Analysis of Parallel Spike Trains

by Sonja Grün (Editor), Stefan Rotter (Editor)

Overview

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.

Product Details

ISBN-13:	9781441956743
Publisher:	Springer US
Publication date:	08/30/2010
Series:	Springer Series in Computational Neuroscience , #7
Edition description:	2010
Pages:	444
Product dimensions:	6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

Part I Basic Spike Train Statistics: Point Process Models

1 Stochastic Models of Spike Trains Carl van Vreeswijk 3

2 Estimating the Firing Rate Shigeru Shinomoto 21

3 Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains Martin Paul Nawrot 37

4 Processing of Phase-Locked Spikes and Periodic Signals Go Ashida Hermann Wagner Catherine E. Carr 59

Part II Pairwise Comparison of Spike Trains

5 Pair-Correlation in the Time and Frequency Domain Jos J. Eggermont 77

6 Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale Tom Tetzlaff Markus Diesmann 103

7 Spike Metrics Jonathan D. Victor Keith P. Purpura 129

8 Gravitational Clustering George Gerstein 157

Part III Multiple-Neuron Spike Patterns

9 Spatio-Temporal Patterns Moshe Abeles 175

10 Unitary Event Analysis Sonja Grün Markus Diesmann Ad Aertsen 191

11 Information Geometry of Multiple Spike Trains Shun-ichi Amari 221

12 Higher-Order Correlations and Cumulants Benjamin Staude Sonja Grün Stefan Rotter 253

Part IV Population-Based Approaches

13 Information Theory and Systems Neuroscience Don H. Johnson Ilan N. Goodman Christopher J. Rozell 283

14 Population Coding Stefano Panzeri Fernando Montani Giuseppe Notaro Cesare Magri Rasmus S. Peterson 303

15 Stochastic Models for Multivariate Neural Point Processes: Collective Dynamics and Neural Decoding Wilson Truccolo 321

Part V Practical Issues

16 Simulation of Stochastic Point Processes with Defined Properties Stefano Cardanobile Stefan Rotter 345

17 Generation and Selection of Surrogate Methods for Correlation Analysis Sebastien Louis Christian Borgelt Sonja Grün 359

18 Bootstrap Tests of Hypotheses Valérie Ventura 383

19 Generating Random Numbers Hans Ekkehard Plesser 399

20 Practically Trivial Parallel Data Processing in a Neuroscience Laboratory Michael Denker Bernd Wiebelt Denny Fliegner Markus Diesmann Abigail Morrison 413

Index 437