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

Fingerprint

Time varying networks
Electroencephalography
Feature extraction
Graph theory
Brain

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

De Vico Fallani, F., Astolfi, L., Cincotti, F., Mattia, D., Tocci, A., Capitanio, S., ... Babiloni, F. (2007). Features extraction from time-varying cortical networks adopting a theoretical graph approach. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 5198-5201). [4353513] https://doi.org/10.1109/IEMBS.2007.4353513

Features extraction from time-varying cortical networks adopting a theoretical graph approach. / De Vico Fallani, F.; Astolfi, L.; Cincotti, F.; Mattia, D.; Tocci, A.; Capitanio, S.; Marciani, M. G.; Salinari, H.; Hesse, W.; Witte, H.; Gao, S.; Colosimo, A.; Babiloni, F.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. p. 5198-5201 4353513.

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

De Vico Fallani, F, Astolfi, L, Cincotti, F, Mattia, D, Tocci, A, Capitanio, S, Marciani, MG, Salinari, H, Hesse, W, Witte, H, Gao, S, Colosimo, A & Babiloni, F 2007, Features extraction from time-varying cortical networks adopting a theoretical graph approach. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings., 4353513, pp. 5198-5201, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 8/23/07. https://doi.org/10.1109/IEMBS.2007.4353513
De Vico Fallani F, Astolfi L, Cincotti F, Mattia D, Tocci A, Capitanio S et al. Features extraction from time-varying cortical networks adopting a theoretical graph approach. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. p. 5198-5201. 4353513 https://doi.org/10.1109/IEMBS.2007.4353513
De Vico Fallani, F. ; Astolfi, L. ; Cincotti, F. ; Mattia, D. ; Tocci, A. ; Capitanio, S. ; Marciani, M. G. ; Salinari, H. ; Hesse, W. ; Witte, H. ; Gao, S. ; Colosimo, A. ; Babiloni, F. / Features extraction from time-varying cortical networks adopting a theoretical graph approach. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. pp. 5198-5201
@inproceedings{7e5ba573476047c981e39fa693c84e59,
title = "Features extraction from time-varying cortical networks adopting a theoretical graph approach",
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.",
author = "{De Vico Fallani}, F. and L. Astolfi and F. Cincotti and D. Mattia and A. Tocci and S. Capitanio and Marciani, {M. G.} and H. Salinari and W. Hesse and H. Witte and S. Gao and A. Colosimo and F. Babiloni",
year = "2007",
doi = "10.1109/IEMBS.2007.4353513",
language = "English",
isbn = "1424407885",
pages = "5198--5201",
booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

}

TY - GEN

T1 - Features extraction from time-varying cortical networks adopting a theoretical graph approach

AU - De Vico Fallani, F.

AU - Astolfi, L.

AU - Cincotti, F.

AU - Mattia, D.

AU - Tocci, A.

AU - Capitanio, S.

AU - Marciani, M. G.

AU - Salinari, H.

AU - Hesse, W.

AU - Witte, H.

AU - Gao, S.

AU - Colosimo, A.

AU - Babiloni, F.

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=57649188613&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=57649188613&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2007.4353513

DO - 10.1109/IEMBS.2007.4353513

M3 - Conference contribution

AN - SCOPUS:57649188613

SN - 1424407885

SN - 9781424407880

SP - 5198

EP - 5201

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -