Computational Neuroscience: Cortical Dynamics

This volume contains invited and contributed papers presented at the eighth edition of the International Summer School on Neural Networks, dedicated to Prof.EduardoR.Caianiello.Theschoolwasestablishedin1996byProf.Antonio Zichichi, director of the Ettore Maiorana Centre for Scienti?c Culture in Erice (Sicily), and Prof. Maria Marinaro, director of the International Institute for Advanced Scienti?c Studies in Vietri sul Mare, in Italy. The school is held each year,alternatingbetweenEriceandVietri,proposingsurveysonseveralresearch ?elds related to cybernetics studies and human-machine interaction. The eighth edition of the school was on cortical dynamics and was held in Erice. The contributions collected in this book are aimed at providing primarily high-level tutorial coverage of the ?elds related to cortical dynamics, repo- ing recent experimental and theoretical results investigating the processing, the transmission, and the imprinting of information in the brain, and important functions of the cortical area such as cortical rhythms, cortical neural plasticity, and their structural basis and functional signi?cance. Height surveys, reporting the most recent original results, are o?ered by specialists in the ?eld. Consequently, the volume may be used as a reference book on models of cortical dynamics from neuroscienceand physics. To this aim the volume is divided into two sections: fundamentals of cortical dynamics, and mathematical models of cortical dynamics.

Includes supplementary material: sn.pub/extras

Contenu
Section 1 Fundamentals of Cortical Dynamics.- Dynamics of Storage and Recall in Hippocampal Associative Memory Networks.- On the Nested Hierarchical Organization of CNS: Basic Characteristics of Neuronal Molecular Networks.- Neural Phase Transitions That Made Us Mammals.- Section 2 Mathematical Models of Cortical Dynamics.- Mean Field Methods for Cortical Network Dynamics.- Chaotic Neuron Dynamics, Synchronization, and Feature Binding.- A Complex Systems Approach to an Interpretation of Dynamic Brain Activity I: Chaotic Itinerancy Can Provide a Mathematical Basis for Information Processing in Cortical Transitory and Nonstationary Dynamics.- A Complex Systems Approach to an Interpretation of Dynamic Brain Activity II: Does Cantor Coding Provide a Dynamic Model for the Formation of Episodic Memory?.- Itinerant Dynamics of Class I* Neurons Coupled by Gap Junctions.