Although extensively studied for decades, attention system remains an interesting challenge in neuroscience field. The Attention Network Task (ANT) has been developed to provide a measure of the efficiency for the three attention components identified in the Posner’s theoretical model: alerting, orienting and executive control. Here we propose a study on 15 healthy subjects who performed the ANT. We combined advanced methods for connectivity estimation on electroencephalographic (EEG) signals and graph theory with the aim to identify neuro-physiological indices describing the most important features of the three networks correlated with behavioral performances. Our results provided a set of band-specific connectivity indices able to follow the behavioral task performances among subjects for each attention component as defined in the ANT paradigm. Extracted EEG-based indices could be employed in future clinical applications to support the behavioral assessment or to evaluate the influence of specific attention deficits on Brain Computer Interface (BCI) performance and/or the effects of BCI training in cognitive rehabilitation applications.

Electroencephalography (EEG)-Derived Markers to Measure Components of Attention Processing / Anzolin, Alessandra; Astolfi, Laura; Toppi, Jlenia; Riccio, Angela; Pichiorri, Floriana; Cincotti, Febo; Mattia, Donatella. - ELETTRONICO. - (2017), pp. 15-19. (Intervento presentato al convegno 7th Graz Brain-Computer Interface Conference 2017 From Vision to Reality tenutosi a Graz; Austria nel September 18-22, 2017) [10.3217/978-3-85125-533-1-04].

Electroencephalography (EEG)-Derived Markers to Measure Components of Attention Processing

Alessandra Anzolin
;
Laura Astolfi;Jlenia Toppi;Angela Riccio;Floriana Pichiorri;Febo Cincotti;Donatella Mattia
2017

Abstract

Although extensively studied for decades, attention system remains an interesting challenge in neuroscience field. The Attention Network Task (ANT) has been developed to provide a measure of the efficiency for the three attention components identified in the Posner’s theoretical model: alerting, orienting and executive control. Here we propose a study on 15 healthy subjects who performed the ANT. We combined advanced methods for connectivity estimation on electroencephalographic (EEG) signals and graph theory with the aim to identify neuro-physiological indices describing the most important features of the three networks correlated with behavioral performances. Our results provided a set of band-specific connectivity indices able to follow the behavioral task performances among subjects for each attention component as defined in the ANT paradigm. Extracted EEG-based indices could be employed in future clinical applications to support the behavioral assessment or to evaluate the influence of specific attention deficits on Brain Computer Interface (BCI) performance and/or the effects of BCI training in cognitive rehabilitation applications.
2017
7th Graz Brain-Computer Interface Conference 2017 From Vision to Reality
EEG-based; electroencephalographic; Brain Computer Interface (BCI)
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Electroencephalography (EEG)-Derived Markers to Measure Components of Attention Processing / Anzolin, Alessandra; Astolfi, Laura; Toppi, Jlenia; Riccio, Angela; Pichiorri, Floriana; Cincotti, Febo; Mattia, Donatella. - ELETTRONICO. - (2017), pp. 15-19. (Intervento presentato al convegno 7th Graz Brain-Computer Interface Conference 2017 From Vision to Reality tenutosi a Graz; Austria nel September 18-22, 2017) [10.3217/978-3-85125-533-1-04].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1019254
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