WS 2021/2022

Computational Neuroscience:
Models of Neural Systems

Richard Kempter and Benjamin Lindner


First Event: Introduction to the MNS module and Computer Practical, 19-October-2021, 18:00h, BCCN lecture hall in Haus 6

Dates: Weekly, from 19-October-2021 to 14-February-2022.

Location: Bernstein Center for Computational Neurosciences Berlin, Haus 6, Philippstr. 13.


Target Group: Students of Computational Neuroscience, Medical Neuroscience, Biology, Biophysics, Physics, Mathematics, Computer Science, and Psycholgy.

Here is the full description of the master modules Models of Neural Systems (Master CNS, TU) and MB-B10 (Master Biology, HU) and P24.3.e (Master Physics, HU).

Requirements: Basic knowledge in Mathematics (e.g. calculus, differential equations, algebra) and a higher programming language (e.g. C, C++, Python, MatLab).

Aims and Topics: Participants should learn basic concepts, their theoretical foundation, and the common models used in Computational Neuroscience. The Module ''Models of Neural Systems'' also provides some neurobiological knowledge and explains the relevant theoretical approaches as well as the findings resulting form these approaches so far. After completing the Module, participants should understand strengths and limitations of the different models. Participating students will learn to appropriately choose the theoretical methods for modeling cellular neural systems. They will learn how to apply these methods while taking into account the neurobiological findings, and they should be able to critically evaluate results obtained. Participants should also be able to adapt models to new problems as well as to develop new models of neural systems.

People and Contents:

Further details are available at this moodle page.

Course Certificates:

Analytic Tutorials:

To obtain a course certificate ("Schein") that certificates a successful participation, solutions to the weekly problem sets must be turned in electronically on Mondays before the beginning of the lecture, and on average at least 60% of the points must be obtained. Students must work in groups of ideally 2 (maximum 3) and submit a single joint solution for each problem set. Group compositions changes two times during the semester (groups of size 3 do not keep subgroups of 2 students). Groups change inbetween the three blocks of problem sets 1-4, 5-9, and 10-13. The 60% threshold applies to each of the 3 blocks of problem sets. An active participation in the tutorials is strongly encouraged. The successful presentation of a problem will be rewarded by bonus points (10%) for the presenting student.

Computer Practicals: To obtain a course certificate ("Schein") that certifies a successful participation, solutions to the assignments must be turned in on the days preceding the computer practicals, and on average at least 60% of the points in the exercises must be obtained. Students must work in groups of ideally 2 (maximum 3) and submit a single joint solution for each assignment. Group compositions must change at least 2 times per semester, and groups must not work in the same constellation for more than 3 assignments (groups of size 3 must not keep subgroups of 2 students). In a final software phase, students must attend the software tutorials and successfully pass one additional exercise sheet (60%).

Module Examinations: Oral exam (graded); certificates of successful participation in the tutorials and/or practicals is a prerequisite for the oral exam. The exam days are 21/22/23-March-2022. Note that the exam should be taken at the end of the semester but has to be taken latest by the end of the semester following the one of obtaining the tutorial certificates. To prepare for the exams, there will a special meeting of students and examiners on Monday, Feb-14-2022 at 11:45h.

Recommended reading:

P. Dayan and L.F. Abbott (2001) Theoretical Neuroscience. MIT Press, Cambridge, Massachusetts.

E. M. Izhikevich (2007) Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting. MIT Press, Cambridge, Massachusetts.

Johnston, Wu (1995) Foundations in Cellular Neurophysiology, MIT Press, Cambrigdge, Massachusetts.

Advanced/additional reading:

M. F. Bear, B. W. Connors, M. A. Paradiso (2007) Neuroscience: Exploring the Brain, Lippincott Williams & Wilkins, Baltimore, Maryland.

Thomas P. Trappenberg (2002) Fundamentals of Computational Neuroscience. Oxford University Press, Oxford, UK.

P. Churchland and T. Sejnowski (1994). The Computational Brain. MIT Press, Cambridge, MA.

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