Graduate Course (PhD program):
Topics in Computational Neuroscience
(Winter term; 2h of lectures per week)
This course is intendend for graduate students in
the Neurosciences with an interest and some previous
knowledge in Computational Neuroscience.
See also the page of the Doctoral School in Neuroscience.
Be introduced by international and local experts to current `hot' topics in Computational Neurosciences, ranging from single-cell modeling, problems of neuronal coding, models of population dynamics, spike-timing dependent plasticity, learning etc. The course is run in form of a Computional Neuroscience Seminar with internal and external speakers. See the detailed program for this year.
Exam: Those students who want to take the course for credit should choose at the end of the term 5 topics (out of the roughly 10-15 topics seen during the semester) which he/she wants to prepare for the exam. This implies in particular reading and understanding the papers covered by the speakers. The oral exam will cover the contents of the papers.