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Analysis of Parallel Spike Trains

  • Book
  • © 2010

Overview

Editors:
  1. Sonja Grün

    1. Computational Neuroscience Group, RIKEN Brain Science Institute, Saitama, Japan

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    You can also search for this editor in PubMed   Google Scholar

  2. Stefan Rotter

    1. Bernstein-Zentrum für Computational Neur, Neuroscience, Universität Freiburg, Freiburg, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • This first textbook on spike train analysis
  • Supplies the reader with stochastic modeling tools and numerical methods.
  • Highlights various prerequisites and pitfalls to avoid potentially wrong interpretations of data.
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Series in Computational Neuroscience (NEUROSCI, volume 7)

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Table of contents (21 chapters)

  1. Front Matter

    Pages I-XIX
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  2. Basic Spike Train Statistics: Point Process Models

    1. Front Matter

      Pages 1-1
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  3. Basic spike train statistics: Point process models

    1. Stochastic Models of Spike Trains

      • Carl van Vreeswijk
      Pages 3-20

    2. Estimating the Firing Rate

      • Shigeru Shinomoto
      Pages 21-35

    3. Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains

      • Martin Paul Nawrot
      Pages 37-58

    4. Processing of Phase-Locked Spikes and Periodic Signals

      • Go Ashida, Hermann Wagner, Catherine E. Carr
      Pages 59-74

  4. Pairwise Comparison of Spike Trains

    1. Front Matter

      Pages 75-75
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  5. Pairwise comparison of spike trains

    1. Pair-Correlation in the Time and Frequency Domain

      • Jos J. Eggermont
      Pages 77-102

    2. Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale

      • Tom Tetzlaff, Markus Diesmann
      Pages 103-127

    3. Spike Metrics

      • Jonathan D. Victor, Keith P. Purpura
      Pages 129-156

    4. Gravitational Clustering

      • George Gerstein
      Pages 157-172

  6. Multiple-Neuron Spike Patterns

    1. Front Matter

      Pages 173-173
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  7. Multiple-neuron spike patterns

    1. Spatio-Temporal Patterns

      • Moshe Abeles
      Pages 175-189

    2. Unitary Event Analysis

      • Sonja Grün, Markus Diesmann, Ad Aertsen
      Pages 191-220

    3. Information Geometry of Multiple Spike Trains

      • Shun-ichi Amari
      Pages 221-252

    4. Higher-Order Correlations and Cumulants

      • Benjamin Staude, Sonja Grün, Stefan Rotter
      Pages 253-280

  8. Population-Based Approaches

    1. Front Matter

      Pages 281-281
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  9. Population-based approaches

    1. Information Theory and Systems Neuroscience

      • Don H. Johnson, Ilan N. Goodman, Christopher J. Rozell
      Pages 283-301

    2. Population Coding

      • Stefano Panzeri, Fernando Montani, Giuseppe Notaro, Cesare Magri, Rasmus S. Peterson
      Pages 303-319

    3. Stochastic Models for Multivariate Neural Point Processes: Collective Dynamics and Neural Decoding

      • Wilson Truccolo
      Pages 321-341
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Keywords

About this book

Solid and transparent data analysis is the most important basis for reliable interpretation of experiments. The technique of parallel spike train recordings using multi-electrode arrangements has been available for many decades now, but only recently gained wide popularity among electro physiologists. Many traditional analysis methods are based on firing rates obtained by trial-averaging, and some of the assumptions for such procedures to work can be ignored without serious consequences. The situation is different for correlation analysis, the result of which may be considerably distorted if certain critical assumptions are violated. The focus of this book is on concepts and methods of correlation analysis (synchrony, patterns, rate covariance), combined with a solid introduction into approaches for single spike trains, which represent the basis of correlations analysis. The book also emphasizes pitfalls and potential wrong interpretations of data due to violations of critical assumptions.

Editors and Affiliations

  • Computational Neuroscience Group, RIKEN Brain Science Institute, Saitama, Japan

    Sonja Grün

  • Bernstein-Zentrum für Computational Neur, Neuroscience, Universität Freiburg, Freiburg, Germany

    Stefan Rotter

Bibliographic Information

  • Book Title: Analysis of Parallel Spike Trains

  • Editors: Sonja Grün, Stefan Rotter

  • Series Title: Springer Series in Computational Neuroscience

  • DOI: https://doi.org/10.1007/978-1-4419-5675-0

  • Publisher: Springer New York, NY

  • eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)

  • Copyright Information: Springer Science+Business Media, LLC 2010

  • Hardcover ISBN: 978-1-4419-5674-3Published: 30 August 2010

  • Softcover ISBN: 978-1-4614-2652-3Published: 13 October 2012

  • eBook ISBN: 978-1-4419-5675-0Published: 18 August 2010

  • Series ISSN: 2197-1900

  • Series E-ISSN: 2197-1919

  • Edition Number: 1

  • Number of Pages: XX, 444

  • Topics: Neurosciences, Neurobiology

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