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Brain source localization using SEEG recordings

Abstract : The surface EEG makes it possible to study the brain activity with a high temporal resolution, however it suffers from the severe attenuation of the electrical propagation through the skull bone as well as the addition of external artifacts. As an alternative, we would like to exploit the Stereo-EEG (SEEG) recordings, consisting in shaft electrodes implanted in the brain volume in the direct vicinity of the brain generators. These data benefit from a high signal to noise ratio compared to this observed in surface EEG. We propose in this thesis a feasibility study of source imaging from the SEEG, based on an equivalent current dipole inversion method associated with an analytical One-Sphere propagation model, able to bring localization precision of the order of a few millimeters. Using a typical clinical electrode implantation, we evaluate the localization performance when different subsets of sensors are considered. In the presence of realistic noise, we observe that the addition of distant sensors with respect to the source can lead to a degradation of the localization accuracy. These conclusions lead us to propose a local sensor selection approach in order to optimize the reliability of the results. The strengths and weaknesses of this approach are analyzed on a realistic simulation framework, for a relevant exploration of the different parameters impacting on the quality of the SEEG source imaging. The approaches are applied on SEEG recordings collected at the CHRU of Nancy to evaluate their performance when facing real measurements
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  • HAL Id : tel-01685079, version 1

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Vairis Caune. Brain source localization using SEEG recordings. Automatic. Université de Lorraine, 2017. English. ⟨NNT : 2017LORR0217⟩. ⟨tel-01685079⟩

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