Fundamentals of Brain Network Analysis

Alex Fornito, Andrew Zalesky, Edward T Bullmore

Research output: Book/ReportBookOtherpeer-review

229 Citations (Scopus)

Abstract

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. It is suitable for use as a reference for both researchers and students aiming to gain familiarity with the field.
Original languageEnglish
Place of PublicationSan Diego CA USA
PublisherAcademic Press
Number of pages494
Edition1
ISBN (Print)9780124079083
DOIs
Publication statusPublished - 2016

Cite this

Fornito, A., Zalesky, A., & Bullmore, E. T. (2016). Fundamentals of Brain Network Analysis. (1 ed.) Academic Press. https://doi.org/10.1016/B978-0-12-407908-3.09999-4