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Analysis of parallel spike trains

Author: Sonja Grün; Stefan Rotter
Publisher: New York ; London : Springer, 2010.
Series: Springer series in computational neuroscience, v. 7.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Action potentials, or spikes, are the most salient expression of neuronal processing in the active brain, and they are likely an important key to understanding the neuronal mechanisms of behavior. However, it is the group dynamics of large networks of neurons that is likely to underlie brain function, and this can only be appreciated if the action potentials from multiple individual nerve cells are observed  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Analysis of parallel spike trains.
New York ; London : Springer, 2010
(OCoLC)528411076
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sonja Grün; Stefan Rotter
ISBN: 9781441956750 1441956751
OCLC Number: 668096686
Description: 1 online resource (xix, 441 pages) : illustrations (some color).
Contents: Part 1: Basic spike train statistics: Point process models Ch 1 --
Stochastic models of spike trains-Carl van Vreeswijk. Ch 2 --
Estimating the firing rate- Shigeru Shinomoto. Ch 3 --
Processing of phase-locked spikes and periodic signals- Go Ashida, Hermann Wagner and Catherine E. Carr. Ch 4 --
Analysis and interpretation of interval and count variability in neural spike trains- Martin Paul Nawrot. Part II: Pairwise comparison of spike trains. Ch 5 --
Dependence of spike-count correlations on spike-train statistics and observation time-scale- Tom Tetzlaff and Markus Diesmann. Ch 6 --
Pair-correlation in the time and frequency domain- Jos J. Eggermont. Ch 7 --
Spike metrics- Jonathan D. Victor and Keith P. Purpura. Ch8 --
Gravitational clustering- George Gerstein. Part III: Multiple-neuron spike patterns. Ch 9 --
Spatio-temporal patterns- Moshe Abeles. Ch 10 --
Unitary Events analysis- Sonja Grün, Markus Diesmann and Ad Aertsen. Ch 11 --
Information geometry of multiple spike trains- Shun-ichi Amari. Ch 12 --
Higher-order correlations and cumulants- Benjamin Staude, Sonja Grün and Stefan Rotter. Part IV: Population-based approaches. Ch13 --
Information theory and systems neuroscience- Don H. Johnson, lan N. Goodman and Christopher J. Rozell. Ch 14 --
Population coding- Stefano Panzeri, Fernando Montani, Giuseppe Notaro, Cesare Magri and Rasmus S. Petersen. Ch 15. Chastic models for multivariate neural point processes: Collective dynamics and neural decoding- Wilson Truccolo. Part V: Practical issues. Ch 15 --
Simulation of stochastic point processes with defined properties-Stefano Cardanobile and Stefan Rotter. Ch 16. Generation and selection of surrogate methods for correlation analysis-Sebastien Louis, Christian Borgelt and Sonja Grün. Ch 17 --
Bootstrap tests of hypotheses-Valerie Ventura. Ch18 --
Generating random numbers --
Hans Ekkehard Plesser. Ch 19. Practically trivial parallel data processing in a neuroscience laboratory- Michael Denker, Bernd Wiebelt, Denny Fliegner, Markus Diesmann and Abigail Morrison.
Series Title: Springer series in computational neuroscience, v. 7.
Responsibility: edited by Sonja Grün, Stefan Rotter.

Abstract:

This is the first book to collect the relevant basic knowledge on analysis of parallel spike trains in a single source. Coverage includes the first steps of stochastic point processes (SPPs) as an  Read more...

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    schema:description "Part 1: Basic spike train statistics: Point process models Ch 1 -- Stochastic models of spike trains-Carl van Vreeswijk. Ch 2 -- Estimating the firing rate- Shigeru Shinomoto. Ch 3 -- Processing of phase-locked spikes and periodic signals- Go Ashida, Hermann Wagner and Catherine E. Carr. Ch 4 -- Analysis and interpretation of interval and count variability in neural spike trains- Martin Paul Nawrot. Part II: Pairwise comparison of spike trains. Ch 5 -- Dependence of spike-count correlations on spike-train statistics and observation time-scale- Tom Tetzlaff and Markus Diesmann. Ch 6 -- Pair-correlation in the time and frequency domain- Jos J. Eggermont. Ch 7 -- Spike metrics- Jonathan D. Victor and Keith P. Purpura. Ch8 -- Gravitational clustering- George Gerstein. Part III: Multiple-neuron spike patterns. Ch 9 -- Spatio-temporal patterns- Moshe Abeles. Ch 10 -- Unitary Events analysis- Sonja Grün, Markus Diesmann and Ad Aertsen. Ch 11 -- Information geometry of multiple spike trains- Shun-ichi Amari. Ch 12 -- Higher-order correlations and cumulants- Benjamin Staude, Sonja Grün and Stefan Rotter. Part IV: Population-based approaches. Ch13 -- Information theory and systems neuroscience- Don H. Johnson, lan N. Goodman and Christopher J. Rozell. Ch 14 -- Population coding- Stefano Panzeri, Fernando Montani, Giuseppe Notaro, Cesare Magri and Rasmus S. Petersen. Ch 15. Chastic models for multivariate neural point processes: Collective dynamics and neural decoding- Wilson Truccolo. Part V: Practical issues. Ch 15 -- Simulation of stochastic point processes with defined properties-Stefano Cardanobile and Stefan Rotter. Ch 16. Generation and selection of surrogate methods for correlation analysis-Sebastien Louis, Christian Borgelt and Sonja Grün. Ch 17 -- Bootstrap tests of hypotheses-Valerie Ventura. Ch18 -- Generating random numbers -- Hans Ekkehard Plesser. Ch 19. Practically trivial parallel data processing in a neuroscience laboratory- Michael Denker, Bernd Wiebelt, Denny Fliegner, Markus Diesmann and Abigail Morrison."@en ;
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