13849 - Introduction to Computational Neuroscience Modulübersicht

Module Number: 13849
Module Title:Introduction to Computational Neuroscience
  Einführung in Computational Neuroscience
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr.-Ing. habil. Glasauer, Stefan
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: Every winter semester
Credits: 6
Learning Outcome:Upon completion of the module, students are able to understandof neuronal systems and behavioral performance, to evaluate the analysis and modeling of neurons, as well as to implement and to analyse neurons and neural networks.
Contents:Based on examples the module presents the methodical procedure for the analysis and modeling of neurons and neural systems. Ethical aspects are discussed in connection with animal and human experiments.

Presented Topics:
Spiking neurons, resting membrane potential, ion channels, action potential, Hodgkin-Huxley model, phase plane analysis, leaky integrate-and-fire model, synaptic transmission, synaptic plasticity, firing rate neurons, neural networks, perceptron, Hebb's learning rule, attractor networks.
Recommended Prerequisites:Knowledge of the topics of the modules 
  • 11112 Mathematik IT-1 (Diskrete Mathematik)
  • 11113 Mathematik IT-2 (Lineare Algebra)
  • 11213 Mathematik IT-3 (Analysis)
  • 11756 Algorithmen und Datenstrukturen, or 12101 Algorithmieren und Programmieren
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:
  • P. Dayan, L. Abbott, Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems (2005), MIT Press, ISBN 978-0262541855
  • Gerstner W, Kistler WM, Naud R, Paninski L: Neuronal Dynamics: From single neurons to networks and models of cognition, Cambridge University Press (2014), https://neuronaldynamics.epfl.ch
Module Examination:Prerequisite + Final Module Examination (MAP)
Assessment Mode for Module Examination:Prerequisite: 
  • Successful completion of exercises
Final Module Examinatio: 
  • Written exam, 120 minutes OR
  • Oral examination, 30-45 minutes
In the first lecture it will be announced, if the examination will be offered in written or oral form.
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:100
Part of the Study Programme:
  • Master (research-oriented) / Artificial Intelligence / PO 2022
  • Bachelor (research-oriented) / Informatik / PO 2008
  • Bachelor (research-oriented) / Informations- und Medientechnik / PO 2017
  • Master (research-oriented) / Künstliche Intelligenz Technologie / PO 2022
  • Abschluss im Ausland / Mathematik / keine PO
  • Bachelor (research-oriented) / Medizininformatik / PO 2016
  • Study programme Medizininformatik B.Sc.: Compulsory elective module in complex „Medizininformatik"
  • Study programme Informatik B.Sc.: Compulsory elective module in complex „Praktische Informatik" (level 300)
  • Study programme Informations- und Medientechnik B.Sc.: Complex „Computer Science", compulsory elective module module in the field of study „Kognitive Systeme"
  • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex  „Advanded Methods“
Module Components:
  • Lecture: Introduction to Computational Neuroscience
  • Accompanying exercise
  • Related examination
Components to be offered in the Current Semester: