Illinois State University, Physics, Normal, IL 61761
In a sequence of two talks, his is the first where we introduce a set of neural model equations intended for mimicking the behavior of neurons. The so-called Huber-Braun model we use consist of a set of four differential equations with physiologically meaningful variables and parameters. They are capable of representing a wide range of neural dynamical states indicated by the various spiking rates and patterns they generate. We use parameter space color maps to illustrate how the dynamics of the neuron can evolve depending on certain combinations of parameters values. Furthermore, we discuss electric and chemical couplings between neurons, which is responsible for the information in neural networks and possibly leading coupled neurons into synchronous states.
[Abstract (DOCX)]