We have been investigating several biophysical processes that may be associated with neuronal excitation and their relationship to a measured MR signal. Uri Nevo, a former STBB post-doctoral fellow, and now Senior Lecturer at Tel Aviv University, successfully constructed and tested an experimental system in our lab to interrogate organotypic cultured brain cortical slices using diffusion MRI. This work showed promising preliminary results, relating changes in the measured apparent diffusion coefficient (ADC) map to environmental challenges to which these cultured tissues were subjected. One hypothesis that emerged from these studies is that active processes occurring at many different length scales (cell streaming, water flow across membranes, etc.) are responsible for a portion of the reduction in the diffusion weighted MRI signal observed in stroke. This insight prompted the development of a theory to explain how microscopic fluid flows affect the measured diffusion weighted MRI signal and possibly the ADC measured in tissues (i.e., pseudo-diffusion) as well as an experimental model test system, a modified Rheo-NMR instrument, in which well-characterized flow field distributions can be produced that result in a predictable amount of pseudo-diffusion. The importance of these combined theoretical and experimental studies is that if such microscopic motions, like streaming, water flow across membranes, etc., manifest themselves as additional signal loss in diffusion weighted MRI, then we could use this information to infer distinct aspects of cell function and vitality, including features of excitability by a judicious analysis of the MRI data. This idea represents a significant advance over the prior Intravoxel Incoherent Motion (IVIM) concept proposed by Le Bihan et al, which only considers the effect of random water motions caused by microcirculatory flows as contributing to observed pseudo-diffusion in vivo. We are continuing and expanding these studies with our doctoral student in Biophysics from the University of Maryland, Ruiliang Bai. This year, Dr Bai received his Ph.D. for research conducted in our lab investigating possible relationships between neuronal excitation and different types of MRI contrast. These findings are currently being submitted to high-impact journals for their consideration. Another area of interest has been in improving our measurement of exchange processes in living tissue, particularly taking advantage of advanced data compression techniques to obtain 1D and 2D relaxation spectra suitable for in vitro and in vivo studies. We have also been involved in complementary studies to understand how induced electric and magnetic fields are distributed within the brain and how they could selectively affect different neuronal populations. Pedro Miranda and his research group at the University of Lisbon, in association with STBB, has performed detailed calculations using the finite element method (FEM) to predict the electric field and current density distributions induced in the brain during Transcranial Magnetic Stimulation (TMS). Previously, we found that both tissue heterogeneity and anisotropy of the electrical conductivity (i.e., the electrical conductivity tensor field) distort these induced fields, and even create excitatory or inhibitory hot spots in some regions that were previously not predicted. More recently, we developed realistic FEM models of cortical folds, containing gyri and sulci, showing that this more complicated cortical anatomy can also significantly affect the induced electric field distribution within the tissue, and the location and types of nerve cells that could be excited or depressed by such stimuli. More recently, we have been developing full 3D models of electric field deposition within the brain, obtained from 3D diffusion tensor MRI data. We are continuing to marry our macroscopic FEM models of TMS with microscopic models of nerve excitability in the CNS in order to predict the locus of excitation in TMS and even the populations of neurons that are excited or depressed. This knowledge is important to have in addressing, for instance, the safety and basis of efficacy of TMS for the treatment of clinical depression--an application we helped pioneer in the early '90s with our then colleagues Mark George in NIMH and Eric Wassermann in NINDS. Despite its growing use and FDA approval for treating persistent depression and migraines, it is still not known what the action of induced electromagnetic fields is in the brain in therapeutic TMS, and specifically which and what populations of nerves TMS might trigger or depress when applied. Our research attempts to provide a biophysical basis for understanding the physiology of this and other clinical applications of TMS to help in part assess its safety and efficacy. More recent studies of ours have focused on the microscopic effects of these electric and magnetic fields on cells in the nervous system, moving from the macro to the microscale in our modeling activities. Moreover, we have not limited ourselves to TMS. Recently, we have also been applying these advanced FEM models to explain the physical basis for Direct Current Excitation (DCE) as well as other therapeutic uses of AC electric fields at different frequencies on the brain. An offshoot of this project has also been the unexpected development of an FEM modeling framework to predict applied electric fields and their therapeutic use in interfering with mitotic processes in brain cancers, particularly to treat Glioblastoma Multiforme (GBM). This promising research activity has already resulted in a patent application.
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