested.|
|Inhalt||Lectures will include the following topics: DNA, chromosomes, RNA, protein, genetics, gene expression, membrane structure and function, vesicular traffic, cellular communication, energy conversion, cytoskeleton, cell cycle, cellular growth, apoptosis, autophagy, cancer, development and stem cells.|
In addition, three journal clubs will be held, where one/two publictions will be discussed. For each journal club, students (alone or in groups of up to three students) have to write a summary and discussion of the publication. These written documents will be graded, and count as 25% for the final grade.
|Skript||Scripts of all lectures will be available.|
|Literatur||"Molecular Biology of the Cell" (5th edition) by Alberts, Johnson, Lewis, Raff, Roberts, and Walter.|
| Kernfächer der Vertiefung|
Während des Studiums müssen mindestens 12 KP aus Kernfächern einer Vertiefung (Track) erreicht werden.
|227-0385-00L||Biomedical Imaging||W||4 KP||3G||S. Kozerke, U. Moser, M. Rudin|
|Kurzbeschreibung||Introduction and analysis of medical imaging technology including X-ray procedures, computed tomography, nuclear imaging techniques using single photon and positron emission tomography, magnetic resonance imaging and ultrasound imaging techniques.|
|Lernziel||Understand the physical and technical principles underlying X-ray imaging, computed tomography, single photon and positron emission tomography, magnetic resonance imaging, ultrasound and Doppler imaging techniques. Develop the mathematical framework to describe image encoding/decoding, point-spread function/modular transfer function, signal-to-noise ratio, contrast behavior for each of the methods.|
|Inhalt||X-ray imaging |
Single photon emission tomography
Positron emission tomography
Magnetic resonance imaging
|Skript||Lecture notes and handouts: Biomedical Imaging|
|Literatur||Introduction to Medical Imaging: Physics, Engineering and Clinical Applications by Andrew Webb, Nadine Barrie Smith, |
Cambridge University Press
|227-0386-00L||Biomedical Engineering||W||4 KP||3G||J. Vörös, S. J. Ferguson, S. Kozerke, U. Moser, M. Rudin, M. P. Wolf, M. Zenobi-Wong|
|Kurzbeschreibung||Introduction into selected topics of biomedical engineering as well as their relationship with physics and physiology. The focus is on learning the concepts that govern common medical instruments and the most important organs from an engineering point of view. In addition, the most recent achievements and trends of the field of biomedical engineering are also outlined.|
|Lernziel||Introduction into selected topics of biomedical engineering as well as their relationship with physics and physiology. The course provides an overview of the various topics of the different tracks of the biomedical engineering master course and helps orienting the students in selecting their specialized classes and project locations.|
|Inhalt||Introduction into neuro- and electrophysiology. Functional analysis of peripheral nerves, muscles, sensory organs and the central nervous system. Electrograms, evoked potentials. Audiometry, optometry. Functional electrostimulation: Cardiac pacemakers. Function of the heart and the circulatory system, transport and exchange of substances in the human body, pharmacokinetics. Endoscopy, medical television technology. Lithotripsy. Electrical Safety. Orthopaedic biomechanics. Lung function. Bioinformatics and Bioelectronics. Biomaterials. Biosensors. Microcirculation.Metabolism. |
Practical and theoretical exercises in small groups in the laboratory.
|Skript||Introduction to Biomedical Engineering|
by Enderle, Banchard, and Bronzino
|227-0447-00L||Image Analysis and Computer Vision||W||6 KP||3V + 1U||G. Székely, O. Göksel, L. Van Gool|
|Kurzbeschreibung||Light and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation and deformable shape matching. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition.|
|Lernziel||Overview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.|
|Inhalt||The first part of the course starts off from 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 it is investigated how the parameters of the electromagnetic waves are related to our perception. Also the interaction of light with matter is considered. The most important hardware components of technical vision systems, such as cameras, optical devices and illumination sources are discussed. The course then turns to the steps that are necessary to arrive at the discrete images that serve as input to algorithms. The next part describes necessary preprocessing steps of image analysis, 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 depth as two important examples. The estimation of image velocities (optical flow) will get due attention and methods for object tracking will be presented. Several techniques are discussed to extract three-dimensional information about objects and scenes. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed.|
|Skript||Course material Script, computer demonstrations, exercises and problem solutions|
|Voraussetzungen / Besonderes||Prerequisites: |
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Linux and C.
