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Reconstruction and localization of auditory sources from intracerebral SEEG using independent component analysis

Authors :
Víctor J. López-Madrona
Samuel Medina Villalon
Jayabal Velmurugan
Aurore Semeux-Bernier
Elodie Garnier
Jean-Michel Badier
Daniele Schön
Christian-G. Bénar
Source :
NeuroImage, Vol 269, Iss , Pp 119905- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Stereo-electroencephalography (SEEG) is the surgical implantation of electrodes in the brain to better localize the epileptic network in pharmaco-resistant epileptic patients. This technique has exquisite spatial and temporal resolution. Still, the number and the position of the electrodes in the brain is limited and determined by the semiology and/or preliminary non-invasive examinations, leading to a large number of unexplored brain structures in each patient. Here, we propose a new approach to reconstruct the activity of non-sampled structures in SEEG, based on independent component analysis (ICA) and dipole source localization. We have tested this approach with an auditory stimulation dataset in ten patients. The activity directly recorded from the auditory cortex served as ground truth and was compared to the ICA applied on all non-auditory electrodes. Our results show that the activity from the auditory cortex can be reconstructed at the single trial level from contacts as far as ∼40 mm from the source. Importantly, this reconstructed activity is localized via dipole fitting in the proximity of the original source. In addition, we show that the size of the confidence interval of the dipole fitting is a good indicator of the reliability of the result, which depends on the geometry of the SEEG implantation. Overall, our approach allows reconstructing the activity of structures far from the electrode locations, partially overcoming the spatial sampling limitation of intracerebral recordings.

Details

Language :
English
ISSN :
10959572
Volume :
269
Issue :
119905-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.42b2c2089f40aebabcf2dcae62f12f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2023.119905