Computational Methods For Neuroscience Discovery With Neuroimaging Data

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Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence

Author : Indranath Chatterjee
Publisher : CRC Press
ISBN 13 : 1040216293
Total Pages : 273 pages
Book Rating : 4.0/5 (42 download)

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Book Synopsis Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence by : Indranath Chatterjee

Download or read book Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence written by Indranath Chatterjee and published by CRC Press. This book was released on 2024-12-18 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unveil the next frontier in neurodegenerative disorder research with Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence. This groundbreaking book goes beyond traditional approaches, utilizing the power of interdisciplinary integration to illuminate new pathways in diagnosis and treatment. From AI-driven diagnostics to computational neuroscience models, this book showcases the forefront of innovation. Join us in exploring the future of neurodegenerative care, where collaboration and cutting-edge technology converge to redefine possibilities. Key Features: Integrates diverse fields of research, from neuroimaging to computational neuroscience and Artificial Intelligence. Emphasizes the translation of research findings into practical applications, ultimately benefitting patients and clinical practice. Reviews the implementation of Artificial Intelligence and computational models in diagnostic settings. Elucidates the current state of translational neuroscience exploring potential areas for further research and collaboration, including personalized treatments and drug development. Contributions from an international team of experts from diverse disciplines.

Advanced Data Analysis in Neuroscience

Author : Daniel Durstewitz
Publisher : Springer
ISBN 13 : 3319599763
Total Pages : 308 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Advanced Data Analysis in Neuroscience by : Daniel Durstewitz

Download or read book Advanced Data Analysis in Neuroscience written by Daniel Durstewitz and published by Springer. This book was released on 2017-09-15 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Advanced Computational Intelligence Methods for Processing Brain Imaging Data

Author : Kaijian Xia
Publisher : Frontiers Media SA
ISBN 13 : 2832504620
Total Pages : 754 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Advanced Computational Intelligence Methods for Processing Brain Imaging Data by : Kaijian Xia

Download or read book Advanced Computational Intelligence Methods for Processing Brain Imaging Data written by Kaijian Xia and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Implementing Reproducible Research

Author : Victoria Stodden
Publisher : CRC Press
ISBN 13 : 1466561599
Total Pages : 450 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Implementing Reproducible Research by : Victoria Stodden

Download or read book Implementing Reproducible Research written by Victoria Stodden and published by CRC Press. This book was released on 2014-04-14 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.

Computational and Network Modeling of Neuroimaging Data

Author : Kendrick Kay
Publisher : Elsevier
ISBN 13 : 0443134812
Total Pages : 356 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Computational and Network Modeling of Neuroimaging Data by : Kendrick Kay

Download or read book Computational and Network Modeling of Neuroimaging Data written by Kendrick Kay and published by Elsevier. This book was released on 2024-06-17 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

The Practice of Reproducible Research

Author : Justin Kitzes
Publisher : Univ of California Press
ISBN 13 : 0520294742
Total Pages : 364 pages
Book Rating : 4.5/5 (22 download)

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Book Synopsis The Practice of Reproducible Research by : Justin Kitzes

Download or read book The Practice of Reproducible Research written by Justin Kitzes and published by Univ of California Press. This book was released on 2018 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.

Fundamentals of Brain Network Analysis

Author : Alex Fornito
Publisher : Academic Press
ISBN 13 : 0124081185
Total Pages : 496 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Fundamentals of Brain Network Analysis by : Alex Fornito

Download or read book Fundamentals of Brain Network Analysis written by Alex Fornito and published by Academic Press. This book was released on 2016-03-04 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Bayesian Estimation and Inference in Computational Anatomy and Neuroimaging: Methods & Applications

Author : Xiaoying Tang
Publisher : Frontiers Media SA
ISBN 13 : 2889459845
Total Pages : 118 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Bayesian Estimation and Inference in Computational Anatomy and Neuroimaging: Methods & Applications by : Xiaoying Tang

