Beschreibung

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.

• The only volume to offer a step-by-step introduction to connectomics suitable for both researchers and students. • Provides a general overview, discussion of various issues involved in using neuroimaging to build a connectomic map, the main measures used to analyze connectomic data, an intro to advanced topics in the field, and discussion of as yet unresolved issues and future directions. • Helps readers determine how they can best use fMRI/DTI data to make a brain network, how they can analyze that network using graph theory, and how they can compare/interpret their findings across different groups • Assumes no prior knowledge beyond basic training in human MRI, and adopts a consistent format across chapters to facilitate learning and linking of different concepts

Alex Fornito completed a PhD in the Departments of Psychology and Psychiatry at the University of Melbourne, Australia, followed by Post-Doctoral training at the University of Cambridge, UK. He is currently an Associate Professor and Australian Research Council Future Fellow in the Brain and Mental Health Laboratory of the Institute of Cognitive and Clinical Science, Monash University. Alex's research uses the tools of cognitive neuroscience, network science and graph theory to understand brain network organization in health and disease. In particular, his work focuses on developing and applying new techniques to understand how brain networks dynamically adapt to changing task demands, how they are disrupted by disease, and how they are shaped by genetic influences.

Autorentext

Alex Fornito completed a PhD in the Departments of Psychology and Psychiatry at the University of Melbourne, Australia, followed by Post-Doctoral training at the University of Cambridge, UK. He is an associate professor, Australian Research Council Future Fellow, and Deputy Director of the Brain and Mental Health Laboratory in the Monash Institute of Cognitive and Clinical Neurosciences, Australia. Alex's research uses cognitive neuroscience, network science, and graph theory to understand brain network organization in health and disease. He has published over 100 scientific articles, much of which are focused on the development and application of new methods to understand how brain networks dynamically adapt to changing task demands, how they are disrupted by disease, and how they are shaped by genetic influences.

Klappentext

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.

• Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology
• Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems
• Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience
• Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain

Inhalt

1. An introduction to brain networks 2. Nodes and edges 3. Connectivity matrices and brain graphs 4. Connectivity degree and strength 5. Centrality and hubs 6. Components, cores and clubs 7. Paths, efficiency and diffusion 8. Motifs, small worlds and network economy 9. Modularity 10. Null models 11. Statistical connectomics

Produktinformationen

Titel:	Fundamentals of Brain Network Analysis
Autor:	Alex Fornito   Andrew Zalesky   Edward Bullmore
EAN:	9780124081185
Digitaler Kopierschutz:	Adobe-DRM
Format:	E-Book (epub)
Hersteller:	Elsevier Science & Techn.
Genre:	Medizin
Anzahl Seiten:	494
Veröffentlichung:	04.03.2016
Dateigrösse:	20.6 MB