دانلود کتاب اصول تجزیه و تحلیل شبکه مغز
Fundamentals of Brain Network Analysis, 1ed

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.

Ed Bullmore trained in medicine at the University of Oxford and St Bartholomew’s Hospital, London, and then in psychiatry at the Bethlem Royal and Maudsley Hospital, London. In 1993, he was a Wellcome Trust (Advanced) Research Fellow at the Institute of Psychiatry, King’s College London, where he completed a PhD in the statistical analysis of MRI data, before moving to Cambridge as Professor of Psychiatry in 1999. Currently, he is co-Chair of Cambridge Neuroscience, Scientific Director of the Wolfson Brain Imaging Centre, and Head of the Department of Psychiatry in the University of Cambridge. He is also an honorary Consultant Psychiatrist, and Director of R&D in Cambridgeshire and Peterborough Foundation NHS Trust. Since 2005, he has worked half-time for GlaxoSmithKline, currently focusing on immuno-psychiatry. He has been elected as a Fellow of the Royal College of Physicians, the Royal College of Psychiatrists, and the Academy of Medical Sciences. He has published about 500 scientific papers, and his work has been highly cited. He has played an internationally-leading role in understanding brain connectivity and networks by graph theoretical analysis of neuroimaging and other neuroscientific datasets.