Janos Vörös: Catalogue data in Autumn Semester 2022
|Name||Prof. Dr. Janos Vörös|
Inst. f. Biomedizinische Technik
ETH Zürich, ETZ F 82
|Telephone||+41 44 632 59 03|
|Fax||+41 44 632 11 93|
|Department||Information Technology and Electrical Engineering|
|227-0085-38L||Projects & Seminars: Controlling Biological Neuronal Networks Using Machine Learning |
Does not take place this semester.
Only for Electrical Engineering and Information Technology BSc.
Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.
|3 credits||2P||J. Vörös|
|Abstract||The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.|
|Objective||The way memory and learning is achieved in the brain is an unsolved problem. Due to its relative simplicity, in-vitro neuroscience can help us discover the fundamentals of information processing in the brain. For this we can simulate a small number of biological neurons on top of an array of microelectrodes. Such an approach allows us to simulate the electrical activity of the neurons when they get stimulated.|
Following this approach, we can investigate biological neural networks, that have about 5-50 neurons and a controlled network architecture. Still, their behavior remains highly unpredictable. Therefore, it is not yet clear how such networks need to be stimulated electrically in order to control their behavior. However, we can use machine learning to find a mapping between a stimulus and a desired response. More specifically, we can use reinforcement learning, since finding the right stimulation pattern is an instance of the so called multi-armed bandit problem.
This P&S consists of two parts. In the first part we will introduce you to the way neurons can be simulated. You will learn how neurons work and how they communicate. The second part will be about machine learning. We will discuss the basics of both artificial neural networks (ANN) and reinforcement learning. As homework exercises you will implement a reward function for a provided reinforcement learner, which will control your biological networks. In addition you will
implement an ANN, that replaces unsatisfactorily performing stimulation patterns with new patterns, that this network evaluates to perform better.
If the current situation will allow, the developed ANNs will be tested on real neurons in our laboratory.
This P&S will be given in English. In total, the P&S takes 8 afternoons and about 50 hours of homework (ANN implementation).
|227-0386-00L||Biomedical Engineering||4 credits||3G||J. Vörös, S. J. Ferguson, S. Kozerke, M. P. Wolf, M. Zenobi-Wong|
|Abstract||Introduction into selected topics of biomedical engineering as well as their relationship with physics and physiology. The focus is on learning the basic vocabulary of biomedical engineering and getting familiar with concepts that govern common medical instruments and the most important organs from an engineering point of view.|
|Objective||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. It also serves as an introduction to the field for students of the ITET, MAVT, HEST and other bachelor programs.|
In addition, the most recent achievements and trends of the field of biomedical engineering are also outlined.
|Content||History of BME and the role of biomedical engineers. Ethical issues related to BME.|
Biomedical sensors both wearable and also biochemical sensors.
Bioelectronics: Nernst equation, Donnan equilibrium, equivalent circuits of biological membranes and bioelectronic devices.
Bioinformatics: genomic and proteomic tools, databases and basic calculations.
Equations describing basic reactions and enzyme kinetics.
Medical optics: Optical components and systems used in hospitals.
Basic concepts of tissue engineering and organ printing.
Biomaterials and their medical applications.
Function of the heart and the circulatory system.
Transport and exchange of substances in the human body, compartment modeling.
The respiratory system.
Lectures (2h), discussion of practical exercises (1h) and homework exercises.
|Lecture notes||Introduction to Biomedical Engineering|
by Enderle, Banchard, and Bronzino
moodle page of the course
|Prerequisites / Notice||No specific requirements, BUT|
ITET, MAVT, PHYS students will have to learn a lot of new words related to biochemistry, biology and medicine, while
HEST and BIOL students will have to grasp basic engineering concepts (circuits, equations, etc.).
|227-0393-10L||Bioelectronics and Biosensors||6 credits||2V + 2U||J. Vörös, M. F. Yanik|
|Abstract||The course introduces bioelectricity and the sensing concepts that enable obtaining information about neurons and their networks. The sources of electrical fields and currents in the context of biological systems are discussed. The fundamental concepts and challenges of measuring bioelectronic signals and the basic concepts to record optogenetically modified organisms are introduced.|
|Objective||During this course the students will:|
- learn the basic concepts in bioelectronics including the sources of bioelectronic signals and the methods to measure them
- be able to solve typical problems in bioelectronics
- learn about the remaining challenges in this field
Sources of bioelectronic signals
2. Membrane and Transport
3-4. Action potential and Hodgkin-Huxley
Measuring bioelectronic signals
5. Detection and Noise
6. Measuring currents in solutions, nanopore sensing and patch clamp pipettes
7. Measuring potentials in solution and core conductance model
8. Measuring electronic signals with wearable electronics, ECG, EEG
9. Measuring mechanical signals with bioelectronics
In vivo stimulation and recording
10. Functional electric stimulation
11. In vivo electrophysiology
Optical recording and control of neurons (optogenetics)
12. Measuring neurons optically, fundamentals of optical microscopy
13. Fluorescent probes and scanning microscopy, optogenetics, in vivo microscopy
14. Measuring biochemical signals
|Lecture notes||A detailed script is provided to each lecture including the exercises and their solutions.|
|Literature||Plonsey and Barr, Bioelectricity: A Quantitative Approach (Third edition)|
|Prerequisites / Notice||The course requires an open attitude to the interdisciplinary approach of bioelectronics. |
In addition, it requires undergraduate entry-level familiarity with electric & magnetic fields/forces, resistors, capacitors, electric circuits, differential equations, calculus, probability calculus, Fourier transformation & frequency domain, lenses / light propagation / refractive index, pressure, diffusion AND basic knowledge of biology and chemistry (e.g. understanding the concepts of concentration, valence, reactants-products, etc.).
|227-0970-00L||Research Topics in Biomedical Engineering|
Does not take place this semester.
|0 credits||1K||K. P. Prüssmann, S. Kozerke, M. Stampanoni, K. Stephan, J. Vörös|
|Abstract||Current topics in Biomedical Engineering presented by speakers from academia and industry.|
|Objective||Getting insight into actual areas and problems of Biomedical Engineering an Health Care.|