BookSonja Grün, Stefan Rotter, editors.
Contents:
Part I: Basic Spike Train Statistics
1 Stochastic Models of Spike Trains
2 Estimating the Firing Rate
3 Analysis and Interpretation of Interval and Count Variability in Neural Spike Trains
4 Processing of Phase-Locked Spikes and Periodic Signals
Part II: Pairwise Comparison of Spike Trains
5 Pair-Correlation in the Time and Frequency Domain
6 Dependence of Spike-Count Correlations on Spike-Train Statistics and Observation Time Scale
7 Spike Metrics
8 Gravitational Clustering
Part III: Multiple-Neuron Spike Patterns
9 Spatio-Temporal Patterns
10 Unitary Event Analysis
11 Information Geometry of Multiple Spike Trains
12 Higher-Order Correlations and Cumulants
Part IV: Population-Based Approaches
13 Information Theory and Systems Neuroscience
14 Population Coding
15 Stochastic Models for Multivariate Neural Point Processes: Collective Dynamics and Neural Decoding
Part V: Practical Issues
16 Simulation of Stochastic Point Processes with Defined Properties
17 Generation and Selection of Surrogate Methods for Correlation Analysis
18 Bootstrap Tests of Hypotheses
19 Generating Random Numbers
20 Practically Trivial Parallel Data Processing in a Neuroscience Laboratory
Index.