The Attention Network Task (ANT) was developed to disentangle the three components of attention identified in the Posner's theoretical model (alerting, orienting and executive control) and to measure the corresponding behavioral efficiency. Several fMRI studies have already provided evidences on the anatomical separability and interdependency of these three networks, and EEG studies have also unveiled the associated brain rhythms. What is still missing is a characterization of the brain circuits subtending the attentional components in terms of directed relationships between the brain areas and their frequency content. Here, we want to exploit the high temporal resolution of the EEG, improving its spatial resolution by means of advanced source localization methods, and to integrate the resulting information by a directed connectivity analysis. The results showed in the present study demonstrate the possibility to associate a specific directed brain circuit to each attention component and to identify synthetic indices able to selectively describe their neurophysiological, spatial and spectral properties.

Brain connectivity networks at the basis of human attention components: An EEG study / Anzolin, A.; Mattia, D.; Toppi, J.; Pichiorri, F.; Riccio, A.; Astolfi, L.. - ELETTRONICO. - (2017), pp. 3953-3956. (Intervento presentato al convegno 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 tenutosi a Island; South Korea nel 2017) [10.1109/EMBC.2017.8037721].

Brain connectivity networks at the basis of human attention components: An EEG study

Anzolin, A.
;
Mattia, D.;Toppi, J.;Pichiorri, F.;Riccio, A.;Astolfi, L.
2017

Abstract

The Attention Network Task (ANT) was developed to disentangle the three components of attention identified in the Posner's theoretical model (alerting, orienting and executive control) and to measure the corresponding behavioral efficiency. Several fMRI studies have already provided evidences on the anatomical separability and interdependency of these three networks, and EEG studies have also unveiled the associated brain rhythms. What is still missing is a characterization of the brain circuits subtending the attentional components in terms of directed relationships between the brain areas and their frequency content. Here, we want to exploit the high temporal resolution of the EEG, improving its spatial resolution by means of advanced source localization methods, and to integrate the resulting information by a directed connectivity analysis. The results showed in the present study demonstrate the possibility to associate a specific directed brain circuit to each attention component and to identify synthetic indices able to selectively describe their neurophysiological, spatial and spectral properties.
2017
39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Signal Processing; Biomedical Engineering; 1707; Health Informatics
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Brain connectivity networks at the basis of human attention components: An EEG study / Anzolin, A.; Mattia, D.; Toppi, J.; Pichiorri, F.; Riccio, A.; Astolfi, L.. - ELETTRONICO. - (2017), pp. 3953-3956. (Intervento presentato al convegno 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 tenutosi a Island; South Korea nel 2017) [10.1109/EMBC.2017.8037721].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1019005
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