WS 2022/2023 Computational Neuroscience: Models of Neural Systems Richard Kempter and Benjamin Lindner

First Event: Introduction to the MNS module and Computer Practical, 18-October-2022, 17:30h, BCCN lecture hall in Haus 6

Dates: Weekly, from 18-October-2022 to 14-February-2023.

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

Times:

• Theoretical Lectures 2112132 (2 SWS, 2 ECTS):
  Mondays from 10:15h to 11:45h (BCCN lecture hall, Haus 6);
  first lecture on October 24, 2022.
  
• Analytic Tutorials 2112446 (2 SWS, 4 ECTS):
  Thursdays, 17:30-19:00h (location: Haus 4, seminar room);
  first brief introdution on October 27, 2022 at 17:30 - 18:00h
  
• Experimental Lectures 2112690 (2 SWS, 2 ECTS):
  Mondays from 16:15h to 17:45h (BCCN lecture hall, Haus 6);
  first lecture on October 24, 2022.
  
• Computer Practical 2112133 (2 SWS, 4 ECTS):
  Weekly, Tuesdays from 17:30h to 19:00h (computer pool: Haus 2, east wing, room 0.10);
  first tutorial on October 18, 2022. 17:30h (BCCN lecture hall, Haus 6)
  Extended introduction (Thursday, October 20, 17:30-19:00h; Thursday October 27, 18:00-19:30h).
  

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.

Moodle Pages and People:

• Theoretical Lectures by Richard Kempter and Benjamin Lindner
  
• Analytic Tutorials by Naomi Auer, Gaspar Cano, Misha Zaks, Ikhwan Bin Khalid
  
• Experimental Lectures organized by Lisa Velenosi
  
• Computer Practical by Paula Kuokkanen, Natalie Schieferstein, Lukas Ramlow, Ana Toro, Stefano Masserini (+ Rike-Benjamin Schuppner for the introduction in the first two weeks)
  

Overview about the contents of the module:
Further details are available at this page.

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), but each student must submit a solution (indicating all group members). 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, and every student is expected to present at least once.

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), but each student must submit a solution (indicating all group members). 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 are expected to 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-March-2023. To prepare for the exams, there will a special meeting of students and examiners on Monday, Feb-13-2023 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.