The activity of neurons in the brain and the code used by these neurons is described by mathematical neuron models at different levels of detail.
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 Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.