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Neural Fields

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Cover of 'Neural Fields'

Table of Contents

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    Book Overview
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    Chapter 1 Tutorial on Neural Field Theory
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    Chapter 2 A Personal Account of the Development of the Field Theory of Large-Scale Brain Activity from 1945 Onward
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    Chapter 3 Heaviside World: Excitation and Self-Organization of Neural Fields
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    Chapter 4 Spatiotemporal Pattern Formation in Neural Fields with Linear Adaptation
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    Chapter 5 PDE Methods for Two-Dimensional Neural Fields
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    Chapter 6 Numerical Simulation Scheme of One- and Two Dimensional Neural Fields Involving Space-Dependent Delays
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    Chapter 7 Spots: Breathing, Drifting and Scattering in a Neural Field Model
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    Chapter 8 Heterogeneous Connectivity in Neural Fields: A Stochastic Approach
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    Chapter 9 Stochastic Neural Field Theory
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    Chapter 10 On the Electrodynamics of Neural Networks
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    Chapter 11 Universal Neural Field Computation
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    Chapter 12 A Neural Approach to Cognition Based on Dynamic Field Theory
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    Chapter 13 A Dynamic Neural Field Approach to Natural and Efficient Human-Robot Collaboration
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    Chapter 14 Neural Fields
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    Chapter 15 Equilibrium and Nonequilibrium Phase Transitions in a Continuum Model of an Anesthetized Cortex
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    Chapter 16 Large Scale Brain Networks of Neural Fields
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    Chapter 17 Neural Fields, Masses and Bayesian Modelling
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    Chapter 18 Neural Field Dynamics and the Evolution of the Cerebral Cortex
Attention for Chapter 1: Tutorial on Neural Field Theory
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Citations

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Chapter title
Tutorial on Neural Field Theory
Chapter number 1
Book title
Neural Fields
Published by
Springer, Berlin, Heidelberg, January 2014
DOI 10.1007/978-3-642-54593-1_1
Book ISBNs
978-3-64-254592-4, 978-3-64-254593-1
Authors

Stephen Coombes, Peter beim Graben, Roland Potthast

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 26%
Researcher 6 26%
Student > Master 4 17%
Student > Bachelor 2 9%
Professor 1 4%
Other 0 0%
Unknown 4 17%
Readers by discipline Count As %
Neuroscience 8 35%
Mathematics 3 13%
Engineering 3 13%
Computer Science 1 4%
Physics and Astronomy 1 4%
Other 1 4%
Unknown 6 26%