The course language is English.
|227-0965-00L||Micro and Nano-Tomography of Biological Tissues||W||4 KP||3G||M. Stampanoni, K. S. Mader|
|Kurzbeschreibung||Einführung in die physikalischen und technischen Grundkenntnisse der tomographischen Röntgenmikroskopie. Verschiedene Röntgenbasierten-Abbildungsmechanismen (Absorptions-, Phasen- und Dunkelfeld-Kontrast) werden erklärt und deren Einsatz in der aktuellen Forschung vorgestellt, insbesondere in der Biologie. Die quantitative Auswertung tomographische Datensätzen wird ausführlich beigebracht.|
|Lernziel||Einführung in die Grundlagen der Röntgentomographie auf der Mikrometer- und Nanometerskala, sowie in die entsprechenden Bildbearbeitungs- und Quantifizierungsmethoden, unter besonderer Berücksichtigung von biologischen Anwendungen.|
|Inhalt||Synchrotron basierte Röntgenmikro- und Nanotomographie ist heutzutage eine leistungsfähige Technik für die hochaufgelösten zerstörungsfreien Untersuchungen einer Vielfalt von Materialien. Die aussergewöhnlichen Stärke und Kohärenz der Strahlung einer Synchrotronquelle der dritten Generation erlauben quantitative drei-dimensionale Aufnahmen auf der Mikro- und Nanometerskala und erweitern die klassischen Absorption-basierten Verfahrensweisen auf die kontrastreicheren kantenverstärkten und phasenempfindlichen Methoden, die für die Analyse von biologischen Proben besonders geeignet sind.|
Die Vorlesung umfasst eine allgemeine Einführung in die Grundsätze der Röntgentomographie, von der Bildentstehung bis zur 3D Bildrekonstruktion. Sie liefert die physikalischen und technischen Grundkentnisse über die bildgebenden Synchrotronstrahllinien, vertieft die neusten Phasenkontrastmethoden und beschreibt die ersten Anwendungen nanotomographischer Röntgenuntersuchungen.
Schliesslich liefert der Kurs den notwendigen Hintergrund, um die quantitative Auswertung tomographischer Daten zu verstehen, von der grundlegenden Bildanalyse bis zur komplexen morphometrischen Berechnung und zur 3D-Visualisierung, unter besonderer Berücksichtigung von biomedizinischen Anwendungen.
|Literatur||Wird in der Vorlesung angegeben.|
| Wahlfächer der Vertiefung|
Diese Fächer sind für die Vertiefung in Bioimaging besonders empfohlen. Bei abweichender Fächerwahl konsultieren Sie bitte den Track Adviser.
|227-0389-00L||Advanced Topics in Magnetic Resonance Imaging||Z||0 KP||1V||K. P. Prüssmann|
|Kurzbeschreibung||Diese Vorlesung richtet sich an Masterstudierende und Doktorierende mit vertieftem Interesse an biomedizinischer Bildgebung. Sie behandelt fortgeschrittene Aspekte der Magnetresonanzbildgebung in zweijährigem Turnus, darunter die Elektrodynamik der Signaldetektion und des Signalrauschens, Bildrekonsntruktion, Radiofrequenzpulse, Pulsschemata, sowie fortgeschrittene Kontrastmechanismen.|
|227-0391-00L||Medical Image Analysis||W||3 KP||2G||P. C. Cattin, M. A. Reyes Aguirre|
|Kurzbeschreibung||It is the objective of this lecture to introduce the basic concepts used |
in Medical Image Analysis. In particular the lecture focuses on shape
representation schemes, segmentation techniques, and the various image registration methods commonly used in Medical Image Analysis applications.
