Download or read book Optimizing Statistical Methods for Connectivity Mapping in MR Neuroimaging written by Anita Meghan Sinha and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Magnetic resonance imaging (MRI) plays an integral role in the study, diagnosis and treatment of neurological diseases. Neuroimaging analyses involve high-dimensional, large-scale data that contain rich spatial and temporal information about the dynamic and integrated systems in the brain. Therefore, it has become imperative to develop and optimize analytical approaches drawn from engineering and mathematics to more precisely model these complex patterns and interactions, which will advance our understanding of functional brain organization in health and disease. Chapter 1 provides an overview and background of MRI, with a particular focus on the use of resting-state functional magnetic resonance imaging (rs-fMRI) to capture and characterize brain connectivity. Previous work of statistical methods developed for fMRI analysis are reviewed. Chapter 2 presents an analysis of changes in functional connectivity and behavioral outcomes in patients of stroke who undergo brain-computer interface (BCI) interventional therapy. This work employs a widely used network-based inference method for fMRI analysis that serves as motivation for subsequent work to overcome statistical challenges associated with its use to more effectively model and characterize brain network dynamics and organization in a robust manner. Chapter 3 presents a novel application of differential covariance trajectory analysis as promising framework for brain network modeling using rs-fMRI data. The proposed algorithm models functional connectivity as trajectories on the manifold and employs a localization procedure to search over and identify subsets of first- and second-order differences in brain connectivity features between patients with Temporal Lobe Epilepsy (TLE) and healthy control subjects. Chapter 4 extends the work presented in the previous chapter to apply the combined differential covariance trajectory and scan statistics framework to characterize the Alzheimer's Disease connectome. We demonstrate the utility and robustness of this method to study altered brain network organization in large-scale functional networks in a different and older clinical population, which is notably of smaller sample size, where the statistical signal may be weak. Chapter 5 discusses conclusions and key takeaways of the work, along with potential future avenues of research.
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
Download or read book Clinical MR Neuroimaging written by Jonathan H. Gillard and published by Cambridge University Press. This book was released on 2010 with total page 917 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers each physiological MR methodology and their applications to all major neurological diseases.
Download or read book Magnetic Resonance Brain Imaging written by Jörg Polzehl and published by Springer Nature. This book was released on 2019-09-25 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain. The data processing pipelines described rely on R. The book is intended for readers from two communities: Statisticians who are interested in neuroimaging and looking for an introduction to the acquired data and typical scientific problems in the field; and neuroimaging students wanting to learn about the statistical modeling and analysis of MRI data. Offering a practical introduction to the field, the book focuses on those problems in data analysis for which implementations within R are available. It also includes fully worked examples and as such serves as a tutorial on MRI analysis with R, from which the readers can derive their own data processing scripts. The book starts with a short introduction to MRI and then examines the process of reading and writing common neuroimaging data formats to and from the R session. The main chapters cover three common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, and Multi-Parameter Mapping. The book concludes with extended appendices providing details of the non-parametric statistics used and the resources for R and MRI data.The book also addresses the issues of reproducibility and topics like data organization and description, as well as open data and open science. It relies solely on a dynamic report generation with knitr and uses neuroimaging data publicly available in data repositories. The PDF was created executing the R code in the chunks and then running LaTeX, which means that almost all figures, numbers, and results were generated while producing the PDF from the sources.
Download or read book Brain Mapping Methods written by Gautam Prasad and published by . This book was released on 2013 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a collection of methods that model and interpret information represented in structural magnetic resonance imaging (MRI) and diffusion MRI images of the living human brain. Our solution to the problem of brain segmentation in structural MRI combines artificial life and deformable models to develop a customizable plan for segmentation realized as cooperative deformable organisms. We also present work to represent and register white matter pathways as described in diffusion MRI. Our method represents these pathways as maximum density paths (MDPs), which compactly represent information and are compared using shape based registration for population studies. In addition, we present a group of methods focused on connectivity in the brain. These include an optimization for a global probabilistic tractography algorithm that computes fibers representing connectivity pathways in tissue, a novel maximum-flow based measure of connectivity, a classification framework identifying Alzheimer's disease based on connectivity measures, and a statistical framework to find the optimal partition of the brain for connectivity analysis. These methods seek to advance our understanding and analysis of neuroimaging data from crucial pre-processing steps to our fundamental understanding of connectivity in the brain.
