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" Nonlinear dynamics in computational neuroscience / "
Fernando Corinto, Alessandro Torcini, editors.
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BL
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| Record Number
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864222
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| Title & Author
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Nonlinear dynamics in computational neuroscience /\ Fernando Corinto, Alessandro Torcini, editors.
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| Publication Statement
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Cham :: Springer,, [2018]
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, ©2019
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| Series Statement
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PoliTO Springer series
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| Page. NO
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1 online resource :: illustrations
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| ISBN
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3319710486
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: 9783319710488
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3319710478
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9783319710471
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| Bibliographies/Indexes
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Includes bibliographical references.
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| Contents
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Characterization of Neural Signals in Preclinical Studies of Neural Plasticity Using Nonlinear Time Series Analysis1 Introduction; 2 Linear and Nonlinear Time Series Analysis Methods; 2.1 Spectral Methods; 2.2 Coupling Measures; 2.3 Power Law Correlations; 3 Characterization of Local Field Potentials in Preclinical Studies of Neural Plasticity; 3.1 Spectral Properties and Inter-hemispheric Coupling Directionality in a Model of Focal Epilepsy; 3.2 Post-stroke Modifications of Inter-hemispheric Coupling in Low Frequency Band; 3.3 Scaling Properties of LFPs in EE Rearing Condition.
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4 Discussion and ConclusionReferences; Functional Cliques in Developmentally Correlated Neural Networks; 1 Introduction; 2 Model and Methods; 2.1 Correlations; 2.2 Functional Connectivity; 3 Results; 3.1 Single Neuron Stimulation and Deletion Experiments; 3.2 The Clique of Functional Hubs; 4 Discussion; References; Chimera States in Pulse Coupled Neural Networks: The Influence of Dilution and Noise; 1 Introduction; 2 The Model; 3 Fully Coupled Network: Phase Diagram; 4 Diluted Networks; 5 Noisy Dynamics; 6 Discussion; References; Nanotechnologies for Neurosciences; 1 Introduction.
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Memristor and Memristor Circuit Modelling Based on Methods of Nonlinear System Theory1 Introduction; 2 One-Memristor Circuits; 2.1 Memristor Model; 2.2 Application of the Theory to One-Memristor Circuits; 2.3 Circuit Dynamic Equations; 2.4 Analytical Derivation of Volterra Kernels; 2.5 Response to a Sine-Wave Input; 2.6 Theory Validation; 3 Extension to Two-Memristor Circuits; 3.1 Memristor Model; 3.2 Application of the Theory to Two-Memristor Circuits; 3.3 Circuit Dynamic Equations; 3.4 Analytical Derivation of Volterra Kernels; 3.5 Response to a Sine-Wave Input; 3.6 Theory Validation.
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| Abstract
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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.
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Computational neuroscience.
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Nonlinear theories.
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Artificial intelligence.
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Computational neuroscience.
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Mathematical modelling.
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MEDICAL-- Physiology.
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Neurosciences.
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Nonlinear science.
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Nonlinear theories.
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SCIENCE-- Life Sciences-- Human Anatomy Physiology.
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| Dewey Classification
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612.8
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| LC Classification
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QP357.5
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| Added Entry
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Corinto, Fernando
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Torcini, Alessandro
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