|Lernziel||This lecture aims to give an overview of the basic concepts of Medical Image Analysis and its application areas.|
|Voraussetzungen / Besonderes||Basic knowledge of computer vision would be helpful.|
|227-0963-00L||Statistical Parametric Mapping (SPM)||W||2 KP||1V||K. Stephan|
|Kurzbeschreibung||This course provides a comprehensive coverage of state-of-the-art statistical methods for fMRI data analysis, focusing on tools provided by the open source software package SPM|
|Lernziel||Knowledge of modern statistical methods for fMRI data analysis|
|Inhalt||Spatial preprocessing & physiological noise correction|
Mass-univariate & multivariate analyses of fMRI
'Resting state' fMRI
Bayesian analysis methods
Effective connectivity analyses (Dynamic Causal Modeling)
|227-0967-00L||Computational Neuroimaging Clinic||W||3 KP||2V||K. Stephan|
|Kurzbeschreibung||This seminar teaches problem solving skills for the design and analysis of neuroimaging data (fMRI, EEG). It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich. Examples may include mass-univariate and multivariate analyses of fMRI data, dynamic causal modeling of fMRI and EEG data.|
|Lernziel||1. Consolidation of theoretical knowledge (obtained in the 'Methods & models for fMRI data analysis' lecture) in a practical setting.|
2. Acquisition of practical problem solving strategies for computational modeling of neuroimaging data.
|Inhalt||This seminar teaches problem solving skills for the design and analysis of neuroimaging data (fMRI, EEG). It deals with a wide variety of real-life problems that are brought to this meeting from the euroimaging community at Zurich. Examples may include mass-univariate and multivariate analyses of fMRI data, dynamic causal modeling of fMRI and EEG data, or analyses of neuroimaging data on the basis of Bayesian models of behaviour.|
|227-0969-00L||Methods & Models for fMRI Data Analysis||W||3 KP||2V||K. Stephan|
|Kurzbeschreibung||This course teaches methods and models for fMRI data analysis, covering all aspects of statistical parametric mapping (SPM), incl. preprocessing, the general linear model, statistical inference, multiple comparison corrections, event-related designs, and Dynamic Causal Modelling (DCM), a Bayesian framework for identification of nonlinear neuronal systems from neurophysiological data.|
|Lernziel||To obtain in-depth knowledge of the theoretical foundations of SPM|
and DCM and of their application to empirical fMRI data.
|Inhalt||This course teaches state-of-the-art methods and models for fMRI data analysis. It covers all aspects of statistical parametric mapping (SPM), incl. preprocessing, the general linear model, frequentist and Bayesian inference, multiple comparison corrections, and event-related designs, and Dynamic Causal Modelling (DCM), a Bayesian framework for identification of nonlinear neuronal systems from neurophysiological data. A particular emphasis of the course will be on methodological questions arising in the context of neuroeconomic and clinical studies.|
|227-0971-00L||Computational Psychiatry||W||3 KP||2S||K. Stephan|
|Kurzbeschreibung||Current methods and concepts for deciphering mechanisms of maladaptive behaviour, such as aberrant learning and decision-making in healthy individuals and psychiatric patients.The key goal is to connect methodological training with biological and clinical knowledge about the phenomenology and pathophysiology of psychiatric and neurological diseases.|
|Lernziel||To understand current concepts about computational and physiological mechanisms of maladaptive behaviour and psychiatric diseases.|
|Inhalt||In this seminar, we discuss current methods and concepts for deciphering mechanisms of maladaptive behaviour, such as aberrant learning and decision-making in healthy individuals and psychiatric patients. The key goal is to connect methodological training (in computational and statistical techniques for analyzing behavioural, fMRI and EEG data) with biological and clinical knowledge about the phenomenology and pathophysiology of psychiatric and neurological diseases. This seminar aims at bridging the gap between mathematical modelers and clinical neuroscientists, enabling more effective communication and joint translational research. To this end, each semester a novel topic is chosen which is examined both from clinical/biological and modeling perspectives.|
|227-2037-00L||Physical Modelling and Simulation||W||5 KP||4G||C. Hafner, J. Smajic|
|Kurzbeschreibung||Physical modelling plays an important role in the analysis and design of new structures, especially for micro and nano devices where fabrication and measurement are difficult. After the fundamentals of electromagnetics, mechanics, and thermodynamics, an introduction to the main concepts and most widely used codes for physical modelling is given and commercial codes are applied.|
|Lernziel||Basic knowledge of the fundamental equations and effects of electromagnetics, mechanics, and thermodynamics. Knowledge of the main concepts of numerical methods for physical modelling and simulation. Ability 1) to select appropriate software, 2) to apply it for solving given problems, 3) to validate the results, 4) to interactively improve the models until sufficiently accurate results are obtained.|
|Inhalt||Since the fabrication and characterization of micro- and nanostructures is difficult, expensive, and time-consuming, numerical modelling drastically reduced the design process. Although many commercial software packages are available, it is important to know the drawbacks and difficulties of the numerical methods behind them and to be able to validate the results obtained with such packages.|
First, an introduction to the fundamental equations and effects of electromagnetics, mechanics, and thermodynamics is given. This is important for understanding the problems to be analyzed and for validating results obtained from software packages. After this, the main concepts of numerical methods and of the most widely used codes for physical modelling are outlined and compared, which is essential for the adequate selection of software for solving given problems. After this, prominent commercial software packages are applied to various types of problems, ranging from electrodynamics to multiphysics. For becoming able to select appropriate software and to validate the results obtained, different commercial software packages will be used and compared during the exercises in form of small projects.
