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EEG/ERP Analysis by Kamel Nidal,Aamir Saeed Malik Pdf
Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and other monitoring systems used in preventive diagnostic procedures incorporate innovative features for brain monitoring functions such as real-time automated signal processing techniques and sophisticated amplifi
An Introduction to the Event-Related Potential Technique, second edition by Steven J. Luck Pdf
An essential guide to designing, conducting, and analyzing event-related potential (ERP) experiments, completely updated for this edition. The event-related potential (ERP) technique, in which neural responses to specific events are extracted from the EEG, provides a powerful noninvasive tool for exploring the human brain. This volume describes practical methods for ERP research along with the underlying theoretical rationale. It offers researchers and students an essential guide to designing, conducting, and analyzing ERP experiments. This second edition has been completely updated, with additional material, new chapters, and more accessible explanations. Freely available supplementary material, including several online-only chapters, offer expanded or advanced treatment of selected topics. The first half of the book presents essential background information, describing the origins of ERPs, the nature of ERP components, and the design of ERP experiments. The second half of the book offers a detailed treatment of the main steps involved in conducting ERP experiments, covering such topics as recording the EEG, filtering the EEG and ERP waveforms, and quantifying amplitudes and latencies. Throughout, the emphasis is on rigorous experimental design and relatively simple analyses. New material in the second edition includes entire chapters devoted to components, artifacts, measuring amplitudes and latencies, and statistical analysis; updated coverage of recording technologies; concrete examples of experimental design; and many more figures. Online chapters cover such topics as overlap, localization, writing and reviewing ERP papers, and setting up and running an ERP lab.
The Oxford Handbook of Event-Related Potential Components by Steven J. Luck,Emily S. Kappenman Pdf
The Oxford Handbook of Event-Related Potential Components provides a detailed and comprehensive overview of the major ERP components. It covers components related to multiple research domains, including perception, cognition, emotion, neurological and psychiatric disorders, and lifespan development.
EEG Signal Processing by Saeid Sanei,Jonathon A. Chambers Pdf
Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.
Quantitative EEG, Event-Related Potentials and Neurotherapy by Juri D. Kropotov Pdf
While the brain is ruled to a large extent by chemical neurotransmitters, it is also a bioelectric organ. The collective study of Quantitative ElectroEncephaloGraphs (QEEG-the conversion of brainwaves to digital form to allow for comparison between neurologically normative and dysfunctional individuals), Event Related Potentials (ERPs - electrophysiological response to stimulus) and Neurotherapy (the process of actually retraining brain processes to) offers a window into brain physiology and function via computer and statistical analyses of traditional EEG patterns, suggesting innovative approaches to the improvement of attention, anxiety, mood and behavior.The volume provides detailed description of the various EEG rhythms and ERPs, the conventional analytic methods such as spectral analysis, and the emerging method utilizing QEEG and ERPs. This research is then related back to practice and all existing approaches in the field of Neurotherapy - conventional EEG-based neurofeedback, brain-computer interface, transcranial Direct Current Stimulation, and Transcranial Magnetic Stimulation - are covered in full. While it does not offer the breadth provided by an edited work, this volume does provide a level of depth and detail that a single author can deliver, as well as giving readers insight into the personl theories of one of the preeminent leaders in the field. Provide a holistic picture of quantitative EEG and event related potentials as a unified scientific field Present a unified description of the methods of quantitative EEG and event related potentials Give a scientifically based overview of existing approaches in the field of neurotherapy Provide practical information for the better understanding and treatment of disorders, such as ADHD, Schizophrenia, Addiction, OCD, Depression, and Alzheimer's Disease
Infant EEG and Event-Related Potentials by Michelle de Haan Pdf
Infancy is a time of rapid growth, when brain plasticity is at a maximum. Event-related potentials (ERPs) are one of the few methods that can easily and safely be used to study this process, and have led to exciting discoveries about human brain functioning and the neural basis of cognition. Over recent years, there has been a massive rise in the level of interest in ERPs and this book considers the advantages which they offer to researchers and clinicians. In particular, it looks at the benefits of this form of neuroimaging as a non-invasive tool for detecting impairments in brain and cognitive development very early in life. The potential use of ERPs for clinical settings is also explored in detail. The contributions are all from eminent researchers in the field and represent the latest thought on the topic. Infant EEG and Event-Related Potentials explains the basics of event-related potentials for those less familiar with the procedures and terminology, as well as offering a valuable handbook of the latest theories and empirical findings for those working in the field. This will be a valuable source for those interested in developmental psychology and neuropsychology, and for clinicians interested in application of ERPs.
