Humboldt Universitaet zu Berlin Faculty of Mathematics and Natural Sciences Department of Physics auf deutsch

4020245112 Models of Neural Systems       

Präsenzkurs

classroom language

EN

aims

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.

requirements

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

structure / topics / contents

-Hodgkin-Huxley model of the action potential / point neurons and multicompartment models
-Models of ion channels and chemical synapses
-Network models
-phase-space analysis of neural excitability
-signal processing in the visual system

assigned modules

P24.3.e

amount, credit points; Exam / major course assessment

4 SWS, 6 SP/ECTS (Arbeitsanteil im Modul für diese Lehrveranstaltung, nicht verbindlich)
Oral exam

other

Lecture and tutorial take place in Berlin Mitte on Campus Nord of HU Berlin, in the lecture hall of house 6 (lecture) and in seminar room of house 4 (tutorial).

contact

Prof. Lindner (In Adlershof: NEW 15, 3.412 and [in Mitte] Philippstr. 13, Haus 2, office 1.17), Prof. Richard Kempter am Institut für Biologie