Key Information
About the content
This course gives an introduction to the field of theoretical and computational neuroscience with a focus on models of single neurons. Neurons encode information about stimuli in a sequence of short electrical pulses (spikes). Students will learn how mathematical tools such as differential equations, phase plane analysis, separation of time scales, and stochastic processes can be used to understand the dynamics of neurons and the neural code.
Week 1: A first simple neuron model
Week 2: Hodgkin-Huxley models and biophysical modeling
Week 3: Two-dimensional models and phase plane analysis
Week 4: Two-dimensional models (cont.)/ Dendrites
Week 5: Variability of spike trains and the neural code
Week 6: Noise models, noisy neurons and coding
Week 7: Estimating neuron models for coding and decoding
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Prerequisite
Calculus, differential equations, probabilities.
Recommended textbook: "NEURONAL DYNAMICS - from single neurons to networks and cognition", Cambridge Univ. Press 2014
Syllabus
- How mathematical tools such as differential equations, phase plane analysis, separation of time scales, and stochastic processes can be used to understand the dynamics of neurons and the neural code
Instructors
Wulfram Gerstner
Professor, Computer Science
EPFL
Content Designer
The École polytechnique fédérale de Lausanne (EPFL, English: Swiss Federal Institute of Technology in Lausanne) is a research university in Lausanne, Switzerland, that specialises in physical sciences and engineering.
One of the two Swiss Federal Institutes of Technology, the school was founded by the Swiss Federal Government with the stated mission to:
Educate engineers and scientists to the highest international standing
Be a national center of excellence in science and technology
Provide a hub for interaction between the scientific community and the industry
EPFL is considered one of the most prestigious universities in the world for engineering and sciences, ranking 17th overall and 10th in engineering in the 2015 QS World University Rankings; 34th overall and 12th in engineering in the 2015 Times Higher Education World University Rankings.
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