Analysis of Neural Data

  • Robert E. Kass
  • Uri T. Eden
  • Emery N. Brown
Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xxv
  2. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 1-22
  3. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 23-35
  4. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 37-69
  5. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 71-104
  6. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 105-135
  7. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 137-148
  8. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 149-178
  9. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 179-220
  10. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 221-246
  11. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 247-286
  12. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 287-307
  13. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 309-359
  14. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 361-389
  15. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 391-412
  16. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 413-438
  17. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 439-489
  18. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 491-512
  19. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 513-561
  20. Robert E. Kass, Uri T. Eden, Emery N. Brown
    Pages 563-603

About this book

Introduction

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Keywords

Data Analysis for Neuroscience Mathematics for Neuroscience Neuroscience Data Statistical Models Brain Sciences Statistics Brain Sciences Statistics Neuroscience

Authors and affiliations

  • Robert E. Kass
    • 1
  • Uri T. Eden
    • 2
  • Emery N. Brown
    • 3
  1. 1.Carnegie Mellon UniversityPittsburghUSA
  2. 2.Boston UniversityBostonUSA
  3. 3.Massachusetts Institute of TechnologyCambridgeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-9602-1
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-1-4614-9601-4
  • Online ISBN 978-1-4614-9602-1
  • Series Print ISSN 0172-7397
  • Series Online ISSN 2197-568X
  • About this book