Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition, written by Wulfram Gerstner, Werner M. Kistler, and Richard Naud, is a textbook suitable for professionals. This English-language reference work addresses the dynamics of neurons from single neurons to complex networks and models of cognitive processes.
The book provides a comprehensive overview of computational and theoretical neuroscience, with topics such as Hodgkin-Huxley equations, the Hopfield model, generalized linear models, and decision theory. The clear step-by-step explanations are aimed at readers with basic knowledge of differential equations and probability theory.
With a rich illustration of figures, examples, and exercises, it is an excellent learning tool for both self-study and teaching. The content connects with themes such as neural networks and fuzzy systems, data science, and professional programming in computing.
This publication uses physical principles and mathematical methods to clarify fundamental questions about neurons and networks, making it a valuable source for anyone who wants to delve into computational networks and models.