Denoising depth EEG signals during DBS using filtering and subspace decomposition.

In difficult epileptic patients, the brain structures are explored by means of depth multicontact electrodes [stereoelectroencephalography (SEEG)]. Recently, a novel diagnostic technique allows an accurate definition of the epileptogenic zone using deep brain stimulation (DBS). The stimulation signal propagates in the brain and thus it appears on most of the other SEEG electrodes, masking the local brain electrophysiological activity. The objective of this paper is the DBS-SEEG signals detrending and denoising in order to recover the masked physiological sources. We review the main filtering methods and put forward an approach based on the combination of filtering with generalized eigenvalue decomposition (GEVD). An experimental study on simulated and real SEEG shows that our approach is able to separate DBS sources from brain activity. The best results are obtained by an original singular spectrum analysis-GEVD approach.

Extraction of deep brain stimulation (DBS) source in SEEG using EMD and ICA.

In the context of drug resistant partial epilepsy, intra-cerebral electrical stimulation (Deep Brain Stimulation) constitutes one of the means of investigation to locate epileptic volume. This exogenous source can then activate the underlying epileptic networks and generate an electrophysiological reaction. The purpose of this work is to estimate and eliminate the overlapping electrical stimulation signal in order to subsequently explore the provoked underlying electrical activity. We propose here several methods to tackle this problem, using two different approaches based on different assumptions: BSS approach based on Independent Component Analysis (ICA) and non parametric decomposition - empirical modes decomposition (EMD) algorithms.

Propagation of electrical field in the brain using electrical intra-cerebral stimulations.

For drug resistant partial epilepsy, intra-cerebral electrical stimulation (Deep Brain Stimulation--DBS) constitutes one of the means to locate epileptic volume. This paper investigates, in the framework of source localization problem, the propagation of the electrical field and current density distribution induced in the brain during in vivo electrical stimulation. There are three objectives in this work: to validate the propagation model for different large frequencies, to highlight the problem of the close field with the DBS source and to show the influence of the proximity to the skull on the results. We compared the Stereo-EEG data, recorded during DBS, with those obtained using: (i) the simplest model, the dipolar model in an infinite homogeneous medium, (ii) a more realistic approach with a numerical method, the Boundary Element Method (BEM). Studies on ten subjects with 234 stimulations showed that the dipole model could be used in the brain far from the skull in direction of dipole moment but that BEM was more appropriate close to the skull.