![]() Chapter 7: Paths, Diffusion, and Navigation.Chapter 6: Components, Cores, and Clubs.3.4 What Type of Network Is a Connectome?.Chapter 3: Connectivity Matrices and Brain Graphs.1.3 Are graph theory and connectomics useful?.1.1 Graphs as Models for Complex Systems.Chapter 1: An Introduction to Brain Networks.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. 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. ![]() 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. Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity.
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