A multimodal neuroimaging study of somatosensory system

The thesis is the result of a training by the Magnetoencephalography (MEG)-lab by the Center mind/brain science of the university of Trento. Final goal of the analysis was answering the question if MEG is capable to capture activities from the subcortical brain areas and to follow the neural information flow up along the fibers to the cortex. First aim of the thesis is describing the project and developing of an experiment on the somatosensory system that I executed by the CIMeC. The somatosensory system was activated by applying electrical stimulation to the median nerve and MEG signal during this stimulation was recorded. Also MRI and diffusion MRI data of the subject were collected. Further aim of the thesis is to describe the analysis I executed on the collected data. For this purpose the MEG source localization was executed and also Monte-Carlo simulation. The data obtained were integrated with the information obtained from diffusion MRI. Satisfactory results were obtained although we could not prove definitely the result

Spatio-temporal analysis in functional brain imaging

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 119-137).Localizing sources of activity from electroencephalography (EEG) and magnetoencephalography (MEG) measurements involves solving an ill-posed inverse problem, where infinitely many source distribution patterns can give rise to identical measurements. This thesis aims to improve the accuracy of source localization by incorporating spatio-temporal models into the reconstruction procedure. First, we introduce a novel method for current source estimation, which we call the l₁l₂-norm source estimator. The underlying model captures the sparseness of the active areas in space while encouraging smooth temporal dynamics. We compute the current source estimates efficiently by solving a second-order cone programming problem. By considering all time points simultaneously, we achieve accurate and stable results as confirmed by the experiments using simulated and human MEG data. Although the l₁l₂-norm estimator enables accurate source estimation, it still faces challenges when the current sources are close to each other in space. To alleviate problems caused by the limited spatial resolution of EEG/MEG measurements, we introduce a new method to incorporate information from functional magnetic resonance imaging (fMRI) into the estimation algorithm.(cont.) Whereas EEG/MEG record neural activity, fMRI reflects hemodynamic activity in the brain with high spatial resolution. We examine empirically the neurovascular coupling in simultaneously recorded MEG and diffuse optical imaging (DOI) data, which also reflects hemodynamic activity and is compatible with MEG recordings. Our results suggest that the neural activity and hemodynamic responses are aligned in space. However, the relationship between the temporal dynamics of the two types of signals is non-linear and varies from region to region. Based on these findings, we develop the fMRI-informed regional EEG/MEG source estimator (FIRE). This method is based on a generative model that encourages similar spatial patterns but allows for differences in time courses across imaging modalities. Our experiments with both Monte Carlo simulation and human fMRI-EEG/MEG data demonstrate that FIRE significantly reduces ambiguities in source localization and accurately captures the timing of activation in adjacent functional regions.by Wanmei Ou.Ph.D

Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.Peer reviewe