Angelakis EEG-reading 2002a (original) (raw)
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The Role of Slow-Wave Electroencephalographic Activity in Reading
Journal of Neurotherapy, 2002
Efthymios Angelakis is a doctoral student in experimental psychology at the University of Tennessee, Knoxville, working under the supervision of Dr. Joel F. Lubar. His research is focused on the QEEG assessment and the development of a possible neurofeedback protocol for the different types of reading disabilities. Joel F. Lubar received his BS and PhD from the Division of the Biological Sciences and Department of Biopsychology at the University of Chicago. He has published more than 100 papers, many book chapters and eight books in the areas of Neuroscience and Applied Psychophysiology. He is currently a Full Professor at the University of Tennessee. He is President of the EEG Division of the Association for Applied Psychophysiology and Biofeedback (AAPB).
Human steady-state visually evoked potential topography and attention
, for providing me with a room for recording the data, and additional support from Pauline and Kathy. The six patients-your cooperation during the recordings made chapter 8 possible. The Swinburne Centre for Applied Neurosciences, for an environment promoting enjoyment in neuroscience research. Also for the availability of equipment, and control data for comparison purposes. Mr Andrew Pipingas, for your work in developing tools for the presentation of the cognitive tasks, and also for analysis routines. Mr David Simpson, the designer and constructor of most of the sixty-four channel system. Professor Richard Ball: from you I have learned so much of the English language. Thank you for your supervision of me, particularly for your encouragement and helpful advice. Professor Richard Silberstein; when I completed my first degree in 1981 you said: "Mark, I want to see a doctorate from you one day.". Thank you for the inspiration to begin, all your hard work in supervising me, and for your constructive advice in putting together and reviewing my scientific, technical, and thought processes. vii Lastly to Meredith, thank you for marrying me after I began this journey; and for all your love, encouragement, support, critique, and welcome suggestions about my research from your perspective. viii Contents Title.
American Clinical Neurophysiology Society: EEG Guidelines Introduction
The Neurodiagnostic journal, 2016
This revision to the EEG Guidelines is an update incorporating current EEG technology and practice. "Standards of practice in clinical electroencephalography" (previously Guideline 4) has been removed. It is currently undergoing revision through collaboration among multiple medical societies and will become part of "Qualifications and Responsibilities of Personnel Performing and Interpreting Clinical Neurophysiology Procedures." The remaining guidelines are reordered and renumbered.
Western electroencephalography society
Electroencephalography and Clinical Neurophysiology, 1969
Capehart, the other two members of the thesis committee, for their suggestions in the preparation of the manuscript.
Reading Your Mind: EEG during Reading Task
Lecture Notes in Computer Science, 2011
This paper demonstrates the ability to study the human reading behaviors with the use of Electroencephalography (EEG). This is a relatively new research direction because, obviously, gaze-tracking technologies are used specifically for those types of studies. We suspect, EEG, with the capability of recording brainwave activities from the human scalp, in theory, could exhibit potential attributes to replace gaze-tracking in such research. To prove the concept, in this paper, we organized a BCI experiment and propose a model for effective classifying EEG data in comparison to the accuracy of gaze-tracking. The results show that by using EEG, we could achieve comparable results against the more established methods while demonstrating a potential live EEG applications. This paper also discusses certain points of consideration for using EEG in this work.
Sanei/EEG Signal Processing, 2013
Introduction to EEG The neural activity of the human brain starts between the 17th and 23rd week of prenatal development. It is believed that from this early stage and throughout life electrical signals generated by the brain represent not only the brain function but also the status of the whole body. This assumption provides the motivation to apply advanced digital signal processing methods to the electroencephalogram (EEG) signals measured from the brain of a human subject, and thereby underpins the later chapters of the book. Although nowhere in this book do the authors attempt to comment on the physiological aspects of brain activities there are several issues related to the nature of the original sources, their actual patterns, and the characteristics of the medium, that have to be addressed. The medium defines the path from the neurons, as so-called signal sources, to the electrodes, which are the sensors where some form of mixtures of the sources are measured. Understanding of neuronal functions and neurophysiological properties of the brain together with the mechanisms underlying the generation of signals and their recordings is, however, vital for those who deal with these signals for detection, diagnosis, and treatment of brain disorders and the related diseases. A brief history of EEG measurements is first provided. 1.1 History Carlo Matteucci (1811-1868) and Emil Du Bois-Reymond (1818-1896) were the first people to register the electrical signals emitted from muscle nerves using a galvanometer and established the concept of neurophysiology [1,2]. However, the concept of action current introduced by Hermann Von Helmholz [3] clarified and confirmed the negative variations that occur during muscle contraction. Richard Caton (1842-1926), a scientist from Liverpool, England, used a galvanometer and placed two electrodes over the scalp of a human subject and thereby first recorded brain activity in the form of electrical signals in 1875. Since then, the concepts of electro-(referring to registration of brain electrical activities) encephalo-(referring to emitting the signals from the head), and gram (or graphy), which means drawing or writing, were combined so that the term EEG was henceforth used to denote electrical neural activity of the brain.
Clinical EEG and Neuroscience 1 -7
In part 1 of this article, we describe an approach and methodology that bridges 2 worlds: the internal, subjective experience of emotions and thoughts, and the external world of brain electrical activity. Using a novel event-related brain activation imaging method, we demonstrate that within single trials, short-term mental processes, on the order of 100 ms, can be clearly related to observed brain activation in controlled experiments. We use an ipsative assessment validation process that combines selfreport with real-time EEG recordings to provide a combined picture of both the mental and the brain activity, during short-term reactions, emotions, and decisions regarding controlled information. Part 2 provides a detailed description of the emerging emotional decision-making model.
The neurophysiological bases of EEG and EEG measurement: a review for the rest of us
Psychophysiology, 2014
A thorough understanding of the EEG signal and its measurement is necessary to produce high quality data and to draw accurate conclusions from those data. However, publications that discuss relevant topics are written for divergent audiences with specific levels of expertise: explanations are either at an abstract level that leaves readers with a fuzzy understanding of the electrophysiology involved, or are at a technical level that requires mastery of the relevant physics to understand. A clear, comprehensive review of the origin and measurement of EEG that bridges these high and low levels of explanation fills a critical gap in the literature and is necessary for promoting better research practices and peer review. The present paper addresses the neurophysiological source of EEG, propagation of the EEG signal, technical aspects of EEG measurement, and implications for interpretation of EEG data.