Obiettivo While reading this text, pat your head and rub your stomach (if someone sees you, tell them it's OK; you're doing science). Right now you are engaging in an action that must be actively monitored and quickly adjusted to avoid making mistakes. Over the past five years, my collaborators and I discovered that there is a specific pattern of brain electrical activity that occurs during response conflict—competition between multiple conflicting actions when a mistake could be made. This brain activity is observed over the midfrontal cortex (MFC) and is characterized by oscillations at around 6 cycles per second (the theta band). MFC theta is a highly statistically robust marker of the neural networks involved in action monitoring and behavior adjustments, correlates with single-trial reaction time, and predicts how well people learn from mistakes. Despite these robust findings linking MFC theta to action monitoring, the significance of MFC theta for how neural microcircuits actually implement action monitoring and adjustments is unknown. In the ERC research we will use computer simulations and rodent models to understand how different types of neurons in different cortical layers might use action potentials and oscillations to implement action monitoring. The results will help us understand how the brain monitors behavior and avoids mistakes, and will also give insight into neural microcircuit organization as it relates to higher cognitive function. While developing these computer simulations and rodent models, we will also take our human research to the next level by asking: If action monitoring in the MFC is supported by theta oscillations, does this mean that our actions, and our ability to monitor and adjust them, occur with theta rhythmicity? To answer this question, we will develop new tasks combining data-gloves and EEG to test how the timing of human sequenced actions during keyboard typing (typists type in “theta”) corresponds to temporal dynamics of MFC theta. Campo scientifico natural sciencesbiological sciencesneurobiologycognitive neurosciencenatural sciencescomputer and information sciencesdata sciencedata processingnatural sciencesmathematicsapplied mathematicsmathematical modelnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programma(i) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Argomento(i) ERC-StG-2014 - ERC Starting Grant Invito a presentare proposte ERC-2014-STG Vedi altri progetti per questo bando Meccanismo di finanziamento ERC-STG - Starting Grant Istituzione ospitante STICHTING RADBOUD UNIVERSITEIT Contribution nette de l'UE € 1 500 000,00 Indirizzo HOUTLAAN 4 6525 XZ Nijmegen Paesi Bassi Mostra sulla mappa Regione Oost-Nederland Gelderland Arnhem/Nijmegen Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 1 500 000,00 Beneficiari (1) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto STICHTING RADBOUD UNIVERSITEIT Paesi Bassi Contribution nette de l'UE € 1 500 000,00 Indirizzo HOUTLAAN 4 6525 XZ Nijmegen Mostra sulla mappa Regione Oost-Nederland Gelderland Arnhem/Nijmegen Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 1 500 000,00