Intracranial voltage profiles from untangled human deep sources reveal multisource composition and source allocation bias.

Abstract

Intracranial potentials are used as functional biomarkers of neural networks. As potentials spread away from the source populations, they become mixed in the recordings. In humans, interindividual differences in the gyral architecture of the cortex pose an additional challenge, as functional areas vary in location and extent. We used source separation techniques to disentangle mixing potentials obtained by exploratory deep arrays implanted in epileptic patients of either sex to gain access to the number, location, relative contribution and dynamics of co-active sources. The unique spatial profiles of separated generators made it possible to discern dozens of independent cortical areas for each patient, whose stability maintained even during seizure, enabling the follow up of activity for days and across states. Through matching these profiles to MRI, we associated each with limited portions of sulci and gyri, and determined the local or remote origin of the corresponding sources. We also plotted source-specific 3D coverage across arrays. In average, individual recording sites are contributed to by 3-5 local and distant generators from areas up to several centimeters apart. During seizure, 13-85 % of generators were involved, and a few appeared anew. Significant bias in location assignment using raw potentials is revealed, including numerous false positives when determining the site of origin of a seizure. This is not amended by bipolar montage, which introduce additional errors of its own. In this way, source disentangling reveals the multisource nature and far intracranial spread of potentials in humans, while efficiently addressing patient-specific anatomofunctional cortical divergence.Significance Statement Field potentials are used to better localize zones showing normal and pathological activity. However, as potentials spread throughout the brain volume, they mix with others and make their place of origin uncertain, even when recorded intracranially. We used advanced algorithms to disentangle the activity of each these zones by their unique spatial profiles, which allowed us to determine the 3D outline of normal and epileptic areas and follow their activity for days. Dozens of independent sources per patient can be explored and precisely located. The findings show that standard stereoEEG recordings are contributed by 3-5 populations, which after separation will help to plan clinical intervention to break epileptic networks by more accurately marking epileptic foci and avoiding false positives.