227-0085-38L  Projects & Seminars: Controlling Biological Neuronal Networks Using Machine Learning

SemesterSpring Semester 2021
LecturersJ. Vörös
Periodicityevery semester recurring course
Language of instructionEnglish
CommentOnly for Electrical Engineering and Information Technology BSc.

Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.



Courses

NumberTitleHoursLecturers
227-0085-38 PProjekte & Seminare: Controlling Biological Neuronal Networks Using Machine Learning Special students and auditors need a special permission from the lecturers.
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Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester.


Zeit: Donnerstag, 13-17 Uhr (Beginn 11.03.2021)
Raum: ETZ F70 / online
2 hrsJ. Vörös

Catalogue data

AbstractThe 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.
ObjectiveThe 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).

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersJ. Vörös
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

General : Special students and auditors need a special permission from the lecturers
PlacesLimited number of places. Special selection procedure.
Beginning of registration periodRegistration possible from 19.02.2021
PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupElectrical Engin. + Information Technology BSc (228000)
Waiting listuntil 12.03.2021
End of registration periodRegistration only possible until 05.03.2021

Offered in

ProgrammeSectionType
Electrical Engineering and Information Technology BachelorProjects & SeminarsWInformation