Fundamentals Of Brain Network Analysis
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Fundamentals Of Brain Network Analysis
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Author : Alex Fornito
language : en
Publisher: Academic Press
Release Date : 2016-03-04
Fundamentals Of Brain Network Analysis written by Alex Fornito and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-04 with Medical categories.
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
Brain Network Analysis
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Author : Moo K. Chung
language : en
Publisher: Cambridge University Press
Release Date : 2019-06-27
Brain Network Analysis written by Moo K. Chung and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-27 with Computers categories.
This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.
Networks Of The Brain
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Author : Olaf Sporns
language : en
Publisher: MIT Press
Release Date : 2016-02-12
Networks Of The Brain written by Olaf Sporns and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-12 with Medical categories.
An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.
Fundamentals Of Neural Network Modeling
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Author : Randolph W. Parks
language : en
Publisher: MIT Press
Release Date : 1998
Fundamentals Of Neural Network Modeling written by Randolph W. Parks and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble
Discovering The Human Connectome
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Author : Olaf Sporns
language : en
Publisher: MIT Press
Release Date : 2012-08-31
Discovering The Human Connectome written by Olaf Sporns and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-31 with Medical categories.
A pioneer in the field outlines new empirical and computational approaches to mapping the neural connections of the human brain. Crucial to understanding how the brain works is connectivity, and the centerpiece of brain connectivity is the connectome, a comprehensive description of how neurons and brain regions are connected. In this book, Olaf Sporns surveys current efforts to chart these connections—to map the human connectome. He argues that the nascent field of connectomics has already begun to influence the way many neuroscientists collect, analyze, and think about their data. Moreover, the idea of mapping the connections of the human brain in their entirety has captured the imaginations of researchers across several disciplines including human cognition, brain and mental disorders, and complex systems and networks. Discovering the Human Connectome offers the first comprehensive overview of current empirical and computational approaches in this rapidly developing field.
An Introduction To Resting State Fmri Functional Connectivity
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Author : Janine Bijsterbosch
language : en
Publisher: Oxford University Press
Release Date : 2017
An Introduction To Resting State Fmri Functional Connectivity written by Janine Bijsterbosch and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Medical categories.
For those new to the field of resting state fMRI, the large variety of approaches to functional connectivity analysis is highly confusing. This primer provides an introduction to the concepts and analysis decisions that need to be made at every step of the processing pipeline, starting from data acquisition through to interpretation of findings.
Social Network Analysis For Startups
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Author : Maksim Tsvetovat
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2011-10-06
Social Network Analysis For Startups written by Maksim Tsvetovat and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-06 with Business & Economics categories.
Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you'll learn concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You'll also learn how to use Python and other open source tools—such as NetworkX, NumPy, and Matplotlib—to gather, analyze, and visualize social data. This book is the perfect marriage between social network theory and practice, and a valuable source of insight and ideas. Discover how internal social networks affect a company’s ability to perform Follow terrorists and revolutionaries through the 1998 Khobar Towers bombing, the 9/11 attacks, and the Egyptian uprising Learn how a single special-interest group can control the outcome of a national election Examine relationships between companies through investment networks and shared boards of directors Delve into the anatomy of cultural fads and trends—offline phenomena often mediated by Twitter and Facebook
Statistical Parametric Mapping The Analysis Of Functional Brain Images
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Author : William D. Penny
language : en
Publisher: Elsevier
Release Date : 2011-04-28
Statistical Parametric Mapping The Analysis Of Functional Brain Images written by William D. Penny and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-28 with Psychology categories.
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Statistical And Computational Methods In Brain Image Analysis
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Author : Moo K. Chung
language : en
Publisher: CRC Press
Release Date : 2013-07-23
Statistical And Computational Methods In Brain Image Analysis written by Moo K. Chung and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-23 with Mathematics categories.
The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.