Analysis of Parallel Spike Trains

Editors:

ISBN: 978-1-4419-5674-3 (Print) 978-1-4419-5675-0 (Online)

Table of contents (22 chapters)

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  1. Front Matter

    Pages I-XIX

  2. Basic spike train statistics: Point process models

    1. Front Matter

      Pages 1-1

    2. No Access

      Book Chapter

      Pages 3-20

      Stochastic Models of Spike Trains

    3. No Access

      Book Chapter

      Pages 21-35

      Estimating the Firing Rate

    4. No Access

      Book Chapter

      Pages 37-58

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

    5. No Access

      Book Chapter

      Pages 59-74

      Processing of Phase-Locked Spikes and Periodic Signals

  3. Pairwise comparison of spike trains

    1. Front Matter

      Pages 75-75

    2. No Access

      Book Chapter

      Pages 77-102

      Pair-Correlation in the Time and Frequency Domain

    3. No Access

      Book Chapter

      Pages 103-127

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

    4. No Access

      Book Chapter

      Pages 129-156

      Spike Metrics

    5. No Access

      Book Chapter

      Pages 157-172

      Gravitational Clustering

  4. Multiple-neuron spike patterns

    1. Front Matter

      Pages 173-173

    2. No Access

      Book Chapter

      Pages 175-189

      Spatio-Temporal Patterns

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      Book Chapter

      Pages 191-220

      Unitary Event Analysis

    4. No Access

      Book Chapter

      Pages 221-252

      Information Geometry of Multiple Spike Trains

    5. No Access

      Book Chapter

      Pages 253-280

      Higher-Order Correlations and Cumulants

  5. Population-based approaches

    1. Front Matter

      Pages 281-281

    2. No Access

      Book Chapter

      Pages 283-301

      Information Theory and Systems Neuroscience

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      Book Chapter

      Pages 303-319

      Population Coding

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      Book Chapter

      Pages 321-341

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

  6. Practical issues

    1. Front Matter

      Pages 343-343

    2. No Access

      Book Chapter

      Pages 345-357

      Simulation of Stochastic Point Processes with Defined Properties

    3. No Access

      Book Chapter

      Pages 359-382

      Generation and Selection of Surrogate Methods for Correlation Analysis

    4. No Access

      Book Chapter

      Pages 383-398

      Bootstrap Tests of Hypotheses

    5. No Access

      Book Chapter

      Pages 399-411

      Generating Random Numbers

    6. No Access

      Book Chapter

      Pages 413-436

      Practically Trivial Parallel Data Processing in a Neuroscience Laboratory

  7. Back Matter

    Pages 439-443

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