Connectome Analysis: Characterization, Methods, and Analysis is a comprehensive companion for the analysis of brain networks, or connectomes. The book provides sources of constituent structural and functional MRI signals, network construction and practices for analysis, cutting-edge methods that address the latest challenges in neuroscience, and the fundamentals of network theory in the context of giving practical methods for building connectomes for analysis. Emphasis is placed on quality control of the individual analysis steps. Subsequent chapters discuss networks in neuroscience in clinical and general populations, including how findings are related to underlying neurophysiology and neuropsychology.
This book is aimed at students and early-career researchers in brain connectomics and neuroimaging who have a background in computer science, mathematics and physics, as well as more broadly to neuroscientists and psychologists who want to start incorporating connectomics into their research.
Key Features
- Provides practical recommendations on how to construct, assess and analyze brain networks
- Gives an understanding of all the technical methods for connectome analysis
- Presents the basic network theoretical principles typically used in neuroscience
- Covers the latest tools and data repositories that are freely available for the reader to carry out connectomic analyses
Chapter 1 - Neurobiology and the connectome
Chapter 2 - Structural network construction using diffusion MRI
Chapter 3 - Functional network construction using functional MRI
Chapter 4 - Network nodes in the brain
Chapter 5 - Network measures and null models
Chapter 6 - Hubs and rich clubs
Chapter 7 - Community detection in network neuroscience
Chapter 8 - Network comparisons and their applications in connectomics
Section II: Advanced concepts and methods
Chapter 9 - Beyond the shortest path—diffusion-based routing strategies
Chapter 10 - Dynamic functional connectivity
Chapter 11 - The synergy of structural and functional connectivity
Chapter 12 - Machine learning in connectomics: from representation learning to model fitting
Chapter 13 - Deep learning with connectomes
Chapter 14 - Uncovering the genetics of the human connectome
Section III: Applications in the human brain
Chapter 15 - The developmental connectome
Chapter 16 - Connectomics in aging and cognition
Chapter 17 - Networks with lesions
Chapter 18 - Clinical application of connectomics to disorders of consciousness
Chapter 19 - Connectome analysis and psychiatric disorders