Download or read book Bayesian Estimation and Inference in Computational Anatomy and Neuroimaging: Methods & Applications written by Xiaoying Tang and published by Frontiers Media SA. This book was released on 2019-08-22 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Anatomy (CA) is an emerging discipline aiming to understand anatomy by utilizing a comprehensive set of mathematical tools. CA focuses on providing precise statistical encodings of anatomy with direct application to a broad range of biological and medical settings. During the past two decades, there has been an ever-increasing pace in the development of neuroimaging techniques, delivering in vivo information on the anatomy and physiological signals of different human organs through a variety of imaging modalities such as MRI, x-ray, CT, and PET. These multi-modality medical images provide valuable data for accurate interpretation and estimation of various biological parameters such as anatomical labels, disease types, cognitive states, functional connectivity between distinct anatomical regions, as well as activation responses to specific stimuli. In the era of big neuroimaging data, Bayes’ theorem provides a powerful tool to deliver statistical conclusions by combining the current information and prior experience. When sufficiently good data is available, Bayes’ theorem can utilize it fully and provide statistical inferences/estimations with the least error rate. Bayes’ theorem arose roughly three hundred years ago and has seen extensive application in many fields of science and technology, including recent neuroimaging, ever since. The last fifteen years have seen a great deal of success in the application of Bayes’ theorem to the field of CA and neuroimaging. That said, given that the power and success of Bayes’ rule largely depends on the validity of its probabilistic inputs, it is still a challenge to perform Bayesian estimation and inference on the typically noisy neuroimaging data of the real world. We assembled contributions focusing on recent developments in CA and neuroimaging through Bayesian estimation and inference, in terms of both methodologies and applications. It is anticipated that the articles in this Research Topic will provide a greater insight into the field of Bayesian imaging analysis.

Fundamentals of Neural Network Modeling

Author : Randolph W. Parks
Publisher : MIT Press
ISBN 13 : 9780262161756
Total Pages : 450 pages
Book Rating : 4.1/5 (617 download)

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Book Synopsis Fundamentals of Neural Network Modeling by : Randolph W. Parks

Download or read book Fundamentals of Neural Network Modeling written by Randolph W. Parks and published by MIT Press. This book was released on 1998 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Machine Learning and Medical Imaging

Author : Guorong Wu
Publisher : Academic Press
ISBN 13 : 0128041145
Total Pages : 514 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Machine Learning and Medical Imaging by : Guorong Wu

Download or read book Machine Learning and Medical Imaging written by Guorong Wu and published by Academic Press. This book was released on 2016-08-11 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. - Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems - Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics - Features self-contained chapters with a thorough literature review - Assesses the development of future machine learning techniques and the further application of existing techniques

Computational Methods for Translational Brain-Behavior Analysis

Author : Rong Chen
Publisher : Frontiers Media SA
ISBN 13 : 2889668975
Total Pages : 147 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Computational Methods for Translational Brain-Behavior Analysis by : Rong Chen

Download or read book Computational Methods for Translational Brain-Behavior Analysis written by Rong Chen and published by Frontiers Media SA. This book was released on 2021-06-24 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Guide to Research Techniques in Neuroscience

Author : Matt Carter
Publisher : Academic Press
ISBN 13 : 0323915612
Total Pages : 416 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Guide to Research Techniques in Neuroscience by : Matt Carter

Download or read book Guide to Research Techniques in Neuroscience written by Matt Carter and published by Academic Press. This book was released on 2022-03-26 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern neuroscience research is inherently multidisciplinary, with a wide variety of cutting edge new techniques to explore multiple levels of investigation. This Third Edition of Guide to Research Techniques in Neuroscience provides a comprehensive overview of classical and cutting edge methods including their utility, limitations, and how data are presented in the literature. This book can be used as an introduction to neuroscience techniques for anyone new to the field or as a reference for any neuroscientist while reading papers or attending talks. - Nearly 200 updated full-color illustrations to clearly convey the theory and practice of neuroscience methods - Expands on techniques from previous editions and covers many new techniques including in vivo calcium imaging, fiber photometry, RNA-Seq, brain spheroids, CRISPR-Cas9 genome editing, and more - Clear, straightforward explanations of each technique for anyone new to the field - A broad scope of methods, from noninvasive brain imaging in human subjects, to electrophysiology in animal models, to recombinant DNA technology in test tubes, to transfection of neurons in cell culture - Detailed recommendations on where to find protocols and other resources for specific techniques - "Walk-through" boxes that guide readers through experiments step-by-step

Statistical Parametric Mapping: The Analysis of Functional Brain Images

Author : William D. Penny
Publisher : Elsevier
ISBN 13 : 0080466508
Total Pages : 689 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Statistical Parametric Mapping: The Analysis of Functional Brain Images by : William D. Penny

Download or read book Statistical Parametric Mapping: The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Cognitive Neuroscience

Author : Marie T. Banich
Publisher : Cambridge University Press
ISBN 13 : 1108924336
Total Pages : 671 pages
Book Rating : 4.1/5 (89 download)

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Book Synopsis Cognitive Neuroscience by : Marie T. Banich

Download or read book Cognitive Neuroscience written by Marie T. Banich and published by Cambridge University Press. This book was released on 2023-09-30 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and updated, this comprehensive text covers key concepts in cognitive neuroscience. Written by two active researchers and experienced teachers, the coverage is both up to date and accessible with clear links made across chapters. Clinical applications, case studies and examples demonstrate the real-world significance of the science.

