Eeg Meg Source Reconstruction

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.

The 41st Annual International Conference of the IEEE EMBS, took place between July 23 and 27, 2019, in Berlin, Germany. The focus was on "Biomedical engineering ranging from wellness to intensive care." This conference provided an opportunity for researchers from academia and industry to discuss a variety of topics relevant to EMBS and hosted the 4th Annual Invited Session on Computational Human Models. At this session, a bevy of research related to the development of human phantoms was presented, together with a substantial variety of practical applications explored through simulation.

Magnetoencephalography (MEG) is an invaluable functional brain imaging technique that provides direct, real-time monitoring of neuronal activity necessary for gaining insight into dynamic cortical networks. Our intentions with this book are to cover the richness and transdisciplinary nature of the MEG field, make it more accessible to newcomers and experienced researchers and to stimulate growth in the MEG area. The book presents a comprehensive overview of MEG basics and the latest developments in methodological, empirical and clinical research, directed toward master and doctoral students, as well as researchers. There are three levels of contributions: 1) tutorials on instrumentation, measurements, modeling, and experimental design; 2) topical reviews providing extensive coverage of relevant research topics; and 3) short contributions on open, challenging issues, future developments and novel applications. The topics range from neuromagnetic measurements, signal processing and source localization techniques to dynamic functional networks underlying perception and cognition in both health and disease. Topical reviews cover, among others: development on SQUID-based and novel sensors, multi-modal integration (low field MRI and MEG; EEG and fMRI), Bayesian approaches to multi-modal integration, direct neuronal imaging, novel noise reduction methods, source-space functional analysis, decoding of brain states, dynamic brain connectivity, sensory-motor integration, MEG studies on perception and cognition, thalamocortical oscillations, fetal and neonatal MEG, pediatric MEG studies, cognitive development, clinical applications of MEG in epilepsy, pre-surgical mapping, stroke, schizophrenia, stuttering, traumatic brain injury, post-traumatic stress disorder, depression, autism, aging and neurodegeneration, MEG applications in cognitive neuropharmacology and an overview of the major open-source analysis tools.

This book constitutes the refereed proceedings of the 15th International Conference on Brain Informatics, BI 2022, held as hybrid event in Padua, Italy (in person) and Queensland, Australia (online) in July 2022. The 29 papers were selected from 65 submissions and the main theme of BI 2022 is Brain Science meets Artificial Intelligence with respect to the five tracks: Cognitive and computational foundations of brain science; human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain inspired computing.

This book constitutes the proceedings of the 16th International Conference on Brain Informatics, BI 2023, which was held in Hoboken, NJ, USA, during August 1–3, 2023. The 40 full papers presented in this book were carefully reviewed and selected from 101 submissions. The papers are divided into the following topical sections: cognitive and computational foundations of brain science; investigations of human Information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; brain-machine intelligence and brain-inspired computing; and the 5th international workshop on cognitive neuroscience of thinking and reasoning.

Brain Mapping: A Comprehensive Reference offers foundational information for students and researchers across neuroscience. With over 300 articles and a media rich environment, this resource provides exhaustive coverage of the methods and systems involved in brain mapping, fully links the data to disease (presenting side by side maps of healthy and diseased brains for direct comparisons), and offers data sets and fully annotated color images. Each entry is built on a layered approach of the content – basic information for those new to the area and more detailed material for experienced readers. Edited and authored by the leading experts in the field, this work offers the most reputable, easily searchable content with cross referencing across articles, a one-stop reference for students, researchers and teaching faculty. Broad overview of neuroimaging concepts with applications across the neurosciences and biomedical research Fully annotated color images and videos for best comprehension of concepts Layered content for readers of different levels of expertise Easily searchable entries for quick access of reputable information Live reference links to ScienceDirect, Scopus and PubMed

One of the major challenges in science is to study and understand the human brain. Numerous methods examining different aspects of brain functions have been developed and employed. To study systemic interactions brain networks in vivo, non-invasive methods such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used with great success. However, each of these methods can map only certain, quite selective aspects of brain function while missing others; and the inferences on neuronal processes and information flow are often rather indirect. To overcome these shortcomings of single methods, researchers have attempted to combine methods in order to make optimal use of their advantages while compensating their disadvantages. Hence, it is not surprising that soon after the introduction of fMRI as a neuroimaging method the possibilities of combinations with EEG have been explored. This book is intended to aid researchers who plan to set up a simultaneous EEG-fMRI laboratory and those who are interested in integrating electrophysiological and hemodynamic data. As will be obvious from the different chapters, this is a dynamically developing field in which several approaches are being tested, validated and compared. Currently, there is no one best solution for all problems available, but many promising techniques are emerging. This book shall give a comprehensive overview of these techniques. In addition, it points to open questions and directions for future research.