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Instructors: Prof. Dr. Helmut Glünder
Event type:
Lecture
Org-unit: Dept. 18 - Electrical Engineering and Information Technology
Displayed in timetable as:
Inf. Neural Systems
Subject:
Crediting for:
Hours per week:
2
Credits:
4,0
Language of instruction:
German
Min. | Max. participants:
- | -
Course Contents:
Introduction to Computational Neuroscience
The course of lectures confronts design disciplines—such as the arts of engineering—with the highly ambitious question of “How do neural systems work?” that is typically to be answered empirically. The course will explicate why and how also design disciplines can help answering this question. Both, widely settled and merely conjectured neurobiological solutions to information processing problems will be presented, especially in view of—for design disciplines—unusual constraints. The latter requires the discussion of biological principles and of neuroscience methods. According to the bio-cybernetical method, an approach based on systems and signal theory is taken.
1) Problems and limits of empirical research
2) What are and what purposes serve neural systems?
(phylogeny and ontogeny, behaviour, sensori-motor cycle)
3) Fundamental difficulties with analyses of neural systems
(extreme complexity versus inadequate empirical methods)
4) The method of bio-cybernetics
(Interplay of engineering concepts and empirical research concerning functionally defined biological systems,
information processing in neural systems versus artificial neural networks, differentiation regarding bionics)
5) Basic functions of nerve cells and their formalizations
(bio-electricity, neural signal representations, signal propagation, impulse generation, synaptic mechanisms, concepts
of formal neurons)
6) Important concepts of neural information processing
(coupled neural layers, self-organization, associative memory networks, non-linear dynamics of impulse-coupled
neurons, analyses of spatio-temporal correspondences, environmental stability under self-motion)
7) Reasons for mistakes and insufficient theoretical concepts
8) Simulation techniques and their limits
Literature:
For the preparation of neurobiological contents by preceding private study:
Thompson, R.F. (2000) The brain. Worth Publishers. New York, NY.
Nicholls J.G., Martin A.R., Wallace B.G. and Fuchs P.A. (2001) From neuron to brain. Sinauer, Sunderland, MA.
Accompanying the Lecture:
Lecture Notes (usually available at the 2nd date of lecture; about 5 Euros)
Exercises & Problems (part of the Lecture Notes)
Comprehension checking Questionnaire (distributed throughout the course of lectures)
Accompanying texts and demos for the required private study are accessible via www.gluender.de/IVNS/IVNSHome.html.
(Text-)Books that efficiently cover the subject matter are not known!
Preconditions:
Successful Bachelor Exam
General interest in Natural Sciences
Background in basic Mathematical Methods for Engineering or Natural Sciences
Of advantage: Basics of Signal and Systems Theory
Expected Number of Participants:
40
Further Grading Information:
Official WebSite of the Course: www.gluender.de/IVNS/IVNSHome.html
Official Course Description:
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