Lecture

MathDetour 1: Separation of time scales

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Description

This lecture covers the concept of separation of time scales in computational neuroscience, focusing on reducing detail in two-dimensional neuron models. The instructor explains the transition from Hodgkin-Huxley to 2D models, the role of nullclines, stability of fixed points, and different types of neuron models. The lecture also delves into nonlinear integrate-and-fire models.

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In MOOC

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).

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