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Fundamentals of Brain Network Analysis

Fundamentals of Brain Network Analysis
  • Author : Alex Fornito,Andrew Zalesky,Edward Bullmore
  • Publisher :Unknown
  • Release Date :2016-03-04
  • Total pages :494
  • ISBN : 9780124081185
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Summary : 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

Fundamentals of Brain Network Analysis

Fundamentals of Brain Network Analysis
  • Author : Alex Fornito,Andrew Zalesky,Edward T. Bullmore
  • Publisher :Unknown
  • Release Date :2015-11-01
  • Total pages :476
  • ISBN : 0124079083
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Summary : Fundamentals of Human Imaging Connectomics is the first book to provide an accessible, practical, and comprehensive introduction to imaging connectomics for researchers of any background. Written by experts in all areas of the field, the book contains non-technical, conceptual, and instructive discussions of each of the core principles of imaging connectomics. It features intuitive diagrams, graphical illustrations of key concepts, step-by-step explanations of mathematical formulae, and recommendations for best practices, providing users with an indispensable guide on the study of the human connectome. Provides a step-by-step introduction to connectomics that is suitable for both researchers and students Presents a general overview and discussions of various issues involved in using neuroimaging to build a connectomic map, the main measures used to analyze connectomic data, and an introduction to advanced topics in the field Helps readers determine how to best use fMRI/DTI data to make a brain network, how to analyze that network using graph theory, and how to compare and interpret findings Assumes no prior knowledge beyond basic training in human MRI, and adopts a consistent format across chapters to facilitate learning and linking of different concepts

Fundamentals of Brain Network Analysis

Fundamentals of Brain Network Analysis
  • Author : Alex Fornito,Andrew Zalesky,Edward T. Bullmore
  • Publisher :Unknown
  • Release Date :2016
  • Total pages :476
  • ISBN : OCLC:956735854
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Summary : This book provides an introduction to neural connectomics. It explains fundamental concepts with detailed examples of their application to neuroscience. It is suitable for use as a reference for both researchers and students aiming to gain familiarity with the field.

Brain Network Analysis

Brain Network Analysis
  • Author : Moo K. Chung
  • Publisher :Unknown
  • Release Date :2019-06-30
  • Total pages :320
  • ISBN : 9781107184862
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Summary : This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

Networks of the Brain

Networks of the Brain
  • Author : Olaf Sporns
  • Publisher :Unknown
  • Release Date :2010-10-01
  • Total pages :424
  • ISBN : 9780262288927
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Summary : An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.

Network Neuroscience

Network Neuroscience
  • Author : Flavio Fröhlich
  • Publisher :Unknown
  • Release Date :2016-09-20
  • Total pages :482
  • ISBN : 9780128015865
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Summary : Studying brain networks has become a truly interdisciplinary endeavor, attracting students and seasoned researchers alike from a wide variety of academic backgrounds. What has been lacking is an introductory textbook that brings together the different fields and provides a gentle introduction to the major concepts and findings in the emerging field of network neuroscience. Network Neuroscience is a one-stop-shop that is of equal use to the neurobiologist, who is interested in understanding the quantitative methods employed in network neuroscience, and to the physicist or engineer, who is interested in neuroscience applications of mathematical and engineering tools. The book spans 27 chapters that cover everything from individual cells all the way to complex network disorders such as depression and autism spectrum disorders. An additional 12 toolboxes provide the necessary background for making network neuroscience accessible independent of the reader’s background. Dr. Flavio Frohlich (www.networkneuroscientist.org) wrote this book based on his experience of mentoring dozens of trainees in the Frohlich Lab, from undergraduate students to senior researchers. The Frohlich lab (www.frohlichlab.org) pursues a unique and integrated vision that combines computer simulations, animal model studies, human studies, and clinical trials with the goal of developing novel brain stimulation treatments for psychiatric disorders. The book is based on a course he teaches at UNC that has attracted trainees from many different departments, including neuroscience, biomedical engineering, psychology, cell biology, physiology, neurology, and psychiatry. Dr. Frohlich has consistently received rave reviews for his teaching. With this book he hopes to make his integrated view of neuroscience available to trainees and researchers on a global scale. His goal is to make the book the training manual for the next generation of (network) neuroscientists, who will be fusing biology, engineering, and medicine to unravel the big questions about the brain and to revolutionize psychiatry and neurology. Easy-to-read, comprehensive introduction to the emerging field of network neuroscience Includes 27 chapters packed with information on topics from single neurons to complex network disorders such as depression and autism Features 12 toolboxes serve as primers to provide essential background knowledge in the fields of biology, mathematics, engineering, and physics

