Brain Network Analysis
eBook - PDF

Brain Network Analysis

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Brain Network Analysis

About this book

This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students.

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Yes, you can access Brain Network Analysis by Moo K. Chung in PDF and/or ePUB format, as well as other popular books in Medizin & Biostatistik. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half-title
  3. Title page
  4. Copyright information
  5. Dedication
  6. Contents
  7. Preface
  8. 1 Statistical Preliminary
  9. 2 Brain Network Nodes and Edges
  10. 3 Graph Theory
  11. 4 Correlation Networks
  12. 5 Big Brain Network Data
  13. 6 Network Simulations
  14. 7 Persistent Homology
  15. 8 Diffusions on Graphs
  16. 9 Sparse Networks
  17. 10 Brain Network Distances
  18. 11 Combinatorial Inferences for Networks
  19. 12 Series Expansion of Connectivity Matrices
  20. 13 Dynamic Network Models
  21. Bibliography
  22. Index