|151-0105-00L||Quantitative Flow Visualization||W||4 KP||2V + 1U||T. Rösgen|
|Kurzbeschreibung||The course provides an introduction to digital image analysis in modern flow diagnostics. Different techniques which are discussed include image velocimetry, laser induced fluorescence, liquid crystal thermography and interferometry. The physical foundations and measurement configurations are explained. Image analysis algorithms are presented in detail and programmed during the exercises.|
|Lernziel||Introduction to modern imaging techniques and post processing algorithms with special emphasis on flow analysis and visualization.|
Understanding of hardware and software requirements and solutions.
Development of basic programming skills for (generic) imaging applications.
|Inhalt||Fundamentals of optics, flow visualization and electronic image acquisition.|
Frequently used mage processing techniques (filtering, correlation processing, FFTs, color space transforms).
Image Velocimetry (tracking, pattern matching, Doppler imaging).
Surface pressure and temperature measurements (fluorescent paints, liquid crystal imaging, infrared thermography).
Laser induced fluorescence.
(Digital) Schlieren techniques, phase contrast imaging, interferometry, phase unwrapping.
Wall shear and heat transfer measurements.
Pattern recognition and feature extraction, proper orthogonal decomposition.
|Voraussetzungen / Besonderes||Prerequisites: Fluiddynamics I, Numerical Mathematics, programming skills. |
Language: German on request.
|376-1279-00L||Virtual Reality in Medicine |
Findet dieses Semester nicht statt.
|W||3 KP||2V||R. Riener|
|Kurzbeschreibung||Virtual Reality has the potential to support medical training and therapy. This lecture will derive the technical principles of multi-modal (audiovisual, haptic, tactile etc.) input devices, displays and rendering techniques. Examples are presented in the fields of surgical training, intra-operative augmentation, and rehabilitation. The lecture is accompanied by practical courses and excursions.|
|Lernziel||Provide theoretical and practical knowledge of new principles and applications of multi-modal simulation and interface technologies in medical education, therapy, and rehabilitation.|
|Inhalt||Virtual Reality has the potential to provide descriptive and practical information for medical training and therapy while relieving the patient and/or the physician. Multi-modal interactions between the user and the virtual environment facilitate the generation of high-fidelity sensory impressions, by using not only visual and auditory modalities, but also kinesthetic, tactile, and even olfactory feedback. On the basis of the existing physiological constraints, this lecture will derive the technical requirements and principles of multi-modal input devices, displays, and rendering techniques. Several examples are presented that are currently being developed or already applied for surgical training, intra-operative augmentation, and rehabilitation. The lecture will be accompanied by several practical courses on graphical and haptic display devices as well as excursions to facilities equipped with large-scale VR equipment. |
Students of higher semesters and PhD students of
- D-HEST, D-MAVT, D-ITET, D-INFK, D-PHYS
- Robotics, Systems and Control Master
- Biomedical Engineering/Movement Science and Sport
- Medical Faculty, University of Zurich
Students of other departments, faculties, courses are also welcome!
|Literatur||Book: Virtual Reality in Medicine. Riener, Robert; Harders, Matthias; 2012 Springer.|
|Voraussetzungen / Besonderes||The course language is English. |
Basic experience in Information Technology and Computer Science will be of advantage
More details will be announced in the lecture.
|151-0605-00L||Nanosystems||W||4 KP||4G||A. Stemmer|
|Kurzbeschreibung||From atoms to molecules to condensed matter: characteristic properties of simple nanosystems and how they evolve when moving towards complex ensembles.|
Intermolecular forces, their macroscopic manifestations, and ways to control such interactions.