Biological Network Analysis

Biological Network Analysis
  • Author : Pietro Hiram Guzzi,Swarup Roy
  • Publisher :Unknown
  • Release Date :2020-05-11
  • Total pages :210
  • ISBN : 9780128193518
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Summary : Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource. Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes Includes a discussion of various graph theoretic and data analytics approaches

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience
  • Author : Thomas Trappenberg
  • Publisher :Unknown
  • Release Date :2010
  • Total pages :390
  • ISBN : 9780199568413
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Summary : The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental networkarchitectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can begained with such studies.

Handbook of Functional MRI Data Analysis

Handbook of Functional MRI Data Analysis
  • Author : Russell A. Poldrack,Jeanette A. Mumford,Thomas E. Nichols
  • Publisher :Unknown
  • Release Date :2011-08-22
  • Total pages :229
  • ISBN : 9781139498364
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Summary : Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Connectome

Connectome
  • Author : Sebastian Seung
  • Publisher :Unknown
  • Release Date :2012-02-07
  • Total pages :256
  • ISBN : 9780547508177
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Summary : “Accessible, witty . . . an important new researcher, philosopher and popularizer of brain science . . . on par with cosmology’s Brian Greene and the late Carl Sagan” (The Plain Dealer). One of the Wall Street Journal’s 10 Best Nonfiction Books of the Year and a Publishers Weekly “Top Ten in Science” Title Every person is unique, but science has struggled to pinpoint where, precisely, that uniqueness resides. Our genome may determine our eye color and even aspects of our character. But our friendships, failures, and passions also shape who we are. The question is: How? Sebastian Seung is at the forefront of a revolution in neuroscience. He believes that our identity lies not in our genes, but in the connections between our brain cells—our particular wiring. Seung and a dedicated group of researchers are leading the effort to map these connections, neuron by neuron, synapse by synapse. It’s a monumental effort, but if they succeed, they will uncover the basis of personality, identity, intelligence, memory, and perhaps disorders such as autism and schizophrenia. Connectome is a mind-bending adventure story offering a daring scientific and technological vision for understanding what makes us who we are, as individuals and as a species. “This is complicated stuff, and it is a testament to Dr. Seung’s remarkable clarity of exposition that the reader is swept along with his enthusiasm, as he moves from the basics of neuroscience out to the farthest regions of the hypothetical, sketching out a spectacularly illustrated giant map of the universe of man.” —TheNew York Times “An elegant primer on what’s known about how the brain is organized and how it grows, wires its neurons, perceives its environment, modifies or repairs itself, and stores information. Seung is a clear, lively writer who chooses vivid examples.” —TheWashington Post

Brain Network Analysis

Brain Network Analysis
  • Author : Moo K. Chung
  • Publisher :Unknown
  • Release Date :2019-06-30
  • Total pages :320
  • ISBN : 9781107184862
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Summary : This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.

Fundamentals of Deep Learning

Fundamentals of Deep Learning
  • Author : Nikhil Buduma,Nicholas Locascio
  • Publisher :Unknown
  • Release Date :2017-05-25
  • Total pages :298
  • ISBN : 9781491925560
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Summary : With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning

Dendrites

Dendrites
  • Author : Greg Stuart,Michael Häusser
  • Publisher :Unknown
  • Release Date :2007
  • Total pages :560
  • ISBN : 0198566565
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Summary : Dendrites form the major receiving part of neurons. It is within these highly complex, branching structures that the real work of the nervous system takes place. The dendrites of neurons receive thousands of synaptic inputs from other neurons. However, dendrites do more than simply collect and funnel these signals to the soma and axon; they shape and integrate the inputs in complex ways. Despite being discovered over a century ago, dendrites received little research attention until the early 1950s. Over the past few years there has been a dramatic explosion of interest in the function of these beautiful structures. Recent new research has developed out understanding of the properties of dendrites, and their role in neuronal function. The first edition of Dendrites was a landmark in the literature, stimulating and guiding further research. The new edition substantially updates the earlier volume, and includes 5 new chapters and color illustrations. It gathers new information on dendrites into a single volume, with contributions written by leading researchers in the field. It presents a survey of the current state of our knowledge of dendrites, from their morphology and development through to their electrical, chemical, and computational properties. As such it will not only be of interest to researchers and graduate-level students in neuroscience, but will also be useful to researchers in computer science and IT, psychology, physiology, and biophysics.

