Neuronal Dynamics (edX)

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.

What you'll 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

Syllabus

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

Suggested Readings:
Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition