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Biophysical modeling for brain tissue conductivity estimation using sEEG electrodes

Abstract : OBJECTIVE: 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 stereoelectroencephalography (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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Contributor : Julien Modolo <>
Submitted on : Wednesday, November 7, 2018 - 11:44:33 AM
Last modification on : Saturday, March 21, 2020 - 11:28:10 AM



Andres Carvallo, Julien Modolo, Pascal Benquet, Stanislas Lagarde, Fabrice Bartolomei, et al.. Biophysical modeling for brain tissue conductivity estimation using sEEG electrodes. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2019, 66 (6), pp.1695-1704. ⟨10.1109/TBME.2018.2877931⟩. ⟨inserm-01914973⟩



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