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Mathematical and Theoretical Neuroscience

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Cover of 'Mathematical and Theoretical Neuroscience'

Table of Contents

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    Book Overview
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    Chapter 1 From Single Neuron Activity to Network Information Processing: Simulating Cortical Local Field Potentials and Thalamus Dynamic Regimes with Integrate-and-Fire Neurons
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    Chapter 2 Computational Modeling as a Means to Defining Neuronal Spike Pattern Behaviors
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    Chapter 3 Chemotactic Guidance of Growth Cones: A Hybrid Computational Model
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    Chapter 4 Mathematical Modelling of Cerebellar Granular Layer Neurons and Network Activity: Information Estimation, Population Behaviour and Robotic Abstractions
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    Chapter 5 Bifurcation Analysis of a Sparse Neural Network with Cubic Topology
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    Chapter 6 Simultaneous Jumps in Interacting Particle Systems: From Neuronal Networks to a General Framework
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    Chapter 7 Neural Fields: Localised States with Piece-Wise Constant Interactions
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    Chapter 8 Mathematical Models of Visual Perception Based on Cortical Architectures
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    Chapter 9 Mathematical Models of Visual Perception for the Analysis of Geometrical Optical Illusions
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    Chapter 10 Exergaming for Autonomous Rehabilitation
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    Chapter 11 E-Infrastructures for Neuroscientists: The GAAIN and neuGRID Examples
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    Chapter 12 Theory and Application of Nonlinear Time Series Analysis
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    Chapter 13 Measures of Spike Train Synchrony and Directionality
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    Chapter 14 Space-by-Time Tensor Decomposition for Single-Trial Analysis of Neural Signals
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    Chapter 15 Inverse Modeling for MEG/EEG Data
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Title
Mathematical and Theoretical Neuroscience
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-68297-6
ISBNs
978-3-31-968296-9, 978-3-31-968297-6
Editors

Giovanni Naldi, Thierry Nieus

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 20%
Researcher 5 20%
Student > Bachelor 2 8%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Other 3 12%
Unknown 6 24%
Readers by discipline Count As %
Neuroscience 8 32%
Agricultural and Biological Sciences 3 12%
Physics and Astronomy 2 8%
Mathematics 2 8%
Medicine and Dentistry 1 4%
Other 1 4%
Unknown 8 32%