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Author: Jesus M. Cortés
Publisher: Frontiers Media SA
ISBN: 2889195023
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 192
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Book Description
The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion. Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables. In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology. Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications. This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.
Author: Jesus M. Cortés
Publisher: Frontiers Media SA
ISBN: 2889195023
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 192
Get Book
Book Description
The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion. Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables. In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology. Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications. This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.
Author:
Publisher:
ISBN:
Category : Brain
Languages : en
Pages : 191
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Book Description
Author: Osvaldo Gervasi
Publisher: Springer
ISBN: 3319951718
Category : Computers
Languages : en
Pages : 819
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Book Description
The five volume set LNCS 10960 until 10964 constitutes the refereed proceedings of the 18th International Conference on Computational Science and Its Applications, ICCSA 2018, held in Melbourne, Australia, in July 2018. Apart from the general tracks, ICCSA 2018 also includes 34 international workshops in various areas of computational sciences, ranging from computational science technologies, to specific areas of computational sciences, such as computer graphics and virtual reality.
Author: Sanja Josef Golubic
Publisher: BoD – Books on Demand
ISBN: 1789858054
Category : Medical
Languages : en
Pages : 172
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Book Description
Neuroimaging provides a valuable noninvasive window into the human neural system and is used in fundamental and clinical research. Imaging techniques are essential for understanding spontaneous neural activity and brain mechanisms engaged in the processing of external inputs, memory formation, and cognition. Modern imaging modalities make it possible to visualize memory processes within the brain and to create images of its structure and function. Scientists and technologists are joining forces to pave the way for improving imaging technologies and methods, data analysis, and the application of imaging to investigate the wide spectra of neurological diseases, neuropsychological disorders, and aging. Imaging techniques are essential for the identification of biological markers of the earliest stages of neurodiseases and the development of new therapies. This book intends to provide the reader with a short overview of the current achievements in the state-of-the-art imaging modality methods, their highlights, and limitations in neuroscience research and clinical applications. The current state of in-vivo neuroimaging methods in the context of the understanding and diagnosis of mental disorders and relation to the mind is also discussed in a modern compact format, featuring the latest and most relevant research results.
Author: Hernando Ombao
Publisher: CRC Press
ISBN: 1482220989
Category : Mathematics
Languages : en
Pages : 702
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Book Description
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.
Author: Judith M. Rumsey
Publisher: Cambridge University Press
ISBN: 1139476750
Category : Medical
Languages : en
Pages : 473
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Book Description
Modern neuroimaging offers tremendous opportunities for gaining insights into normative development and a wide array of developmental neuropsychiatric disorders. Focusing on ontogeny, this text covers basic processes involved in both healthy and atypical maturation, and also addresses the range of neuroimaging techniques most widely used for studying children. This book will enable you to understand normative structural and functional brain maturation and the mechanisms underlying basic developmental processes; become familiar with current knowledge and hypotheses concerning the neural bases of developmental neuropsychiatric disorders; and learn about neuroimaging techniques, including their unique strengths and limitations. Coverage includes normal developmental processes, atypical processing in developmental neuropsychiatric disorders, ethical issues, neuroimaging techniques and their integration with psychopharmacologic and molecular genetic research approaches, and future directions. This comprehensive volume is an essential resource for neurologists, neuropsychologists, psychiatrists, pediatricians, and radiologists concerned with normal development and developmental neuropsychiatric disorders.
Author: William D. Penny
Publisher: Elsevier
ISBN: 0080466508
Category : Psychology
Languages : en
Pages : 689
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Book Description
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
Author: Alex Fornito
Publisher: Academic Press
ISBN: 0124081185
Category : Medical
Languages : en
Pages : 494
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Book Description
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. 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
Author: Stephen J. Wood
Publisher: Cambridge University Press
ISBN: 0521862892
Category : Medical
Languages : en
Pages : 465
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Book Description
Describes neuropsychological approaches to the investigation, description, measurement and management of a wide range of mental illnesses.
Author: Gerald M. Edelman
Publisher: MIT Press
ISBN: 0262550075
Category : Medical
Languages : en
Pages : 107
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Book Description
A proposal by two eminent biological scientists for a mechanism whereby mind becomes manifest from the operations of brain tissue. This significant contribution to neuroscience consists of two papers, the first by Mountcastle an, the second by Edelman. Between them, they examine from different but complementary directions the relationships that connect the higher brain—memory, learning, perception, thinking—with what goes on at the most basic levels of neural activity, with particular stress on the role of local neuronal circuits.Edelman's major hypothesis is that "the conscious state results from phasic reentrant signaling occurring in parallel processes that involve associations between stored patterns and current sensory or internal input." This selective process occurs by the polling of degenerate primary repertoires of neuronal groups that are formed during embryogenesis and development. Edelman's theory extrapolates to the brain the selectionistic immunological theories for which he was awarded the 1972 Nobel Prize in Physiology or Medicine. Mountcastle's paper reviews what is known about the actual structure of various parts of the neo cortex. He relates the large entities of the neocortex to their component modules—the local neuronal circuits—and shows how the complex interrelationships of such a distributed system can yield dynamic distributed functioning. There are strong conceptual parallels between Mountcastle's idea of cortical columns and their functional subunits and Edelman's concept of populations of neurons functioning as processors in a brain system based on selectional rather than instructional principles. These parallels are traced and put into perspective in Francis Schmitt's Introduction.
