The characterization of human neural activity during imaginary movement tasks represent an important challenge in order to develop er effective applications that allow the control of a machine. Yet methods based on brain network analysis of functional connectivity have been scarcely investigated. As a result we use graph theoretic methods to investigate the functional connectivity and brain network measures in order to characterize imagery hand movements in a set of healthy subjects. The results of the present study show that functional connectivity analysis and minimum spanning tree (MST) parameters allow to successfully discriminate between imagery hand movements (both right and left) and resting state conditions. In conclusion, this paper shows that brain network analysis of EEG functional connectivity could represent an efficient alternative to more classical local activation based approaches. Furthermore, it also suggests the shift toward methods based on the characterization of a limited set of fundamental functional connections that disclose salient network topological features.

Brain network analysis of EEG functional connectivity during imagery hand movements

DEMURU, MATTEO;FRASCHINI, MATTEO
2013-01-01

Abstract

The characterization of human neural activity during imaginary movement tasks represent an important challenge in order to develop er effective applications that allow the control of a machine. Yet methods based on brain network analysis of functional connectivity have been scarcely investigated. As a result we use graph theoretic methods to investigate the functional connectivity and brain network measures in order to characterize imagery hand movements in a set of healthy subjects. The results of the present study show that functional connectivity analysis and minimum spanning tree (MST) parameters allow to successfully discriminate between imagery hand movements (both right and left) and resting state conditions. In conclusion, this paper shows that brain network analysis of EEG functional connectivity could represent an efficient alternative to more classical local activation based approaches. Furthermore, it also suggests the shift toward methods based on the characterization of a limited set of fundamental functional connections that disclose salient network topological features.
2013
Imagery movements; functional connectivity; brain networks; minimum spanning tree; EEG; beta band
File in questo prodotto:
File Dimensione Formato  
S021963521350026X.pdf

Solo gestori archivio

Tipologia: versione editoriale
Dimensione 254.95 kB
Formato Adobe PDF
254.95 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/105488
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 34
  • ???jsp.display-item.citation.isi??? 33
social impact