Mathematical Approaches to Brain Functioning Diagnostics
Mathematical Approaches to Brain Functioning Diagnostics

Author: Ivan Dvorak

Publisher: John Wiley & Sons

Published: 1992-03

Total Pages: 478

ISBN-13: 9780471935070

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Mathematical approaches to modelling of brain functioning; analysis and mapping of EEG activity; analysis of event related brain electrical activity; computer and mathematical modelling of brain activity; mathematical and computer techniques in brain functioning diagnostics; dynamic system approach to brain functioning analysis; analysis and modelling of brain perception and cognitive processes.

Human Brain Function
Human Brain Function

Author: Karl J. Friston

Publisher: Elsevier

Published: 2004-01-26

Total Pages: 1161

ISBN-13: 0080472958

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This updated second edition provides the state of the art perspective of the theory, practice and application of modern non-invasive imaging methods employed in exploring the structural and functional architecture of the normal and diseased human brain. Like the successful first edition, it is written by members of the Functional Imaging Laboratory - the Wellcome Trust funded London lab that has contributed much to the development of brain imaging methods and their application in the last decade. This book should excite and intrigue anyone interested in the new facts about the brain gained from neuroimaging and also those who wish to participate in this area of brain science.* Represents an almost entirely new book from 1st edition, covering the rapid advances in methods and in understanding of how human brains are organized* Reviews major advances in cognition, perception, emotion and action* Introduces novel experimental designs and analytical techniques made possible with fMRI, including event-related designs and non-linear analysis

Molecular Imaging of the Brain
Molecular Imaging of the Brain

Author: M. M. Kaila

Publisher: Springer Science & Business Media

Published: 2012-09-20

Total Pages: 430

ISBN-13: 3642303013

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This book examines multi-quantum magnetic resonance imaging methods and the diagnostics of brain disorders. It consists of two Parts. The part I is initially devoted towards the basic concepts of the conventional single quantum MRI techniques. It is supplemented by the basic knowledge required to understand multi-quantum MRI. Practical illustrations are included both on recent developments in conventional MRI and the MQ-MRI. This is to illustrate the connection between theoretical concepts and their scope in the clinical applications. The Part II initially sets out the basic details about quadrupole charge distribution present in certain nuclei and their importance about the functions they perform in our brain. Some simplified final mathematical expressions are included to illustrate facts about the basic concepts of the quantum level interactions between magnetic dipole and the electric quadrupole behavior of useful nuclei present in the brain. Selected practical illustrations, from research and clinical practices are included to illustrate the newly emerging ideas and techniques. The reader should note that the two parts of the book are written with no interdependence. One can read them quite independently.

Neural Network Dynamics
Neural Network Dynamics

Author: J.G. Taylor

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 378

ISBN-13: 1447120019

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Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.

Smoothing and Regression
Smoothing and Regression

Author: Michael G. Schimek

Publisher: Wiley-Interscience

Published: 2000-08-07

Total Pages: 656

ISBN-13:

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A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis. Using examples of applications from the biosciences, environmental sciences, engineering, and economics, as well as medical research and marketing, this volume addresses the theory, computation, and application of each approach. A number of the techniques discussed, such as smoothing under shape restrictions or of dependent data, are presented for the first time in book form. Special features of this book include: * Comprehensive coverage of smoothing and regression with software hints and applications from a wide variety of disciplines * A unified, easy-to-follow format * Contributions from more than 25 leading researchers from around the world * More than 150 illustrations also covering new graphical techniques important for exploratory data analysis and visualization of high-dimensional problems * Extensive end-of-chapter references For professionals and aspiring professionals in statistics, applied mathematics, computer science, and econometrics, as well as for researchers in the applied and social sciences, Smoothing and Regression is a unique and important new resource destined to become one the most frequently consulted references in the field.