Advanced Signal Processing on Brain Event-Related Potentials by Fengyu Cong,Tapani Ristaniemi,Heikki Lyytinen Pdf
This book is devoted to the application of advanced signal processing on event-related potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive neuroscience. ERPs are usually produced through averaging single-trials of preprocessed EEG, and then, the interpretation of underlying brain activities is based on the ordinarily averaged EEG. We find that randomly fluctuating activities and artifacts can still present in the averaged EEG data, and that constant brain activities over single trials can overlap with each other in time, frequency and spatial domains. Therefore, before interpretation, it will be beneficial to further separate the averaged EEG into individual brain activities. The book proposes systematic approaches pre-process wavelet transform (WT), independent component analysis (ICA), and nonnegative tensor factorization (NTF) to filter averaged EEG in time, frequency and space domains to sequentially and simultaneously obtain the pure ERP of interest. Software of the proposed approaches will be open-accessed. Contents:IntroductionWavelet Filter Design Based on Frequency Responses for Filtering ERP Data With Duration of One EpochIndividual-Level ICA to Extract the ERP Components from the Averaged EEG DataMulti-Domain Feature of the ERP Extracted by NTF: New Approach for Group-Level Analysis of ERPsAnalysis of Ongoing EEG by NTF During Real-World Music ExperiencesAppendix: Introduction to Basic Knowledge of Mismatch Negativity Readership: Undergraduate, graduate, researchers and professionals in the field of neurology/neuroscience, medical imaging, psychology, biomedical engineering and computer science. Key Features:Advanced signal processing approaches can be applied on averaged EEG to extract ERPs' componentsFiltering ERPs in time, frequency and space domains sequentially and simultaneouslyDemo of ERP data and MATLAB codes are open-access for the advanced signal processing approaches on ERPsKeywords:Event-Related Potentials (ERPs);Digital Filter;Wavelet Filter;Independent Component Analysis;Tensor Decomposition;Nonnegative Tensor Factorization;Time-Frequency Representation
Invasive Studies of the Human Epileptic Brain by Samden D. Lhatoo,Philippe Kahane,Hans O. Luders Pdf
No other neurological condition allows the same opportunities for an intracranial electrophysiological study of the human brain as epilepsy does. Epileptic surgery is designed to remove the epileptic focus from the human brain, thereby effecting either cure or substantial reduction of seizures in an individual with an otherwise intractable condition. Its use as a treatment modality dates from the late 19th century, and it has become a widely used treatment option throughout the world in the last 20-30 years. The complexity of epilepsy cases in surgical centres, and the need for invasive electrode studies for pre-surgical evaluation, are both greatly increasing. Invasive Studies of the Human Epileptic Brain is the definitive reference text on the use of invasive electroencephalographic (EEG) diagnostic studies in human epilepsy. Written by some of the most renowned epilepsy experts of the 20th and 21st centuries, the authors provide their expertise and insights into the identification and mapping of intracranial epileptiform and non-epileptiform activity, mapping of the human brain function, and approaches in the use of invasive electroencephalography in a variety of clinical situations. The book is organized into an easily readable series of chapters and is brilliantly illustrated with case studies; each providing an intuitively comprehensive approach to invasive brain studies.
An Introduction to the Event-Related Potential Technique, second edition by Steven J. Luck Pdf
An essential guide to designing, conducting, and analyzing event-related potential (ERP) experiments, completely updated for this edition. The event-related potential (ERP) technique, in which neural responses to specific events are extracted from the EEG, provides a powerful noninvasive tool for exploring the human brain. This volume describes practical methods for ERP research along with the underlying theoretical rationale. It offers researchers and students an essential guide to designing, conducting, and analyzing ERP experiments. This second edition has been completely updated, with additional material, new chapters, and more accessible explanations. Freely available supplementary material, including several online-only chapters, offer expanded or advanced treatment of selected topics. The first half of the book presents essential background information, describing the origins of ERPs, the nature of ERP components, and the design of ERP experiments. The second half of the book offers a detailed treatment of the main steps involved in conducting ERP experiments, covering such topics as recording the EEG, filtering the EEG and ERP waveforms, and quantifying amplitudes and latencies. Throughout, the emphasis is on rigorous experimental design and relatively simple analyses. New material in the second edition includes entire chapters devoted to components, artifacts, measuring amplitudes and latencies, and statistical analysis; updated coverage of recording technologies; concrete examples of experimental design; and many more figures. Online chapters cover such topics as overlap, localization, writing and reviewing ERP papers, and setting up and running an ERP lab.
This volume presents the first systematic overview of how event-related brain potential (ERP), cognitive electroencephalography (EEG), and functional magnetic imaging (fMRI) measures reflect the mental events arising from changes in sensory stimulation. The contents are fresh, the literature distillations highly informative, and the range of topics extremely useful for cognitive neuroscientists, psychologists, and researchers.
Author : Mark A. Kramer,Uri T. Eden Publisher : MIT Press Page : 385 pages File Size : 54,7 Mb Release : 2016-11-04 Category : Science ISBN : 9780262529372
Case Studies in Neural Data Analysis by Mark A. Kramer,Uri T. Eden Pdf
A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.
EEG Signal Processing and Feature Extraction by Li Hu,Zhiguo Zhang Pdf
This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.
Author : Steven J. Luck,Emily S. Kappenman Publisher : Oxford University Press Page : 664 pages File Size : 53,7 Mb Release : 2013-07-04 Category : Medical ISBN : 9780199328048
This book introduces and reviews all of the currently available methods being used for computational electroencephalogram (EEG) analysis, from the fundamentals through to the state-of-the-art. The aim of the book is to help biomedical engineers and medical doctors who use EEG to better understand the methods and applications of computational EEG analysis from a single, well-organized resource. Following a brief introduction to the principles of EEG and acquisition techniques, the book is divided into two main sections. The first of these covers analysis methods, beginning with preprocessing, and then describing EEG spectral analysis, event-related potential analysis, source imaging and multimodal neuroimaging, and functional connectivity analysis. The following section covers application of EEG analysis to specific fields, including the diagnosis of psychiatric diseases and neurological disorders, brain-computer interfacing, and social neuroscience. Aimed at practicing medical specialists, engineers, researchers and advanced students, the book features contributions from world-renowned biomedical engineers working across a broad spectrum of computational EEG analysis techniques and EEG applications.