Statistical Analysis of FMRI Data

Statistical Analysis of FMRI Data
  • Author : F. Gregory Ashby
  • Publisher :Unknown
  • Release Date :2011
  • Total pages :332
  • ISBN : 9780262015042
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Summary : An overview of statistical methods for analyzing data from fMRI experiments. 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; researchers face significant challenges in analyzing the data they collect. This book offers an overview of the most widely used statistical methods of analyzing fMRI data. Every step is covered, from preprocessing to advanced methods for assessing functional connectivity. The goal is not to describe which buttons to push in the popular software packages but to help readers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method. The book covers all of the important current topics in fMRI data analysis, including the relation of the fMRI BOLD (blood oxygen-level dependent) response to neural activation; basic analyses done in virtually every fMRI article--preprocessing, constructing statistical parametrical maps using the general linear model, solving the multiple comparison problem, and group analyses; the most popular methods for assessing functional connectivity--coherence analysis and Granger causality; two widely used multivariate approaches, principal components analysis and independent component analysis; and a brief survey of other current fMRI methods. The necessary mathematics is explained at a conceptual level, but in enough detail to allow mathematically sophisticated readers to gain more than a purely conceptual understanding. The book also includes short examples of Matlab code that implement many of the methods described; an appendix offers an introduction to basic Matlab matrix algebra commands (as well as a tutorial on matrix algebra). A second appendix introduces multivariate probability distributions.

Introduction to Neuroimaging Analysis

Introduction to Neuroimaging Analysis
  • Author : Mark Jenkinson,Michael Chappell
  • Publisher :Unknown
  • Release Date :2017-10-26
  • Total pages :208
  • ISBN : 9780198816300
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Summary : MRI has emerged as a powerful way of studying in-vivo brain structure and function in both healthy and disease states. Whilst new researchers may be able to call upon advice and support for acquisition from operators, radiologists and technicians, it is more challenging to obtain anunderstanding of the principles of analysing neuroimaging data. This is crucial for choosing acquisition parameters, designing and performing appropriate experiments, and correctly interpreting the results. This primer gives a general and accessible introduction to the wide array of MRI-based neuroimaging methods that are used in research. Supplemented with online datasets and examples to enable the reader to obtain hands-on experience working with real data, it provides a practical and approachableintroduction for those new to the neuroimaging field. The text also covers the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common "pipelines" including brain extraction, registration and segmentation. As it does not require any background knowledge beyond high-school mathematics and physics, this primer is essential reading for anyone wanting to work in neuroimaging or grasp the results coming from this rapidly expanding field.The Oxford Neuroimaging Primers are short texts aimed at new researchers or advanced undergraduates from the biological, medical or physical sciences. They are intended to provide a broad understanding of the ways in which neuroimaging data can be analyzed and how that relates to acquisition andinterpretation. Each primer has been written so that it is a stand-alone introduction to a particular area of neuroimaging, and the primers also work together to provide a comprehensive foundation for this increasingly influential field.

MATLAB for Neuroscientists

MATLAB for Neuroscientists
  • Author : Pascal Wallisch,Michael E. Lusignan,Marc D. Benayoun,Tanya I. Baker,Adam Seth Dickey,Nicholas G. Hatsopoulos
  • Publisher :Unknown
  • Release Date :2014-01-09
  • Total pages :570
  • ISBN : 9780123838377
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Summary : MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Discovering the Human Connectome

Discovering the Human Connectome
  • Author : Olaf Sporns
  • Publisher :Unknown
  • Release Date :2012-09-07
  • Total pages :248
  • ISBN : 9780262304801
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Summary : A pioneer in the field outlines new empirical and computational approaches to mapping the neural connections of the human brain. Crucial to understanding how the brain works is connectivity, and the centerpiece of brain connectivity is the connectome, a comprehensive description of how neurons and brain regions are connected. In this book, Olaf Sporns surveys current efforts to chart these connections—to map the human connectome. He argues that the nascent field of connectomics has already begun to influence the way many neuroscientists collect, analyze, and think about their data. Moreover, the idea of mapping the connections of the human brain in their entirety has captured the imaginations of researchers across several disciplines including human cognition, brain and mental disorders, and complex systems and networks. Discovering the Human Connectome offers the first comprehensive overview of current empirical and computational approaches in this rapidly developing field.

