Analysis of Parallel Spike Trains

1. Front Matter

   Pages I-XIX

   PDF

2. Basic Spike Train Statistics: Point Process Models

   1. Front Matter

      Pages 1-1

      PDF

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

      PDF

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

      PDF

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

      PDF

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

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.

• Computerassistierte Detektion
• Radiologieinformationssystem
• correlation
• neural coding
• neural ensembles
• point processes
• spike patterns
• statistics

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

  Sonja Grün

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

  Stefan Rotter

Policies and ethics