Computational Neuroscience - Summer term 2024
Interdisciplinary lecture series taught by neuroscience experts from TUM and LMU that provides an introduction to computational neuroscience. Topics range from a general overview on neurobiology and basic modeling to neuroengineering and -prothetics. In winter terms a focus is given to neuroengineering and -prothetics whereas summer terms cover topics more strongly related to biological mechanisms.
Some background on Julius Bernstein, who lent his name to the Bernstein Network: Julius Bernstein (1839–1917): pioneer neurobiologist and biophysicist.
For general inquiries on the lecture please get in touch with Dr. Kay Thurley
Day and Time
Tuesday 18:00-19:30 s.t., summer term 2024
Venue
LMU Main Building, Geschwister-Scholl-Platz 1, E 006
floor plan
More information and lecture notes will be posted on our Moodle page Moodle@elearningTUM a couple of days before each lecture listed below.
Overview
No. | Date | Lecturer | Topic | |
---|---|---|---|---|
1 | 04/16 | Herz | Modelling |
Introduction to Computational Neuroscience |
04/23 |
no lecture |
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2 | 04/30 | Luksch | Biology |
Neuroanatomy primer |
3 | 05/07 | Luksch | Biology |
Neurophysiology primer |
4 | 05/14 | Młynarski | Modelling |
Information theory in neurobiology |
05/21 | no lecture -- Pentecost |
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5 | 05/28 | Modelling | Perceptual inference in the brain | |
6 | 06/04 | Gjorgjieva | Modelling |
Plasticity and development of neural circuits |
7 | 06/11 | Busse | Integration |
Visual system I: neurobiology |
8 | 06/18 | Modelling | Visual system II: computation |
|
9 | 06/25 | Engineering | Neuroprosthetics | |
10 | 07/02 | Sirota | Integration |
Methods of systems neuroscience: measurement and perturbation of neural activity |
11 | 07/09 | Sirota | Integration |
Systems mechanisms of learning and memory from theory to experimental data |
12 | 07/16 | Thurley | Integration |
Temporal cognition |
Exam |
Time: tba Registration for LMU students until ... by email to Dr. Kay Thurley! |
Exam/Credits
3 ECTS
In the written examination, an overview of the various aspects of computational neuroscience will be tested. Knowledge-based learning outcomes from the lecture as well as the understanding and ability to solve (practical) problems will be assessed in a 60 min written examination with questions set and corrected by the respective lecturers.
Here you can find an example exam and the sample solutions. Due to the limited number of questions and the slightly changing lecture content and the lecturers, we cannot provide further example exams. Please ask the individual lectures for further help, e.g., self-assessment questions.
For general questions on the exam please get in touch with Dr. Kay Thurley.