From Raw Meg Eeg To Publication How To Perform Meg Eeg Group Analysis With Free Academic Software

Language, as a system we use to communicate, represents the brain’s biologically perfected machinery for converting thoughts (ideas, concepts, and reflections of both the outside world and our inner feelings) into words and sentences. Crucially, this process occurs in real time. How hundreds of billions of neurons within the dark of the skull control language and speech remains, in some respects, a mystery. To track such neural dynamics in time, we need to exploit physiological tools capable of following temporal patterns of neural activity on a fine-grain time scale. In parallel, it is necessary to begin to provide a real interdisciplinary academic background for scholars wishing to embark on this field of study. Unlike many similar efforts, this book has been conceived as a hands-on tool offering the reader the possibility to progressively acquire principles, techniques, and methods necessary to pursue interdisciplinary research in a fascinating field intersecting linguistic and neuroscience. It focuses on neurophysiological methods and applications useful to track the high speed and rapid temporal dynamics of neural activity involved in language and speech. The chapters in this book are organized into four parts. Part One discusses neural principles and tools for an effective approach to the field of investigation. Part Two looks at the issues and perspectives concerned with the use of a range of neurophysiological technologies to investigate the neural computations of language and speech processes. Part Three focuses on an in-depth exploration of the neural processes associated with the main types of linguistic information, ranging from phonemes and prosody to syntax, pragmatics, and figurative language. Lastly, Part Five explores the phenomena that goes beyond the segments of basic linguistic units. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory Cutting-edge and thorough, Language Electrified: Principles, Methods, and Future Perspectives of Investigation is a valuable resource that offers the necessary tool-box for all researchers and scientists interested in the challenging field of the neurophysiology of language and speech.

This work provides newcomers and more experienced researchers with the very basics of magnetoencephalography (MEG) and electroencephalography (EEG)-two noninvasive methods that can inform about the neurodynamics of the human brain on a millisecond scale. These two closely related methods are addressed side by side, starting from their physical and physiological bases and then advancing to methods of data acquisition, analysis, visualization, and interpretation

Recent advances in the neuroimaging field areas allow us to visualize the aggregate of neural connections at the macroscopic level within the brain, the so-called “connectome”. In order to promote the development of the neurophysiological investigation of connectome of brain oscillations, this eBook aims at bringing together contributions from researchers in basic and clinical neuroscience using EEG and MEG connectome analysis. The most important focal point will be to address the functional roles of connectome of brain oscillations in contributing to understandings of higher cognitive processes in normal subjects and pathophysiology of psychiatric diseases. This Research Topic presented novel methodologies and various applications of neurophysiological connectome analysis. As a result, these papers were cited more than 120 times in these four years in total and threw light and impact on new directions for investigating the connectome of human brain.

This textbook provides a comprehensive and didactic introduction from the basics to the current state of the art in the field of EEG/MEG source reconstruction. Reconstructing the generators or sources of electroencephalographic and magnetoencephalographic (EEG/MEG) signals is an important problem in basic neuroscience as well as clinical research and practice. Over the past few decades, an entire theory, together with a whole collection of algorithms and techniques, has developed. In this textbook, the authors provide a unified perspective on a broad range of EEG/MEG source reconstruction methods, with particular emphasis on their respective assumptions about sources, data, head tissues, and sensor properties. An introductory chapter highlights the concept of brain imaging and the particular importance of the neuroelectromagnetic inverse problem. This is followed by an in-depth discussion of neural information processing and brain signal generation and an introduction to the practice of data acquisition. Next, the relevant mathematical models for the sources of EEG and MEG are discussed in detail, followed by the neuroelectromagnetic forward problem, that is, the prediction of EEG or MEG signals from those source models, using biophysical descriptions of the head tissues and the sensors. The main part of this textbook is dedicated to the source reconstruction methods. The authors present a theoretical framework of the neuroelectromagnetic inverse problem, centered on Bayes’ theorem, which then serves as the basis for a detailed description of a large variety of techniques, including dipole fit methods, distributed source reconstruction, spatial filters, and dynamic source reconstruction methods. The final two chapters address the important topic of assessment, including verification and validation of source reconstruction methods, and their actual application to real-world scientific and clinical questions. This book is intended as basic reading for anybody who is engaged with EEG/MEG source reconstruction, be it as a method developer or as a user, including advanced undergraduate students, PhD students, and postdocs in neuroscience, biomedical engineering, and related fields.