Application 2008
Students from the European Union can still send their applications up to
August 31st, 2008.
Information on application
The deadline for Non-EU-students has passed, there are no more applications to uni-assist possible.
New Students 2008
Introduction week starts at
September 22nd, 2008,
lectures start at
September 29th, 2008
Further Information
Exams
August 11th - September 9th:
Students have to regsiter for the (re-) exams in September
Title of Course: Computational Neuroscience -Re-Engineering the Brain
Exam number: XM 1460
Length of course: 2 hours per week
Type of course: lecture
Language: English
Lecturer: Dr. U.G. Hofmann
Aim of course:
Course Requirements: Basic knowledge of signal processing
Recommended Literature:
Dayan, P, Abbott, LF (2001) Theoretical neuroscience , Webversion:
-
Windhorst U, Johansson H (1999) Modern Techniques in Neuroscience Research , 1 Edition. Berlin: Springer.
Kandel ER, Schwartz JH, Jessel TM (1991) Principles of neural science , 3rd Edition. London: Prentice-Hall.
Nicholls JG, Martin AR, Wallace BG (1992) From Neuron to Brain, 3rd Edition. Sunderland, MA: Sinauer Assoc., Inc.
Koch C, Segev I (1998) Methods in Neuronal Modeling, 2nd Edition. Cambridge, MA:
MIT Press.
Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W, eds (1998)Spikes - Exploring the Neural Code. Cambridge, MA:
MIT Press.
Shares Module with: Diploma Students in Informatics
Content:
Macroscopic Level
Anatomy, imaging devices CT, MRI, fMRI (BOLD), PET, SPECT
Functional Anatomy, EEG, ERP, MEG
Pathologies and Diseases
Deep Brain Stimulation and Parkinsons Disease, Brain pacemaker
Microscopic Level
Technology of Electrophysiology
Membrane and Ion Channels
Single cell physiology
Biophysics of the neuron
Hodgkin-Huxley-model of action potentials
Human Brain Interfaces
Mesoscopic Level
Micro-anatomy
Network function: The sum is bigger than its constituents
Binding and synchronicity
Modeling and Simulations
Realistic modeling of single cells and networks
Explaining and calculating neuron properties
Neuromorphic systems and technical copies
Elementary building blocks
Technical counterparts
Theoretical Neuroscience
Information theory and Synfire chains
Hebb's learning rules
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