Self-assembly and directed assembly of 2D and 3D structures.
Special emphasis on the emerging field of molecular electronic devices.
|Lernziel||Familiarize students with basic science and engineering principles governing the nano domain.|
|Inhalt||The course addresses basic science and engineering principles ruling the nano domain. We particularly work out the links between topics that are traditionally taught separately.|
Special emphasis is placed on the emerging field of molecular electronic devices, their working principles, applications, and how they may be assembled.
Topics are treated in 2 blocks:
(I) From Quantum to Continuum
From atoms to molecules to condensed matter: characteristic properties of simple nanosystems and how they evolve when moving towards complex ensembles.
(II) Interaction Forces on the Micro and Nano Scale
Intermolecular forces, their macroscopic manifestations, and ways to control such interactions.
Self-assembly and directed assembly of 2D and 3D structures.
|Literatur||- Kuhn, Hans; Försterling, H.D.: Principles of Physical Chemistry. Understanding Molecules, Molecular Assemblies, Supramolecular Machines. 1999, Wiley, ISBN: 0-471-95902-2|
- Chen, Gang: Nanoscale Energy Transport and Conversion. 2005, Oxford University Press, ISBN: 978-0-19-515942-4
- Ouisse, Thierry: Electron Transport in Nanostructures and Mesoscopic Devices. 2008, Wiley, ISBN: 978-1-84821-050-9
- Wolf, Edward L.: Nanophysics and Nanotechnology. 2004, Wiley-VCH, ISBN: 3-527-40407-4
- Israelachvili, Jacob N.: Intermolecular and Surface Forces. 2nd ed., 1992, Academic Press,ISBN: 0-12-375181-0
- Evans, D.F.; Wennerstrom, H.: The Colloidal Domain. Where Physics, Chemistry, Biology, and Technology Meet. Advances in Interfacial Engineering Series. 2nd ed., 1999, Wiley, ISBN: 0-471-24247-0
- Hunter, Robert J.: Foundations of Colloid Science. 2nd ed., 2001, Oxford, ISBN: 0-19-850502-7
|Voraussetzungen / Besonderes||Course format:|
Lectures: Thursday 10-12, ML F 36
Students select a paper (list distributed in class) and expand the topic into a Mini-Review that illuminates the particular field beyond the immediate results reported in the paper.
|252-0543-01L||Computer Graphics||W||6 KP||3V + 2U||M. Gross, O. Sorkine Hornung|
|Kurzbeschreibung||This course covers some of the fundamental concepts of computer graphics. The two main parts of the class are image synthesis and geometric modeling.|
|Lernziel||At the end of the course students will be able to design and implement a rendering system based on raytracing. You will study the basic principles of modeling with splines and integrate spline-based representations into a rendering system. In addition we want to stimulate your curiosity to explore the field of computer graphics on your own or in future courses.|
|Inhalt||This course covers some of the fundamental concepts of computer graphics. The two main parts of the class are rendering and modeling. In the first part, we will discuss the basics of photorealistic image synthesis, i.e. how to generate a realistic image from a digital representation of a 3D scene. After introducing raytracing, we will briefly look at the physics of light transport, discuss the rendering equation, and investigate some advanced techniques to enhance the realism of rendered images. The second part will introduce the basics of modeling with curves and surfaces. We will discuss Bezier curves and surfaces, B-Splines and NURBS, and show how they can be used to design complex 3D geometry.|
|Voraussetzungen / Besonderes||Prerequisites:|
|402-0674-00L||Physics in Medical Research: From Atoms to Cells||W||6 KP||2V + 1U||B. K. R. Müller|
|Kurzbeschreibung||Scanning probe and diffraction techniques allow studying activated atomic processes during early stages of epitaxial growth. For quantitative description, rate equation analysis, mean-field nucleation and scaling theories are applied on systems ranging from simple metallic to complex organic materials. The knowledge is expanded to optical and electronic properties as well as to proteins and cells.|
|Lernziel||The lecture series is motivated by an overview covering the skin of the crystals, roughness analysis, contact angle measurements, protein absorption/activity and monocyte behaviour.|
As the first step, real structures on clean surfaces including surface reconstructions and surface relaxations, defects in crystals are presented, before the preparation of clean metallic, semiconducting, oxidic and organic surfaces are introduced.
The atomic processes on surfaces are activated by the increase of the substrate temperature. They can be studied using scanning tunneling microscopy (STM) and atomic force microscopy (AFM). The combination with molecular beam epitaxy (MBE) allows determining the sizes of the critical nuclei and the other activated processes in a hierarchical fashion. The evolution of the surface morphology is characterized by the density and size distribution of the nanostructures that could be quantified by means of the rate equation analysis, the mean-field nucleation theory, as well as the scaling theory. The surface morphology is further characterized by defects and nanostructure's shapes, which are based on the strain relieving mechanisms and kinetic growth processes.
High-resolution electron diffraction is complementary to scanning probe techniques and provides exact mean values. Some phenomena are quantitatively described by the kinematic theory and perfectly understood by means of the Ewald construction. Other phenomena need to be described by the more complex dynamical theory. Electron diffraction is not only associated with elastic scattering but also inelastic excitation mechanisms that reflect the electronic structure of the surfaces studied. Low-energy electrons lead to phonon and high-energy electrons to plasmon excitations. Both effects are perfectly described by dipole and impact scattering.
Thin-films of rather complex organic materials are often quantitatively characterized by photons with a broad range of wavelengths from ultra-violet to infra-red light. Asymmetries and preferential orientations of the (anisotropic) molecules are verified using the optical dichroism and second harmonic generation measurements. These characterization techniques are vital for optimizing the preparation of medical implants and the determination of tissue's anisotropies within the human body.
Cell-surface interactions are related to the cell adhesion and the contractile cellular forces. Physical means have been developed to quantify these interactions. Other physical techniques are introduced in cell biology, namely to count and sort cells, to study cell proliferation and metabolism and to determine the relation between cell morphology and function.
3D scaffolds are important for tissue augmentation and engineering. Design, preparation methods, and characterization of these highly porous 3D microstructures are also presented.
Visiting clinical research in a leading university hospital will show the usefulness of the lecture series.
|227-1033-00L||Neuromorphic Engineering I||W||6 KP||2V + 3U||T. Delbrück, G. Indiveri, S.‑C. Liu|
|Kurzbeschreibung||This course covers analog circuits with emphasis on neuromorphic engineering: MOS transistors in CMOS technology, static circuits, dynamic circuits, systems (silicon neuron, silicon retina, motion circuits) and an introduction to multi-chip systems. The lectures are accompanied by weekly laboratory sessions.|
|Lernziel||Understanding of the characteristics of neuromorphic circuit elements and their interaction in parallel networks.|
|Inhalt||Neuromorphic circuits are inspired by the structure, function and plasticity of biological neurons and neural networks. 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. The high parallelism and connectivity of neuromorphic circuits permit structures with massive feedback without iterative methods and convergence problems and real-time processing networks for high-dimensional signals (e.g. vision). Application domains of neuromorphic circuits include silcon retinas and cochleas, 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, multipliers, power-law circuits, resistive networks, etc.), dynamic circuits (linear and nonlinear filters, adaptive circuits), systems (silicon neuron, silicon retina, motion circuits) and an introduction to multi-chip systems. The lectures are accompanied by weekly laboratory sessions on the characterization of neuromorphic circuits, from elementary devices to systems.|
|Literatur||S.-C. Liu et al.: Analog VLSI Circuits and Principles; various publications.|
|Voraussetzungen / Besonderes||Particular: The course is highly recommended for those who intend to take the spring semester course 'Neuromorphic Engineering II', that teaches the conception and layout of such circuits with a set of inexpensive software tools, ending with an optional submission of a mini-project for CMOS fabrication.|
Prerequisites: Background in basics of semiconductor physics helpful, but not required.
|227-1037-00L||Introduction to Neuroinformatics||W||6 KP||2V + 1U||K. A. Martin, M. Cook, V. Mante, M. Pfeiffer|
|Kurzbeschreibung||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.|
|Inhalt||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.|
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