Nonlinear Dynamics in Computational Neuroscience

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Corinto, Fernando (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Torcini, Alessandro (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: PoliTO Springer Series,
• Θέματα: Computational intelligence.; Neural networks (Computer science) .; Neurosciences.; Statistical physics.; Computational Intelligence.; Mathematical Models of Cognitive Processes and Neural Networks.; Applications of Nonlinear Dynamics and Chaos Theory.

 This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the development of engineering devices and platforms for neuromorphic computation. Written by leading experts in such diverse fields as neuroscience, physics, psychology, neural engineering, cognitive science and applied mathematics, the book reflects the remarkable advances that have been made in the field of computational neuroscience, an emerging discipline devoted to the study of brain functions in terms of the information-processing properties of the structures forming the nervous system. The contents build on the workshop "Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT," which was held in Torino, Italy in September 2015. 

 Introduction -- Next generation neural mass models -- Unraveling brain modularity through its slow oscillations -- Characterization of Neural Signals in Preclinical Studies of Neural Plasticity using Nonlinear Time Series Analysis -- Functional Cliques in Developmentally Correlated Neural Networks -- Chimera states in pulse coupled neural networks: the influence of dilution and noise -- Nanotechnologies for Neurosciences -- Memristor and Memristor Circuit Modelling based on Methods of Nonlinear System Theory -- A memristor-based cell for complexity.