Features extraction from time-varying cortical networks adopting a theoretical graph approach

F. De Vico Fallani, L. Astolfi, F. Cincotti, D. Mattia, A. Tocci, S. Capitanio, M. G. Marciani, H. Salinari, W. Hesse, H. Witte, S. Gao, A. Colosimo, F. Babiloni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, a novel approach is proposed in order to capture relevant features related to the structure and organization of the functional brain networks estimated in the time-frequency domain. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high resolution EEG techniques. Then, on the cortical signals from different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive Partial Directed Coherence. Such time-varying connectivity estimation returns a series of causality patterns evolving during the examined task which can be summarized and interpreted with the aid of mathematical indexes based on the graph theory. The combination of all these methods is demonstrated on a set of high resolution EEG data recorded from a healthy subject performing a simple foot movement.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages5198-5201
Number of pages4
DOIs
Publication statusPublished - 2007
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: Aug 23 2007Aug 26 2007

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
CountryFrance
CityLyon
Period8/23/078/26/07

ASJC Scopus subject areas

  • Biomedical Engineering

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