Computational And Network Modeling Of Neuroimaging Data
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Computational And Network Modeling Of Neuroimaging Data
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Author : Kendrick Kay
language : en
Publisher: Elsevier
Release Date : 2024-06-17
Computational And Network Modeling Of Neuroimaging Data written by Kendrick Kay and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-17 with Science categories.
Neuroimaging is witnessing a massive increase in the quality and quantity of data being acquired. It is widely recognized that effective interpretation and extraction of information from such data requires quantitative modeling. However, modeling comes in many diverse forms, with different research communities tackling different brain systems, different spatial and temporal scales, and different aspects of brain structure and function. Computational and Network Modeling of Neuroimaging Data provides an authoritative and comprehensive overview of the many diverse modeling approaches that have been fruitfully applied to neuroimaging data. This book gives an accessible foundation to the field of computational and network modeling of neuroimaging data and is suitable for graduate students, academic researchers, and industry practitioners who are interested in adopting or applying model-based approaches in neuroimaging. - Provides an authoritative and comprehensive overview of major modeling approaches to neuroimaging data - Written by experts, the book's chapters use a common structure to introduce, motivate, and describe a specific modeling approach used in neuroimaging - Gives insights into the similarities and differences across different modeling approaches - Analyses details of outstanding research challenges in the field
Advanced Data Analysis In Neuroscience
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Author : Daniel Durstewitz
language : en
Publisher: Springer
Release Date : 2017-09-15
Advanced Data Analysis In Neuroscience written by Daniel Durstewitz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-15 with Medical categories.
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck
The Dynamic Brain
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Author : Mingzhou Ding
language : en
Publisher:
Release Date : 2011
The Dynamic Brain written by Mingzhou Ding and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Medical categories.
Theoretical, experimental and clinical perspectives. Readership: Graduate students, postdocs and research scientists in Neuroscience.
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.
Neuroimaging
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Author : Peter Bright
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-02-17
Neuroimaging written by Peter Bright and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-17 with Medical categories.
Neuroimaging methodologies continue to develop at a remarkable rate, providing ever more sophisticated techniques for investigating brain structure and function. The scope of this book is not to provide a comprehensive overview of methods and applications but to provide a 'snapshot' of current approaches using well established and newly emerging techniques. Taken together, these chapters provide a broad sense of how the limits of what is achievable with neuroimaging methods are being stretched.
Handbook Of Neuroimaging Data Analysis
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Author : Hernando Ombao
language : en
Publisher: CRC Press
Release Date : 2016-11-18
Handbook Of Neuroimaging Data Analysis written by Hernando Ombao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-18 with Mathematics categories.
This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.
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
Psychiatric Neuroimaging
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Author : Virginia Ng
language : en
Publisher: IOS Press
Release Date : 2003
Psychiatric Neuroimaging written by Virginia Ng and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Machine Learning And Deep Learning In Neuroimaging Data Analysis
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Author : Anitha S. Pillai
language : en
Publisher: CRC Press
Release Date : 2024-02-15
Machine Learning And Deep Learning In Neuroimaging Data Analysis written by Anitha S. Pillai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-15 with Computers categories.
Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.
Medical Image Computing And Computer Assisted Intervention Miccai 2013
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Author : Kensaku Mori
language : en
Publisher: Springer
Release Date : 2013-09-20
Medical Image Computing And Computer Assisted Intervention Miccai 2013 written by Kensaku Mori and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-20 with Computers categories.
The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications.