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Biophysical model for measurement of brain tissue conductivity and diagnostic applications

Abstract : We aimed at providing an accurate estimation of human brain tissue electrical conductivity in clinico, using local, low-intensity pulsed stimulation. Methods: Using the quasi-static approximation of Maxwell equations, we derived an analytical model of the electric field generated by intracerebral stereotactic-EEG (SEEG) electrodes. We coupled this electric field model with a model of the electrode-electrolyte interface to provide an explicit, analytical expression of brain tissue conductivity based on the recorded brain tissue response to pulse stimulation. Results: We validated our biophysical model using: i) saline solutions calibrated in electrical conductivity, ii) rat brain tissue, and iii) electrophysiological data recorded in clinico from two epileptic patients during SEEG. Conclusion: This new model-based method offers a fast and reliable estimation of brain tissue electrical conductivity by accounting for contributions from the electrode-electrolyte interface. Significance: This method outperforms standard bioimpedance measurements since it provides absolute (as opposed to relative) changes in brain tissue conductivity. Application for diagnosis is envisioned since conductivity values strongly differ when estimated in the healthy vs. hyperexcitable brain tissue.
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https://tel.archives-ouvertes.fr/tel-01978679
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Submitted on : Friday, January 11, 2019 - 4:33:06 PM
Last modification on : Wednesday, September 9, 2020 - 4:02:20 AM

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  • HAL Id : tel-01978679, version 1

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Andrés Nicolás Carvallo Pecci. Biophysical model for measurement of brain tissue conductivity and diagnostic applications. Signal and Image processing. Université Rennes 1, 2018. English. ⟨NNT : 2018REN1S039⟩. ⟨tel-01978679⟩

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