Quo vadis, MEG?
Matti Hämäläinen, Professor of Radiology, Harvard Medical School,
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, USA
Magnetoencephalography (MEG) was established as a viable method to study brain function when David Cohen recorded the first real-time magnetoencephalogram at MIT in 1971 using a SQUID magnetometer. Very soon after these pioneering measurements the technology landed in Otaniemi. With Olli Lounasmaa and Riitta Hari as the torchbearers, a multidisciplinary research group at the Low Temperature Laboratory (LTL) of Helsinki University of Technology (Aalto University) was in the forefront of the development of MEG technology and its applications: they produced the first whole-head MEG system with more than 100 channels in 1992. This instrument was subsequently commercialized by Neuromag, a spinoff of LTL, and expanded to provide higher-density sampling with 306 sensors. The key to this success was the existence of the vibrant interactions between neuroscientists, clinicians, physicists, mathematicians, and engineers who worked on the instrumentation, analysis methods, and the actual neuroscience and clinical applications together in close proximity.
During this century, one hallmark of MEG has been the widespread use of high-quality opensource academic software packages, which have enhanced the rigor and reproducibility of scientific investigations using MEG. With the advent of low-noise room-temperature magnetic field sensors we are now at the verge of a revolution which will critically improve the sensitivity and spatial resolution of MEG and allow MEG recordings together with transcranial magnetic brain stimulation (TMS). These new devices also also enable adaptation of the MEG array to the size of the head so that a high signal-to-noise ratio can be achieved even in developmental studies. To fully capitalize on these advances, one needs improvements to forward and inverse modeling techniques, as well as to biophysical models of assemblies of neurons. The latter make it possible to suggest mechanisms underlying the observed macroscopic neural currents and provide links animal models to human MEG data. The only established clinical applications of MEG are characterization of epileptic activity and presurgical mapping of eloquent cortex. However, new studies of, e.g., the autism spectrum disorders, give hope that MEG, used in combination with EEG and other non-invasive brain imaging methods, can be in the future harnessed for better diagnosis and for monitoring the efficacy of treatments of several neurological and psychiatric diseases.
Diffusion MRI: Recent advances and applications
Timo Roine, Postdoctoral Researcher, Department of Neuroscience and Biomedical Engineering, Aalto University
Diffusion MRI can be used to noninvasively investigate structural brain connectivity through the reconstruction of neural pathways. I will present and discuss the limitations and strengths of various methods used for the analysis of structural brain connectivity and white matter microstructure. In addition, recent research applying these methods in clinical samples is presented.