neu246 - Computational Neuroscience - Biophysical Modeling (Vollständige Modulbeschreibung)

Students from other study programs are welcome if space is available
This module requires good programming skills! (As taught in neu710 or neu715.)

Goals of this module:

upon completion of this module, students…
- are able to implement and apply algorithms in Matlab
- have programmed and applied simulation techniques
-  know about computational model approaches on different levels of abstraction
- know how to perform model simulations for single cells and small neuronal networks
- can interpret simulation results in a neuroscientific context

Skills to be acquired/ competencies:

++          Neuroscience knowledge
+            Scientific Literature
+            Social skills
++          Maths/Stats/Programming
+            Data presentation/discussion
+            Scientific English

Conductance-based single cell models using differential equations (passive membrane equation, integrate-and-fire, Hodgkin-Huxley)
Synaptic interaction in small network models (alpha synapses,  spike-timing dependent plasticity, feed-forward and feed-back networks, lateral inhibition,  central pattern generator)

Skripts for each course day will be provided prior to the course
Copies of scientific articles for the seminar and as basis for portfolio assignments will be provided prior to the course.
Recommended textbooks or other literature:
Dayan / Abbott: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. MIT Press (More text book chapters will be suggested prior to the course).