Cognitive and Computational Neuroscience

Author : Seyyed Abed Hosseini
Publisher : BoD – Books on Demand
ISBN 13 : 1789231884
Total Pages : 106 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Cognitive and Computational Neuroscience by : Seyyed Abed Hosseini

Download or read book Cognitive and Computational Neuroscience written by Seyyed Abed Hosseini and published by BoD – Books on Demand. This book was released on 2018-05-30 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book "Cognitive and Computational Neuroscience - Principles, Algorithms and Applications" will answer the following question and statements: System-level neural modeling: what and why? We know a lot about the brain! Need to integrate data: molecular/cellular/system levels. Complexity: need to abstract away higher-order principles. Models are tools to develop explicit theories, constrained by multiple levels (neural and behavioral). Key: models (should) make novel testable predictions on both neural and behavioral levels. Models are useful tools for guiding experiments. The hope is that the information provided in this book will trigger new researches that will help to connect basic neuroscience to clinical medicine.

The Cognitive Neurosciences, sixth edition

Author : David Poeppel
Publisher : MIT Press
ISBN 13 : 0262043254
Total Pages : 1241 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Cognitive Neurosciences, sixth edition by : David Poeppel

Download or read book The Cognitive Neurosciences, sixth edition written by David Poeppel and published by MIT Press. This book was released on 2020-04-21 with total page 1241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sixth edition of the foundational reference on cognitive neuroscience, with entirely new material that covers the latest research, experimental approaches, and measurement methodologies. Each edition of this classic reference has proved to be a benchmark in the developing field of cognitive neuroscience. The sixth edition of The Cognitive Neurosciences continues to chart new directions in the study of the biological underpinnings of complex cognition—the relationship between the structural and physiological mechanisms of the nervous system and the psychological reality of the mind. It offers entirely new material, reflecting recent advances in the field, covering the latest research, experimental approaches, and measurement methodologies. This sixth edition treats such foundational topics as memory, attention, and language, as well as other areas, including computational models of cognition, reward and decision making, social neuroscience, scientific ethics, and methods advances. Over the last twenty-five years, the cognitive neurosciences have seen the development of sophisticated tools and methods, including computational approaches that generate enormous data sets. This volume deploys these exciting new instruments but also emphasizes the value of theory, behavior, observation, and other time-tested scientific habits. Section editors Sarah-Jayne Blakemore and Ulman Lindenberger, Kalanit Grill-Spector and Maria Chait, Tomás Ryan and Charan Ranganath, Sabine Kastner and Steven Luck, Stanislas Dehaene and Josh McDermott, Rich Ivry and John Krakauer, Daphna Shohamy and Wolfram Schultz, Danielle Bassett and Nikolaus Kriegeskorte, Marina Bedny and Alfonso Caramazza, Liina Pylkkänen and Karen Emmorey, Mauricio Delgado and Elizabeth Phelps, Anjan Chatterjee and Adina Roskies

Neuroimaging Part A

Author :
Publisher : Elsevier
ISBN 13 : 008047859X
Total Pages : 347 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Neuroimaging Part A by :

Download or read book Neuroimaging Part A written by and published by Elsevier. This book was released on 2005-11-11 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consisting of two separate volumes, Neuroimaging provides a state-of-the-art review of a broad range of neuroimaging techniques applied to both clinical and research settings. The breadth of the methods covered is matched by the depth of description of the theoretical background. Part A focuses on the cutting edge of research methodologies, providing a foundation for both established and evolving techniques. These include voxel-based morphometry using structural MRI, functional MRI, perfusion MRI, diffusion tensor imaging, near-infrared spectroscopy and the technique of combining EEG and fMRI studies. Two chapters are devoted to describing methods for studying brain responses and neural models, focusing on functional connectivity, effective connectivity, dynamic causal modeling, and large-scale neural models. The important role played by brain atlases in facilitating the study of normal and diseased brain populations is described in one chapter, and the concept of neuroimaging data bases as a future resource for scientific discovery is elucidated in another. The two parts of Neuroimaging complement each other providing in-depth information on a broad range of routine and cutting edge techniques that is not available in any other text. This book is superbly written and beautifully illustrated by contributors working at the top of their chosen specialty.* Serves as an up-to-date review of cutting-edge neuroimaging techniques * Exquisitely illustrated * Authoritatively written by leading researchers