A fine-grained time course investigation of brain dynamics during conflict monitoring

Détails

ID Serval
serval:BIB_8D39CD4483F6
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
A fine-grained time course investigation of brain dynamics during conflict monitoring
Périodique
Scientific Reports
Auteur(s)
Ruggeri Paolo, Meziane Hadj Boumediene, Koenig Thomas, Brandner Catherine
ISSN
2045-2322
Statut éditorial
Publié
Date de publication
12/2019
Volume
9
Numéro
1
Langue
anglais
Résumé
The conflict monitoring model predicting higher anterior cingulate cortex (ACC) neuronal activity on incongruent trials has been recently challenged by a model predicting longer neuronal activity in incongruent trials characterized by longer RTs. To clarify this issue, brain dynamics were explored through event-related-potential (ERP) recordings during a Stroop task. We assessed differences between experimental conditions by combining complementary methods sensitive to the temporality of events including microstate, TANOVA and source localization analysis. The analysis demonstrated the same electrical dynamics only differed in duration towards the end of information processing in the incongruent condition. Specifically, the activation strength of the ACC region did not differ significantly between congruent and incongruent conditions but lasted longer in the incongruent condition. Taken together, our results support the model predicting longer neuronal activity in incongruent trials characterized by longer RTs. They highlight that brain dynamics can dramatically change through periods of interest and that caution is required when interpreting fMRI results. To conclude, these results indicate how time-sensitive measures can contribute to a better understanding of the mechanisms underlying information processing, and thus offer new venues to explore conflict monitoring
Mots-clé
Multidisciplinary
Pubmed
Création de la notice
15/03/2019 17:28
Dernière modification de la notice
03/04/2019 6:12
Données d'usage