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Analysis of Parallel Spike Trains

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Cover of 'Analysis of Parallel Spike Trains'

Table of Contents

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    Book Overview
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    Chapter 1 Stochastic Models of Spike Trains
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    Chapter 2 Estimating the Firing Rate
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    Chapter 3 Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains
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    Chapter 4 Processing of Phase-Locked Spikes and Periodic Signals
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    Chapter 5 Pair-Correlation in the Time and Frequency Domain
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    Chapter 6 Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale
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    Chapter 7 Spike Metrics
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    Chapter 8 Gravitational Clustering
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    Chapter 9 Spatio-Temporal Patterns
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    Chapter 10 Unitary Event Analysis
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    Chapter 11 Information Geometry of Multiple Spike Trains
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    Chapter 12 Higher-Order Correlations and Cumulants
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    Chapter 13 Information Theory and Systems Neuroscience
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    Chapter 14 Population Coding
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    Chapter 15 Stochastic Models for Multivariate Neural Point Processes: Collective Dynamics and Neural Decoding
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    Chapter 16 Simulation of Stochastic Point Processes with Defined Properties
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    Chapter 17 Generation and Selection of Surrogate Methods for Correlation Analysis
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    Chapter 18 Bootstrap Tests of Hypotheses
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    Chapter 19 Generating Random Numbers
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    Chapter 20 Practically Trivial Parallel Data Processing in a Neuroscience Laboratory
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    Chapter 21 Erratum to: Population Coding
Attention for Chapter 1: Stochastic Models of Spike Trains
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Chapter title
Stochastic Models of Spike Trains
Chapter number 1
Book title
Analysis of Parallel Spike Trains
Published by
Springer, Boston, MA, January 2010
DOI 10.1007/978-1-4419-5675-0_1
Book ISBNs
978-1-4419-5674-3, 978-1-4419-5675-0
Authors

Carl van Vreeswijk

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Chile 1 3%
United States 1 3%
Unknown 26 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 48%
Researcher 4 14%
Student > Bachelor 2 7%
Student > Postgraduate 2 7%
Professor 2 7%
Other 4 14%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 41%
Neuroscience 6 21%
Engineering 3 10%
Computer Science 2 7%
Physics and Astronomy 2 7%
Other 3 10%
Unknown 1 3%