Download or read book Advanced MR Neuroimaging written by Ioannis Tsougos and published by CRC Press. This book was released on 2017-12-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last decade, some of the greatest achievements in the field of neuroimaging have been related to remarkable advances in magnetic resonance techniques, including diffusion, perfusion, magnetic resonance spectroscopy, and functional MRI. Such techniques have provided valuable insights into tissue microstructure, microvasculature, metabolism and brain connectivity. Previously available mostly in research environments, these techniques are now becoming part of everyday clinical practice in a plethora of clinical MR systems. Nevertheless, despite growing interest and wider acceptance, there remains a lack of a comprehensive body of knowledge on the subject, exploring the intrinsic complexity and physical difficulty of the techniques. This book focuses on the basic principles and theories of diffusion, perfusion, magnetic resonance spectroscopy, and functional MRI. It also explores their clinical applications and places emphasis on the associated artifacts and pitfalls with a comprehensive and didactic approach. This book aims to bridge the gap between research applications and clinical practice. It will serve as an educational manual for neuroimaging researchers and radiologists, neurologists, neurosurgeons, and physicists with an interest in advanced MR techniques. It will also be a useful reference text for experienced clinical scientists who wish to optimize their multi-parametric imaging approach.
Download or read book fMRI Neurofeedback written by Michelle Hampson and published by Academic Press. This book was released on 2021-10-09 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: fMRI Neurofeedback provides a perspective on how the field of functional magnetic resonance imaging (fMRI) neurofeedback has evolved, an introduction to state-of-the-art methods used for fMRI neurofeedback, a review of published neuroscientific and clinical applications, and a discussion of relevant ethical considerations. It gives a view of the ongoing research challenges throughout and provides guidance for researchers new to the field on the practical implementation and design of fMRI neurofeedback protocols. This book is designed to be accessible to all scientists and clinicians interested in conducting fMRI neurofeedback research, addressing the variety of different knowledge gaps that readers may have given their varied backgrounds and avoiding field-specific jargon. The book, therefore, will be suitable for engineers, computer scientists, neuroscientists, psychologists, and physicians working in fMRI neurofeedback. Provides a reference on fMRI neurofeedback covering history, methods, mechanisms, clinical applications, and basic research, as well as ethical considerations Offers contributions from international experts—leading research groups are represented, including from Europe, Japan, Israel, and the United States Includes coverage of data analytic methods, study design, neuroscience mechanisms, and clinical considerations Presents a perspective on future translational development
Download or read book Brain Mapping written by and published by Academic Press. This book was released on 2015-02-14 with total page 2668 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Mapping: A Comprehensive Reference, Three Volume Set offers foundational information for students and researchers across neuroscience. With over 300 articles and a media rich environment, this resource provides exhaustive coverage of the methods and systems involved in brain mapping, fully links the data to disease (presenting side by side maps of healthy and diseased brains for direct comparisons), and offers data sets and fully annotated color images. Each entry is built on a layered approach of the content – basic information for those new to the area and more detailed material for experienced readers. Edited and authored by the leading experts in the field, this work offers the most reputable, easily searchable content with cross referencing across articles, a one-stop reference for students, researchers and teaching faculty. Broad overview of neuroimaging concepts with applications across the neurosciences and biomedical research Fully annotated color images and videos for best comprehension of concepts Layered content for readers of different levels of expertise Easily searchable entries for quick access of reputable information Live reference links to ScienceDirect, Scopus and PubMed
Download or read book Statistical Techniques for Neuroscientists written by Young K. Truong and published by CRC Press. This book was released on 2016-10-04 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Techniques for Neuroscientists introduces new and useful methods for data analysis involving simultaneous recording of neuron or large cluster (brain region) neuron activity. The statistical estimation and tests of hypotheses are based on the likelihood principle derived from stationary point processes and time series. Algorithms and software development are given in each chapter to reproduce the computer simulated results described therein. The book examines current statistical methods for solving emerging problems in neuroscience. These methods have been applied to data involving multichannel neural spike train, spike sorting, blind source separation, functional and effective neural connectivity, spatiotemporal modeling, and multimodal neuroimaging techniques. The author provides an overview of various methods being applied to specific research areas of neuroscience, emphasizing statistical principles and their software. The book includes examples and experimental data so that readers can understand the principles and master the methods. The first part of the book deals with the traditional multivariate time series analysis applied to the context of multichannel spike trains and fMRI using respectively the probability structures or likelihood associated with time-to-fire and discrete Fourier transforms (DFT) of point processes. The second part introduces a relatively new form of statistical spatiotemporal modeling for fMRI and EEG data analysis. In addition to neural scientists and statisticians, anyone wishing to employ intense computing methods to extract important features and information directly from data rather than relying heavily on models built on leading cases such as linear regression or Gaussian processes will find this book extremely helpful.
