We have been investigating several biophysical mechanisms associated with neuronal excitation that may be possible to measure and map using MRI. Uri Nevo, a former SQITS 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 water transport processes occurring at many different length scales (cell streaming, water flow across membranes, etc.) could be the basis of a new biophysically based fMRI method. 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 judiciously analyzing 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 visting fellow, Ruiliang Bai, who continues to investigate possible relationships between neuronal excitation and MRI contrasts. 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. Both Dan Benjamini and Ruiliang Bai have actively been developing methods to make migrate 2D relaxation spectroscopic imaging into viable pre-clinical methods which may be valuable in assessing water transport between different compartments within neurons or axons associated with excitation. 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 SQITS, 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 brin 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 neuronal 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 colleague Mark George (NIMH) and Eric Wassermann (NINDS). Despite its growing use and FDA approval for treating persistent clinical depression and migraines, it is still not known what the mechanism of 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 surprising offshoot of this TMS project has been the recent study of the possible anti-mitotic effect of applied electric fields and their therapeutic use in treating brain cancers, particularly Glioblastoma Multiforme (GBM). The electric fields used in this application are in the 100-300 kHz frequency range and have an amplitude of approximately 1 V/cm or greater. According to our calculations, these fields will not cause neural stimulation, but may be able to interfere with mitotic spindle formation, required for cell division, or interfere with cell membrane pinching, which occurs just before two daughter cells are formed from one parent cell. We proposed that an efficient means to deliver electric fields to brain regions is by electromagnetic induction rather than using electrodes placed on the skin. This idea resulted in a patent application for devices that could be used to assess the effect of electric fields on tissue as well as therapeutic devices for treating various brain cancers. Although in a preliminary stage of development, our group continues to work on advancing this technology. We believe that in addition to its possibly clinical applications, it may provide us with a means to perturb normally developing cells to help better understand different biophysical forces and flows at work during different phases of the cell cycle.

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20
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2017
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U.S. National Inst/Child Hlth/Human Dev
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Bai, Ruiliang; Stewart, Craig V; Plenz, Dietmar et al. (2016) Assessing the sensitivity of diffusion MRI to detect neuronal activity directly. Proc Natl Acad Sci U S A 113:E1728-37
Benjamini, Dan; Komlosh, Michal E; Holtzclaw, Lynne A et al. (2016) White matter microstructure from nonparametric axon diameter distribution mapping. Neuroimage 135:333-44
Wenger, Cornelia; Salvador, Ricardo; Basser, Peter J et al. (2016) Improving Tumor Treating Fields Treatment Efficacy in Patients With Glioblastoma Using Personalized Array Layouts. Int J Radiat Oncol Biol Phys 94:1137-43
Wenger, Cornelia; Salvador, Ricardo; Basser, Peter J et al. (2015) The electric field distribution in the brain during TTFields therapy and its dependence on tissue dielectric properties and anatomy: a computational study. Phys Med Biol 60:7339-57
Fields, R Douglas; Woo, Dong Ho; Basser, Peter J (2015) Glial Regulation of the Neuronal Connectome through Local and Long-Distant Communication. Neuron 86:374-86
Bai, Ruiliang; Koay, Cheng Guan; Hutchinson, Elizabeth et al. (2014) A framework for accurate determination of the T? distribution from multiple echo magnitude MRI images. J Magn Reson 244:53-63
Bai, Ruiliang; Basser, Peter J; Briber, Robert M et al. (2014) NMR Water Self-Diffusion and Relaxation Studies on Sodium Polyacrylate Solutions and Gels in Physiologic Ionic Solutions. J Appl Polym Sci 131:
Miranda, Pedro C; Mekonnen, Abeye; Salvador, Ricardo et al. (2014) Predicting the electric field distribution in the brain for the treatment of glioblastoma. Phys Med Biol 59:4137-47
Pajevic, S; Basser, P J; Fields, R D (2014) Role of myelin plasticity in oscillations and synchrony of neuronal activity. Neuroscience 276:135-47
Salvador, R; Silva, S; Basser, P J et al. (2011) Determining which mechanisms lead to activation in the motor cortex: a modeling study of transcranial magnetic stimulation using realistic stimulus waveforms and sulcal geometry. Clin Neurophysiol 122:748-58

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