S.B. Baumann

Bio: S.B. Baumann is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Conductivity. The author has an hindex of 1, co-authored 1 publications receiving 421 citations.

The electrical conductivity of human cerebrospinal fluid at body temperature

Abstract: The electrical conductivity of human cerebrospinal fluid (CSF) from seven patients was measured at both room temperature (25/spl deg/C) and body temperature (37/spl deg/C). Across the frequency range of 10 Hz-10 kHz, room temperature conductivity was 1.45 S/m, but body temperature conductivity was 1.79 S/m, approximately 23% higher. Modelers of electrical sources in the human brain have underestimated human CSF conductivity by as much as 44% for nearly two decades, and this should be corrected to increase the accuracy of source localization models.

Conductivity tensor mapping of the human brain using diffusion tensor MRI

Abstract: Knowledge of the electrical conductivity properties of excitable tissues is essential for relating the electromagnetic fields generated by the tissue to the underlying electrophysiological currents. Efforts to characterize these endogenous currents from measurements of the associated electromagnetic fields would significantly benefit from the ability to measure the electrical conductivity properties of the tissue noninvasively. Here, using an effective medium approach, we show how the electrical conductivity tensor of tissue can be quantitatively inferred from the water selfdiffusion tensor as measured by diffusion tensor magnetic resonance imaging. The effective medium model indicates a strong linear relationship between the conductivity and diffusion tensor eigenvalues (respectively, s and d) in agreement with theoretical bounds and experimental measurements presented here (syd ’ 0.844 6 0.0545 Szsymm3, r2 5 0.945). The extension to other biological transport phenomena is also discussed.

Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS).

Abstract: Techniques for electrical brain stimulation (EBS), in which weak electrical stimulation is applied to the brain, have been extensively studied in various therapeutic brain functional applications. The extracellular fluid in the brain is a complex electrolyte that is composed of different types of ions, such as sodium (Na+), potassium (K+), and calcium (Ca+). Abnormal levels of electrolytes can cause a variety of pathological disorders. In this paper, we present a novel technique to visualize the total electrolyte concentration in the extracellular compartment of biological tissues. The electrical conductivity of biological tissues can be expressed as a product of the concentration and the mobility of the ions. Magnetic resonance electrical impedance tomography (MREIT) investigates the electrical properties in a region of interest (ROI) at low frequencies (below 1 kHz) by injecting currents into the brain region. Combining with diffusion tensor MRI (DT-MRI), we analyze the relation between the concentration of ions and the electrical properties extracted from the magnetic flux density measurements using the MREIT technique. By measuring the magnetic flux density induced by EBS, we propose a fast non-iterative technique to visualize the total extracellular electrolyte concentration (EEC), which is a fundamental component of the conductivity. The proposed technique directly recovers the total EEC distribution associated with the water transport mobility tensor.

Review on solving the forward problem in EEG source analysis

Abstract: Background The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes.