Prestimulus interhemispheric coupling of brain rhythms predicts cognitive-motor performance in healthy humans

Giordano Lacidogna, Paolo Maria Rossini, Fabrizio Vecchio, Francesca Miraglia, Placido Bramanti, Florinda Ferreri

Risultato della ricerca: Contributo in rivistaArticolo in rivista

20 Citazioni (Scopus)

Abstract

Physiological and neuroimaging studies suggest that human actions are characterized by time-varying engagement of functional distributed networks within the brain. In this study, we investigated whether specific prestimulus interhemispheric connectivity, as a measure of synchronized network between the two hemispheres, could lead to a better performance (as revealed by RT) in a simple visuomotor task. Eighteen healthy adults underwent EEG recording during a visual go/no-go task. In the go/no-go task, a central fixation stimulus was followed by a green (50% of probability) or red visual stimulus. Participants had to press the mouse button after the green stimuli (go trials). Interhemispheric coupling was evaluated by the spectral coherence among all the electrodes covering one hemisphere and matched with those on the other. The frequency bands of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). The task-related results showed that interhemispheric connectivity decreased in delta and increased in alpha band. Furthermore, we observed positive delta and negative alpha correlations with the RT; namely, the faster the RT, the lower delta and the higher alpha connection between the two hemispheres. These results suggested that the best performance is anticipated by the better functional coupling of cortical circuits involved during the processing of the sensorimotor information, occurring between the two hemispheres pending cognitive go/no-go task.
Lingua originaleEnglish
pagine (da-a)1883-1890
Numero di pagine8
RivistaJournal of Cognitive Neuroscience
Volume26
DOI
Stato di pubblicazionePubblicato - 2014

Keywords

  • Physiological
  • neuroimaging

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