[BIC-announce] FW: Special Lecture on Friday February 8, 2008 at 1:00 pm - Progress and Challenges of Multimodal Imaging using MEG, EEG, MRI, & fMRI
Jennifer Chew, Ms.
jennifer.chew at mcgill.ca
Thu Jan 31 11:43:04 EST 2008
PLEASE DISCARD IF THIS IS A DUPLICATE. THANK YOU. JENNIFER
SPECIAL LECTURE
Matti S. Hämäläinen, PhD
Director, MEG Core
Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital, Charlestown, MA, USA
Progress and Challenges of Multimodal Imaging using
MEG, EEG, MRI, & fMRI
Friday February 8, 2008
1:00 pm
de Grandpré Communications Centre
Abstract of lecture:
Independently, electromagnetic and hemodynamic measurements of brain activity offer compromises between spatial and temporal resolution. fMRI is temporally limited by the slow time course of the hemodynamic response, but can provide a spatial sampling on a millimeter scale. EEG and MEG in turn provide a temporal resolution of milliseconds, but the localization of sources is more complicated because of the ill-posed electromagnetic inverse problem. Elucidating the spatial distribution and temporal orchestration of human brain regions is thus facilitated by combining information provided by both anatomical and functional MRI with EEG/MEG data.
It was recognized very early on by the MEG researchers that the spatiotemporal distribution of the magnetic field can be used to estimate the sources of the underlying brain activity. This information can be integrated with anatomical MRI data to associate the source locations with anatomical structures. Such a combination of the two methods has been often called Magnetic Source Imaging (MSI). In addition, anatomical MRI date are now employed routinely to delineate boundaries between regions of different electrical conductivities for forward field computations, to restrict the locations and orientations of the sources, and in advanced visualization techniques involving three-dimensional renderings of the cortical mantle and other structures.
The fusion of electromagnetic and hemodynamic data is still in its infancy. In the presently available modeling methods, this is usually accomplished by confining the sources to the cortical gray matter and by computing a distributed current estimate with a stronger a priori weighting at locations with significant fMRI activity. More elaborate methods which attempt to model the two data sets jointly under a common framework are also emerging. Furthermore, basic studies which aim at understanding the relationship between the hemodynamic and electromagnetic signals are ongoing and will eventually result in physiologically motivated rather than partly heuristic source estimation models.
Rather surprisingly, relatively little effort has been devoted to combination of MEG with EEG, its most obvious companion. This has been due to difficulties in collecting both types of data simultaneously with truly indentical preprocessing and to challenges in combined modelling of the two data sets. Presently, many laboratories are collecting MEG and EEG data simultaneously and exploring source models which incorporate the two types of data. Both simulations and analyses of actual data sets have shown that the combination of these two methods yields more reliable estimates of the sources than using one modality alone. Furthermore, these studies indicate that the improvement is not due to the increased number of measurement channels but is attributable to the different sensitivities of MEG and EEG to the cerebral current sources.
Short biography:
Matti Hämäläinen joined the neuromagnetism group, now known as the Brain Research Unit (BRU), at the Low Temperature Laboratory of Helsinki University of Technology (HUT) in 1981 and received his MSc and PhD degrees in 1983 and 1989, respectively. Throughout his scientific career his main research interest has been the source analysis of bioelectromagnetic measurements and the combination of MEG and EEG with other imaging methods, most notably MRI and fMRI.
Hämäläinen's about 80 peer-reviewed publications include several seminal results on MEG analysis methods and instrumentation and he has delivered more than 20 invited talks in international conferences. His findings include the introduction of minimum-norm approach for estimating the sources of MEG signals, introduction of the Bayesian statistical approach to MEG source estimation, and a novel and since then widely used approach to avoid numerical instability in the solution of the MEG/EEG forward problem with the boundary-element method. He was also a member of the core team developing the 122-channel and 306-channel whole-head neuromagnetometers in Helsinki. Together with his coworkers, he received the Innovation Prize of the Finnish National Fund for Research and Development in 1992 and The Finnish Engineering Prize in 1996. Hämäläinen has also been an active collaborator in numerous neuroscientific research projects in which MEG has been applied to reveal functional organization of the human brain. The H-index of his publications is 34, which indicates a very strong influence of his work on the scientific community. Together with his colleagues, Matti Hämäläinen published in 1993 a seminal review article on MEG in Reviews of Modern Physics, which has attracted more than 1000 citations.
From the beginning of 2001 he has been working at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital in Boston. At present he is the Director of the MEG core at the Martinos Center and Associate Professor of Radiology at Harvard Medical School. His current research interests include the development of anatomically-constrained source estimation methods, combination of electromagnetic source imaging with fMRI and NIRS, as well as frequency-domain and coherence analysis of MEG and EEG data.
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