Janos Vörös: Katalogdaten im Frühjahrssemester 2021

NameHerr Prof. Dr. Janos Vörös
LehrgebietBioelektronik
Adresse
Inst. f. Biomedizinische Technik
ETH Zürich, ETZ F 82
Gloriastrasse 35
8092 Zürich
SWITZERLAND
Telefon+41 44 632 59 03
Fax+41 44 632 11 93
E-Mailjanos.voros@biomed.ee.ethz.ch
URLhttp://www.lbb.ethz.ch
DepartementInformationstechnologie und Elektrotechnik
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
227-0085-38LProjekte & Seminare: Controlling Biological Neuronal Networks Using Machine Learning Belegung eingeschränkt - Details anzeigen
Nur für Elektrotechnik und Informationstechnologie BSc.

Die Lerneinheit kann nur einmal belegt werden. Eine wiederholte Belegung in einem späteren Semester ist nicht anrechenbar.
3 KP2PJ. Vörös
KurzbeschreibungDer Bereich Praktika, Projekte, Seminare umfasst Lehrveranstaltungen in unterschiedlichen Formaten zum Erwerb von praktischen Kenntnissen und Fertigkeiten. Ausserdem soll selbstständiges Experimentieren und Gestalten gefördert, exploratives Lernen ermöglicht und die Methodik von Projektarbeiten vermittelt werden.
LernzielThe 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).
227-0970-00LResearch Topics in Biomedical Engineering0 KP2KK. P. Prüssmann, S. Kozerke, M. Stampanoni, K. Stephan, J. Vörös
KurzbeschreibungCurrent topics in Biomedical Engineering presented mostly by external speakers from academia and industry.
Lernzielsee above