Magnetic Source Imaging of the Human Brain

Magnetic Source Imaging of the Human Brain
Author: Zhong-Lin Lu
Publisher: Taylor & Francis
Total Pages: 415
Release: 2003-10-17
Genre: Psychology
ISBN: 1135625689

This book is designed to acquaint serious students, scientists, and clinicians with magnetic source imaging (MSI)--a brain imaging technique of proven importance that promises even more important advances. The technique permits spatial resolution of neural events on a scale measured in millimeters and temporal resolution measured in milliseconds. Although widely mentioned in literature dealing with cognitive neuroscience and functional brain imaging, there is no single book describing both the foundations and actual methods of magnetoencephalopgraphy and its underlying science, neuromagnetism. This volume fills a long-standing need, as it is accessible to scientists and students having no special background in the field, and makes it possible for them to understand this literature and undertake their own research. A self-contained unit, this book covers MSI from beginning to end, including its relationship to allied technologies, such as electroencephalography and modern functional imaging modalities. In addition, the book: *introduces the field to the non-specialist, providing a framework for the rest of the book; *provides a thorough review of the physiological basis of MSI; *describes the mathematical bases of MSI--the forward and inverse problems; *outlines new signal processing methods that extract information from single-trial MEG; *depicts the early, as well as the most recent versions of MSI technology; *compares MSI with other imaging methodologies; *describes new paradigms and analysis techniques in applying MSI to study human perception and cognition, which are also applicable to EEG; and *reviews some of the most important results in MSI from the most prominent researchers and laboratories around the world.

PARALLEL IMPLEMENTATION OF THE BOUNDARY ELEMENT METHOD FOR ELECTROMAGNETIC SOURCE IMAGING OF THE HUMAN BRAIN.

PARALLEL IMPLEMENTATION OF THE BOUNDARY ELEMENT METHOD FOR ELECTROMAGNETIC SOURCE IMAGING OF THE HUMAN BRAIN.
Author:
Publisher:
Total Pages:
Release: 2005
Genre:
ISBN:

Human brain functions are based on the electrochemical activity and interaction of the neurons constituting the brain. Some brain diseases are characterized by abnormalities of this activity. Detection of the location and orientation of this electrical activity is called electro-magnetic source imaging (EMSI) and is of signicant importance since it promises to serve as a powerful tool for neuroscience. Boundary Element Method (BEM) is a method applicable for EMSI on realistic head geometries that generates large systems of linear equations with dense matrices. Generation and solution of these matrix equations are time and memory consuming due to the size of the matrices and high computational complexity of direct methods. This study presents a relatively cheap and e ective solution the this problem and reduces the processing times to clinically acceptable values using parallel cluster of personal computers on a local area network. For this purpose, a cluster of 8 workstations is used. A parallel BEM solver is implemented that distributes the model eciently to the processors. The parallel solver for BEM is developed using the PETSc library. The performance of the iv solver is evaluated in terms of CPU and memory usage for di erent number of processors. For a 15011 node mesh, a speed-up eciency of 97.5% is observed when computing transfer matrices. Individual solutions can be obtained in 520 ms on 8 processors with 94.2% parallellization eciency. It was observed that workstation clusters is a cost e ective tool for solving complex BEM models in clinically acceptable time. E ect of parallelization on inverse problem is also demonstrated by a genetic algorithm and very similar speed-up is obtained.

Magnetoencephalography,An Issue of Neuroimaging Clinics of North America

Magnetoencephalography,An Issue of Neuroimaging Clinics of North America
Author: Roland Lee
Publisher: Elsevier Health Sciences
Total Pages: 153
Release: 2020-06-21
Genre: Medical
ISBN: 0323709419

This issue of Neuroimaging Clinics of North America focuses on Magnetoencephalography (MEG), and is edited by Drs. Roland Lee and Mingxiong Huang. Articles will include: MEG signal processing, forward modeling, MEG inverse source imaging, and Coherence analysis; Magnetoencephalography for pre-surgical functional mapping; Magnetoencephalography for mild TBI and PTSD; Magnetoencephalography for autism; Magnetoencephalography for schizophrenia; Magnetoencephalography for Alzheimer's disease; Pediatric Magnetoencephalography; The MEG Measurement Techniques; MEG and Language/Linguistics; MEG for Epilepsy; Integration of MEG results into the patient workup – Merging multiple modalities; and more!

