Winter Term 2020-21 / Neural Behav Sci


 Downloads: 

 GUIDELINES  •  MODULE HANDBOOK 2019-20  •  IMPORTANT DATES  •  WEEK PLAN  •  EXAM SCHEDULE

Course title

Introduction to Computational Neuroscience

Lecturer
Mallot
Credits
3.0
Course content / topics

The course will provide a first overview over the field of theoretical neurobiology. In particular, the following topics will be covered:
1. Excitable membranes: Hodgkin-Huxley theory of the action potential; cable theory of passive conduction; examples of ordinary differential equations.
2. Receptive fields: Linear, spatio-temporal systems theory and the convolution integral; special functions used for modelling receptive fields in the visual system; relation to neurophysiological measurement protocols; nonlinear receptive fields (stereo, motion).
3. Fourier analysis: Eigenfunctions of linear systems; Fourier decomposition; complex sinusoidal functions; modulation transfer function.
4. Artificial neural networks: Activation functions, topologies, learning rules; perceptron (pattern recognition); associative memory and self-organizing feature maps; covariance matrices and principal component analysis.
5. Coding and representation: The notion of statistical information (entropy); population coding; topographic maps in the visual cortex.

Course schedule & topics (the course will start on Oct 18, 2019)

Day, time & location

Fri, 10am - 12, Hörsaalzentrum Morgenstelle, N01