Title of Course: Computational Neuroscience - Re-Engineering the Brain
Exam number: XM 3020
Length of course: 2 hours per week
Type of course: lecture
Language: English
Lecturer: Prof. Dr. U. Hofmann
Learning outcomes: The students get access to special methods and requirements of brain research. The students can mathematically simulate simple processes in the brain.
Course Requirements: Basic knowledge matlab, signal processing, anatomy, physiology
Shares Module with: Diploma Students in Informatics
Content:

• Macroscopic Level: Functional Anatomy, EEG, ERP, MEG; Deep Brain Stimulation and Parkinsons Disease; Brain pacemaker; Human Brain Interfaces
• Microscopic Level: Technology of Electrophysiology; Membrane and Ion Channels; Single cell physiology; Biophysics of the neuron; Hodgkin-Huxley-model of action potentials
• 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
• Theoretical Neuroscience: Information theory and Synfire chains; Hebb’s learning rules

Recommended Literature:

• Dayan, P, Abbott, LF (2001) Theoretical neuroscience , Webversion: http://play.ccs.brandeis.edu/abbott/book/
• 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 Modelling, 2nd Edition. Cambridge, MA: MIT Press

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