We have been investigating several biophysical processes associated with nerve excitation and their relationship to the measured MR signal. Uri Nevo, a former STBB post-doctoral fellow, and now an Assistant Professor at Tel Aviv University, successfully constructed and tested an experimental system in our lab to interrogate organotypic cultured brain 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 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 some loss in the diffusion weighted MRI signal. 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) and of an experimental model system, an altered Rheo-NMR, in which well-characterized flow field distributions can be produced that result in known amounts 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. We are now continuing these studies now with a second-year doctoral student in Biophysics from the University of Maryland, Ruiliang Bai. We have also been involved in companion studies in the area of Transcranial Magnetic Stimulation (TMS) to understand how electric and magnetic fields are distributed within the brain and how they could selectively affect different populations of neuron. Pedro Miranda and his research group in 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 TMS. Previously, we found that both tissue heterogeneity and anisotropy of the electrical conductivity (i.e., the electrical conductivity tensor field) contribute significantly to distort these induced fields, and even to create excitatory or inhibitory """"""""hot spots"""""""" in some regions that were previously not predicted. More recently, we have been developing realistic FEM models of cortical folds, containing gyri and sulci, and showed that this more complicated cortical anatomy can significantly affect the distribution of induced electric fields within the tissue, and the location and types of nerve cells that could be excited or depressed by such stimuli. We are beginning 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. These knowledge 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 '90s. Despite its growing use, it is still not known what the action of induced electromagnetic fields are in the brain in therapeutic TMS, and specifically which and what populations of nerves it might trigger or depress. Our research can provide a basis for understanding the physics and physiology of this and other clinical applications of TMS. Recently, we have also been applying these advanced FEM models to explain the physical basis for Direct Current Excitation (DCE) as well as therapeutic uses of AC electric fields on the brain.
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