Advances Of Neuroimaging And Data Analysis
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Advances Of Neuroimaging And Data Analysis
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Author : Jue Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2020-06-05
Advances Of Neuroimaging And Data Analysis written by Jue Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-05 with categories.
Recent Advances And Challenges On Big Data Analysis In Neuroimaging
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Author : Jian Kang
language : en
Publisher: Frontiers Media SA
Release Date : 2017-05-17
Recent Advances And Challenges On Big Data Analysis In Neuroimaging written by Jian Kang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-17 with Electronic book categories.
Big data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.
Recent Advances And Challenges On Big Data Analysis In Neuroimaging
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Author :
language : en
Publisher:
Release Date : 2017
Recent Advances And Challenges On Big Data Analysis In Neuroimaging written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Big data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.
Multivariate Analysis For Neuroimaging Data
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Author : Atsushi Kawaguchi
language : en
Publisher: CRC Press
Release Date : 2021-07-01
Multivariate Analysis For Neuroimaging Data written by Atsushi Kawaguchi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Mathematics categories.
This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors’ team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.
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 Medical 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
Brain Signal Analysis
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Author : Todd C. Handy
language : en
Publisher: MIT Press
Release Date : 2009
Brain Signal Analysis written by Todd C. Handy and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Cognitive neuroscience categories.
Recent developments in the tools and techniques of data acquisition and analysis in cognitive electrophysiology.
Statistical Analysis Of Fmri Data Second Edition
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Author : F. Gregory Ashby
language : en
Publisher: MIT Press
Release Date : 2019-09-17
Statistical Analysis Of Fmri Data Second Edition written by F. Gregory Ashby and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Medical categories.
A guide to all aspects of experimental design and data analysis for fMRI experiments, completely revised and updated for the second edition. Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data for researchers to analyze. This book describes all aspects of experimental design and data analysis for fMRI experiments, covering every step—from preprocessing to advanced methods for assessing functional connectivity—as well as the most popular multivariate approaches. The goal is not to describe which buttons to push in the popular software packages but to help researchers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method. The field of fMRI research has advanced dramatically in recent years, in both methodology and technology, and this second edition has been completely revised and updated. Six new chapters cover experimental design, functional connectivity analysis through the methods of psychophysiological interactions and beta-series regression, decoding using multi-voxel pattern analysis, dynamic causal modeling, and representational similarity analysis. Other chapters offer new material on recently discovered problems related to head movements, the multivariate GLM, meta-analysis, and other topics. All complex derivations now appear at the end of the relevant chapter to improve readability. A new appendix describes how to build a design matrix with effect coding for group analysis. As in the first edition, MATLAB code is provided with which readers can implement many of the methods described.
Recent Advances And The Future Generation Of Neuroinformatics Infrastructure
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Author : Xi Cheng
language : en
Publisher: Frontiers Media SA
Release Date : 2015-12-11
Recent Advances And The Future Generation Of Neuroinformatics Infrastructure written by Xi Cheng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Electronic book categories.
The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.
Innovative Applications With Artificial Intelligence Methods In Neuroimaging Data Analysis
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Author : Yao Wu
language : en
Publisher: Frontiers Media SA
Release Date : 2023-02-08
Innovative Applications With Artificial Intelligence Methods In Neuroimaging Data Analysis written by Yao Wu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-08 with Science categories.
Advances In Neuroimaging Data Processing
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Author : Alexander E Hramov
language : en
Publisher: Mdpi AG
Release Date : 2023-03-21
Advances In Neuroimaging Data Processing written by Alexander E Hramov and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Science categories.
The development of in vivo neuroimaging techniques has yielded an incredible amount of digital information about the brain. Neuroimaging techniques are increasingly being used to study human cognitive processes, create brain-machine interfaces, and also to identify and diagnose certain brain disorders. Currently, neuroscientists and medics actively use different methods for brain scans, including electro- and magnetoencephalography (EEG/MEG), functional near-infrared spectroscopy (fNIRS), electrocorticography (ECoG), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and diffusion tensor imaging (DTI). Recent advances in signal processing and machine learning for neuroimaging data using various signal processing methods have made impressive progress in solving a number of practical tasks in medicine, healthcare, neuroscience, biomedical engineering, brain-machine interfaces, and cognitive science, to name but a few. This Special Issue aims to provide a forum for academic and industrial communities to present and discuss the latest theoretical and experimental results related to recent advances in neuroimaging data processing in terms of new theories, algorithms, architectures, and applications.