4020205100 Models of Neural Systems - Theoretical Lecture
Digital- & Präsenz-basierter Kurs
- classroom language
- DE
- 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
- keine
- structure / topics / contents
- • Hodgkin-Huxley-Modell des Aktionspotentials – Punktneurone und Multikompartimentmodelle
• Modelle für Ionenkanäle und chemische Synapsen
• Modelle synaptischer Plastizität und Lernmodelle
• Netzwerkmodelle
• Phasenraumanalyse neuronaler Anregbarkeit
• Signalverarbeitung im visuellen System
- assigned modules
-
P24.3.e
- amount, credit points; Exam / major course assessment
- 2 SWS, 2 SP/ECTS (Arbeitsanteil im Modul für diese Lehrveranstaltung, nicht verbindlich)
Participation
- other
- This lecture takes place on mondays, from 10:00-11:30 on Campus North, Bernstein Center for Computational Neuroscience, Philippstr. 13, Haus 6, Lecture Hall 102.
- contact
- Benjamin Lindner, Professor for Theory of Complex Systems and Neurophysics BCCN Berlin Philippstr. 13, Haus 2, 10115 Berlin Room: 1.17, phone: 0049(0)302093 6336 Physics Dep. Humboldt University Berlin Newtonstr. 15 12489 Berlin Room: 3.412, phone: 0049(0)302093 7934