Epileptogenic zone classification with functional connectivity and graph measures

Author(s)

Carlos, Bruna M. ; Campos, Brunno M. ; Alvim, Marina K. M. ; Patino, Manuel G. ; Cendes, Fernando ; Castellano, Gabriela ; IEEE

• Document type: Journal article
• Source: 2023 11TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING, NER; v. N/A, p. 4-pg., 2023-01-01.

Abstract

Epilepsy is one of the most common neurological diseases, and it has a great variety of possible diagnosis that can involve different treatments. The characterization of epileptogenic zones (EZs) is of extreme importance for the evaluation of patients, specially for pharmacoresistant epilepsy patients that are candidates for surgery. Many works have been showing that epilepsy interferes with brain network organization, in particular during seizures or epileptic discharges, although there is also indication that there are significant alterations during interictal periods. With most studies using intracranial electroencephalography (EEG), there are few results about the alterations present in regular EEG examinations that could be used to indicate the general location of the EZ in advance. This prior indication could be beneficial for a better understanding of network changes across the whole scalp. The aim of this work was to extract relevant information from patients with different EZs, using functional connectivity and graph measures from normal background EEG signals. Patients with EZs in the temporal and frontal lobe were included in this study. Our results reinforce that centrality graph measures from many areas of the scalp are useful in the distinction between patients with different EZs. We also found that connectivity in the alpha band can be used for EZ classification and might be of interest in future studies. (AU)

• FAPESP's process: 20/16571-0 - Investigation of brain changes in neurological patients undergoing different rehabilitation treatments
• Grantee: Bruna Mezzari Carlos
• Support Opportunities: Scholarships in Brazil - Doctorate