Pre-seizure architecture of the local connections of the epileptic focus examined via graph-theory

Fabrizio Vecchio, Francesca Miraglia, Catello Vollono, Filomena Fuggetta, Placido Bramanti, Beatrice Cioni, Paolo Maria Rossini

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Objective Epilepsy is characterized by unpredictable and sudden paroxysmal neuronal firing occurrences and sometimes evolving in clinically evident seizure. To predict seizure event, small-world characteristic in nine minutes before seizure, divided in three 3-min periods (T0, T1, T2) were investigated. Methods Intracerebral recordings were obtained from 10 patients with drug resistant focal epilepsy examined by means of stereotactically implanted electrodes; analysis was focused in a period of low spiking (Baseline) and during two seizures. Networks’ architecture is undirected and weighted. Electrodes’ contacts close to epileptic focus are the vertices, edges are weighted by mscohere (=magnitude squared coherence). Results Differences were observed between Baseline and T1 and between Baseline and T2 in theta band; and between Baseline and T1, Baseline and T2, and near-significant difference between T0 and T2 in Alpha 2 band. Moreover, an intra-band index was computed for small worldness as difference between Theta and Alpha 2. It was found a growing index trend from Baseline to T2. Conclusions Cortical network features a specific pre-seizure architecture which could predict the incoming epileptic seizure. Significance Through this study future researches could investigate brain connectivity modifications approximating a clinical seizure also in order to address a preventive therapy.
Original languageEnglish
Pages (from-to)3252-3258
Number of pages7
JournalClinical Neurophysiology
Volume127
DOIs
Publication statusPublished - 2016

Keywords

  • Epilepsy
  • Functional connectivity
  • Graph theory
  • Neurology
  • Neurology (clinical)
  • Physiology (medical)
  • Seizure
  • Sensory Systems
  • Small-world
  • eLORETA
  • sEEG

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