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Neuronal Dynamics - Computational Neuroscience of Single Neurons

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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Rating Not enough ratings
Length 7 weeks
Effort 6 hours/week
Starts On Demand (Start anytime)
Cost $50
From École polytechnique fédérale de Lausanne via edX
Instructor Wulfram Gerstner
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics Science
Tags Computer Science Math Biology & Life Sciences Physics

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Rating Not enough ratings
Length 7 weeks
Effort 6 hours/week
Starts On Demand (Start anytime)
Cost $50
From École polytechnique fédérale de Lausanne via edX
Instructor Wulfram Gerstner
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics Science
Tags Computer Science Math Biology & Life Sciences Physics

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