Clinical Magnetoencephalography and Magnetic Source Imaging

Clinical Magnetoencephalography and Magnetic Source Imaging
Author: Andrew C. Papanicolaou
Publisher: Cambridge University Press
Total Pages: 220
Release: 2009-08-13
Genre: Medical
ISBN: 0521873754

The first volume on clinical magnetoencephalography and magnetic source imaging, measuring the magnetic fields generated by neuronal activity in the brain.

Adaptive Spatial Filters for Electromagnetic Brain Imaging

Adaptive Spatial Filters for Electromagnetic Brain Imaging
Author: Kensuke Sekihara
Publisher: Springer Science & Business Media
Total Pages: 247
Release: 2008-05-30
Genre: Technology & Engineering
ISBN: 3540793704

Neural activity in the human brain generates coherent synaptic and intracellular currents in cortical columns that create electromagnetic signals which can be measured outside the head using magnetoencephalography (MEG) and electroencephalography (EEG). Electromagnetic brain imaging refers to techniques that reconstruct neural activity from MEG and EEG signals. Electromagnetic brain imaging is unique among functional imaging techniques for its ability to provide spatio-temporal brain activation profiles that reflect not only where the activity occurs in the brain but also when this activity occurs in relation to external and internal cognitive events, as well as to activity in other brain regions. Adaptive spatial filters are powerful algorithms for electromagnetic brain imaging that enable high-fidelity reconstruction of neuronal activity. This book describes the technical advances of adaptive spatial filters for electromagnetic brain imaging by integrating and synthesizing available information and describes various factors that affect its performance. The intended audience include graduate students and researchers interested in the methodological aspects of electromagnetic brain imaging.

Multimodal Imaging in Neurology

Multimodal Imaging in Neurology
Author: Hans-Peter Müller
Publisher: Morgan & Claypool Publishers
Total Pages: 85
Release: 2008
Genre: Brain
ISBN: 1598295500

The field of brain imaging is developing at a rapid pace and has greatly advanced the areas of cognitive and clinical neuroscience. The availability of neuroimaging techniques, especially magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging (DTI) and magnetoencephalography (MEG) and magnetic source imaging (MSI) has brought about breakthroughs in neuroscience. To obtain comprehensive information about the activity of the human brain, different analytical approaches should be complemented. Thus, in "intermodal multimodality" imaging, great efforts have been made to combine the highest spatial resolution (MRI, fMRI) with the best temporal resolution (MEG or EEG). "Intramodal multimodality" imaging combines various functional MRI techniques (e.g., fMRI, DTI, and/or morphometric/volumetric analysis). The multimodal approach is conceptually based on the combination of different noninvasive functional neuroimaging tools, their registration and cointegration. In particular, the combination of imaging applications that map different functional systems is useful, such as fMRI as a technique for the localization of cortical function and DTI as a technique for mapping of white matter fiber bundles or tracts. This booklet gives an insight into the wide field of multimodal imaging with respect to concepts, data acquisition, and postprocessing. Examples for intermodal and intramodal multimodality imaging are also demonstrated.

Recent Advances in Human Brain Mapping

Recent Advances in Human Brain Mapping
Author: International Society for Brain Electromagnetic Topography. World Congress
Publisher:
Total Pages: 966
Release: 2002
Genre: Medical
ISBN:

These proceedings cover a wide range of topics in the field of brain function mapping; from basic neuroscience to clinical applications. It provides an important overview of brain mapping research and will be useful reading for the neuroscientist who intends to clarify the brain function using physiological or imaging techniques. Techniques used include EEG, ERP, PET, SPECT, MEG, MRI, MRS, fMRI and optic topography.

Electromagnetic Inverse Applications for Functional Brain Imaging

Electromagnetic Inverse Applications for Functional Brain Imaging
Author:
Publisher:
Total Pages: 4
Release: 1997
Genre:
ISBN:

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). This project addresses an important mathematical and computational problem in functional brain imaging, namely the electromagnetic {open_quotes}inverse problem.{close_quotes} Electromagnetic brain imaging techniques, magnetoencephalography (MEG) and electroencephalography (EEG), are based on measurements of electrical potentials and magnetic fields at hundreds of locations outside the human head. The inverse problem is the estimation of the locations, magnitudes, and time-sources of electrical currents in the brain from surface measurements. This project extends recent progress on the inverse problem by combining the use of anatomical constraints derived from magnetic resonance imaging (MRI) with Bayesian and other novel algorithmic approaches. The results suggest that we can achieve significant improvements in the accuracy and robustness of inverse solutions by these two approaches.