Analysis of Parallel Spike Trains

By: Sonja GrÃ¼n (Editor), Stefan Rotter (Editor)

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Hardcover | 30 August 2010

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464 Pages

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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.

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Non-Fiction Medicine Clinical & Internal Medicine Neurology & Clinical Neurophysiology Science Biology, Life Sciences Life Sciences in General Neurosciences Pre-Clinical Medicine & Basic Sciences Zoology & Animal Sciences

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Published: 13th October 2012

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Basic Spike Train Statistics: Point Process Models
Stochastic Models of Spike Trains	p. 3
Estimating the Firing Rate	p. 21
Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains	p. 37
Processing of Phase-Locked Spikes and Periodic Signals	p. 59
Pairwise Comparison of Spike Trains
Pair-Correlation in the Time and Frequency Domain	p. 77
Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale	p. 103
Spike Metrics	p. 129
Gravitational Clustering	p. 157
Multiple-Neuron Spike Patterns
Spatio-Temporal Patterns	p. 175
Unitary Event Analysis	p. 191
Information Geometry of Multiple Spike Trains	p. 221
Higher-Order Correlations and Cumulants	p. 253
Population-Based Approaches
Information Theory and Systems Neuroscience	p. 283
Population Coding	p. 303
Stochastic Models for Multivariate Neural Point Processes: Collective Dynamics and Neural Decoding	p. 321
Practical Issues
Simulation of Stochastic Point Processes with Defined Properties	p. 345
Generation and Selection of Surrogate Methods for Correlation Analysis	p. 359
Bootstrap Tests of Hypotheses	p. 383
Generating Random Numbers	p. 399
Practically Trivial Parallel Data Processing in a Neuroscience Laboratory	p. 413
Index	p. 437
Table of Contents provided by Ingram. All Rights Reserved.

Analysis of Parallel Spike Trains

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