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.
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2021 written by Marleen de Bruijne and published by Springer Nature. This book was released on 2021-09-23 with total page 827 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.
Download or read book Neuroethics written by Judy Illes and published by Oxford University Press. This book was released on 2017-07-14 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pressing ethical issues are at the foreground of newfound knowledge of how the brain works, how the brain fails, and how information about its functions and failures are addressed, recorded and shared. In Neuroethics: Anticipating the Future, a distinguished group of contributors tackle current critical questions and anticipate the issues on the horizon. What new balances should be struck between diagnosis and prediction, or invasive and non-invasive interventions, given the rapid advances in neuroscience? Are new criteria needed for the clinical definition of death for those eligible for organ donation? What educational, social and medical opportunities will new neuroscience discoveries bring to the children of tomorrow? As data from emerging technologies are made available on public databases, what frameworks will maximize benefits while ensuring privacy of health information? How is the environment shaping humans, and humans shaping the environment? These challenging questions and other future-looking neuroethical concerns are discussed in depth. Written by eminent scholars from diverse disciplines - neurology and neuroscience, ethics, law, public health, and philosophy - this new volume on neuroethics sets out the conditions for active consideration. It is essential reading for the fields of neuroethics, neurosciences and psychology, and an invaluable resource for physicians in neurology and neurosurgery, psychiatry, paediatrics, and rehabilitation medicine, academics in humanities and law, and health policy makers.
Download or read book The Oxford Handbook of Social Neuroscience written by Jean Decety and published by Oxford University Press. This book was released on 2015-04-15 with total page 1124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexities of the brain and nervous system make neuroscience an inherently interdisciplinary pursuit, one that comprises disparate basic, clinical, and applied disciplines. Behavioral neuroscientists approach the brain and nervous system as instruments of sensation and response; cognitive neuroscientists view the same systems as a solitary computer with a focus on representations and processes. The Oxford Handbook of Social Neuroscience marks the emergence of a third broad perspective in this field. Social neuroscience emphasizes the functions that emerge through the coaction and interaction of conspecifics, the neural mechanisms that underlie these functions, and the commonality and differences across social species and superorganismal structures. With an emphasis on the neural, hormonal, cellular, and genetic mechanisms underlying social behavior, social neuroscience places emphasis on the associations and influences between social and biological levels of organization. This complex interdisciplinary perspective demands theoretical, methodological, statistical, and inferential rigor to effectively integrate basic, clinical, and applied perspectives on the nervous system and brain. Reflecting the diverse perspectives that make up this field, The Oxford Handbook of Social Neuroscience brings together perspectives from across the sciences in one authoritative volume.
Download or read book Pattern Analysis of the Human Connectome written by Dewen Hu and published by Springer. This book was released on 2020-11-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.
Download or read book Multiple Sclerosis and Associated Demyelinating Disorders An Issue of Neuroimaging Clinics of North America E Book written by Frederik Barkhof and published by Elsevier Health Sciences. This book was released on 2024-07-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this issue of Neuroimaging Clinics, guest editors Drs. Frederik Barkhof and Yaou Liu bring their considerable expertise to the topic of Multiple Sclerosis and Associated Demyelinating Disorders. Top experts in the field discuss advanced brain imaging in CNS demyelinating diseases; new imaging markers in MS and related disorders: smoldering inflammation and central vein sign; the use of AI in MS and white matter disease; optic nerve imaging in MS and related disorders; atypical demyelinating disorders; and more. Co-Editor Frederik Barkhof, MD, has received the National Multiple Sclerosis Society and the American Academy of Neurology’s 2018 John Dystel Prize for Multiple Sclerosis Research for his many years of outstanding research in the field of MS, especially in advancing the understanding and clinical use of brain imaging. Contains 12 relevant, practice-oriented topics including diagnostic criteria for MS, NMOSD and MOGAD; routine MRI protocol and standardization in CNS demyelinating diseases; spinal cord imaging in MS and related disorders; treatment monitoring in MS: efficacy and safety; cognitive impairment in MS and related disorders; and more. Provides in-depth clinical reviews on multiple sclerosis and associated demyelinating disorders, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
Download or read book Functional Brain Mapping of Epilepsy Networks Methods and Applications written by David F. Abbott and published by Frontiers Media SA. This book was released on 2020-01-29 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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
