Benda
Neurons are the basic elements of neural systems that process sensory information and generate behavior. To allow for the broad spectrum of brain functions, single neurons already implement complex signal processing tasks. The necessary non-linearities are generated by voltage-gated ion channels and in particular by action potentials. However, these non-linearities make an intuitive understanding and simple qualitative descriptions of brain functions difficult if not impossible. Mathematical models and computer simulations help to overcome these difficulties and are important standard tools in modern neuroscience for the interpretation and generalization of experimental results.
The lecture introduces models of neurons of different complexity from the detailed Hodgkin-Huxley models for action potential generation via integrate-and-fire models to simple firing rate models. Based on these specific examples basic concepts of differential equations, linear system theory, dynamical systems theory and stochastic systems are introduced. These tools are essential for modelling neural systems and other complex systems like, for example, signaling cascades and population dynamics. Central to the module are the exercises that match the topics from the lecture and repeat the necessary math basics.