Fundamentals Of Network Biology

Fundamentals Of Network Biology
  • Author : Zhang Wenjun
  • Publisher :Unknown
  • Release Date :2018-05-16
  • Total pages :568
  • ISBN : 9781786345103
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Summary : As the first comprehensive title on network biology, this book covers a wide range of subjects including scientific fundamentals (graphs, networks, etc) of network biology, construction and analysis of biological networks, methods for identifying crucial nodes in biological networks, link prediction, flow analysis, network dynamics, evolution, simulation and control, ecological networks, social networks, molecular and cellular networks, network pharmacology and network toxicology, big data analytics, and more. Across 12 parts and 26 chapters, with Matlab codes provided for most models and algorithms, this self-contained title provides an in-depth and complete insight on network biology. It is a valuable read for high-level undergraduates and postgraduates in the areas of biology, ecology, environmental sciences, medical science, computational science, applied mathematics, and social science. Contents: Mathematical Fundamentals: Fundamentals of Graph TheoryGraph AlgorithmsFundamentals of Network TheoryOther FundamentalsCrucial Nodes/Subnetworks/Modules, Network Types, and Structural Comparison: Identification of Crucial Nodes and Subnetworks/ModulesDetection of Network TypesComparison of Network StructureNetwork Dynamics, Evolution, Simulation and Control: Network DynamicsNetwork Robustness and Sensitivity AnalysisNetwork ControlNetwork EvolutionCellular AutomataSelf-OrganizationAgent-based ModelingFlow Analysis: Flow/Flux AnalysisLink and Node Prediction: Link Prediction: Sampling-based MethodsLink Prediction: Structure- and Perturbation-based MethodsLink Prediction: Node-Similarity-based MethodsNode PredictionNetwork Construction: Construction of Biological NetworksPharmacological and Toxicological Networks: Network Pharmacology and ToxicologyEcological Networks: Food WebsMicroscopic Networks: Molecular and Cellular NetworksSocial Networks: Social Network AnalysisSoftware: Software for Network AnalysisBig Data Analytics: Big Data Analytics for Network Biology Readership: Advanced undergraduates and graduate students and researchers in biology, ecology, pharmacology, applied mathematics, computational science, etc. Keywords: Network Biology;Network Analysis;Food Webs;Molecular Networks;Social Networks;Network Pharmacology;Link Prediction;Network Dynamics;Big Data Analytics;Software;Models;Algorithms;Nodes;LinksReview:0

Changing Connectomes

Changing Connectomes
  • Author : Marcus Kaiser
  • Publisher :Unknown
  • Release Date :2020-09-08
  • Total pages :248
  • ISBN : 9780262360814
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Summary : An up-to-date overview of the field of connectomics, introducing concepts and mechanisms underlying brain network change at different stages. The human brain undergoes massive changes during its development, from early childhood and the teenage years to adulthood and old age. Across a wide range of species, from C. elegans and fruit flies to mice, monkeys, and humans, information about brain connectivity (connectomes) at different stages is now becoming available. New approaches in network neuroscience can be used to analyze the topological, spatial, and dynamical organization of such connectomes. In Changing Connectomes, Marcus Kaiser provides an up-to-date overview of the field of connectomics and introduces concepts and mechanisms underlying brain network changes during evolution and development.

Fundamentals of Neural Network Modeling

Fundamentals of Neural Network Modeling
  • Author : Randolph W. Parks,Daniel S. Levine,Debra L. Long
  • Publisher :Unknown
  • Release Date :1998
  • Total pages :428
  • ISBN : 0262161753
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Summary : 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

Analyzing Neural Time Series Data

Analyzing Neural Time Series Data
  • Author : Mike X Cohen
  • Publisher :Unknown
  • Release Date :2014-01-17
  • Total pages :600
  • ISBN : 9780262019873
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Summary : A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings.