Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization.

• Builds a conceptual understanding on the minimum of prior knowledge by a series of chapters that lead from basic to more advanced technical issues
• Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analysis of nervous systems
• Comprehensively covers graph theoretical analysis of structural and functional brain networks from microscopic to macroscopic scales using examples based on a wide variety of experimental methods in neuroscience
• Detailed text boxes and glossary provide in-depth background to key concepts and terminology
• Designed to inform and empower scientists with all levels of experience, and from any specialist background, wanting to use the modern methods of network science to analyse the organization of the brain