Gianluca Coppola1, Antonio Di Renzo1, Barbara Petolicchio1, Emanuele Tinelli1, Cherubino Di Lorenzo1, Vincenzo Parisi2, Mariano Serrao1, Valentina Calistri1, Stefano Tardioli1, Gaia Cartocci1, Jean Schoenen1, Francesca Caramia1, Vittorio Di Piero1, Francesco Pierelli1. 1. From the Department of Medico-Surgical Sciences and Biotechnologies (G. Coppola, M.S., F.P.), Sapienza University of Rome Polo Pontino, Latina; Research Unit of Neurophysiology of Vision and Neuroophthalmology (A.D.R., V.P.), IRCCS-Fondazione Bietti; Department of Human Neurosciences (B.P., E.T., V.C., S.T., G. Cartocci, F.C., V.D.P.), Sapienza University of Rome; Don Carlo Gnocchi Onlus Foundation (C.D.L.), Milan, Italy; Headache Research Unit, University Department of Neurology CHR (J.S.), Citadelle Hospital, University of Liège, Belgium; and IRCCS-Neuromed (F.P.), Pozzilli, Italy. 2. From the Department of Medico-Surgical Sciences and Biotechnologies (G. Coppola, M.S., F.P.), Sapienza University of Rome Polo Pontino, Latina; Research Unit of Neurophysiology of Vision and Neuroophthalmology (A.D.R., V.P.), IRCCS-Fondazione Bietti; Department of Human Neurosciences (B.P., E.T., V.C., S.T., G. Cartocci, F.C., V.D.P.), Sapienza University of Rome; Don Carlo Gnocchi Onlus Foundation (C.D.L.), Milan, Italy; Headache Research Unit, University Department of Neurology CHR (J.S.), Citadelle Hospital, University of Liège, Belgium; and IRCCS-Neuromed (F.P.), Pozzilli, Italy. vmp_g@outlook.it.
Abstract
OBJECTIVE: We investigated resting-state (RS)-fMRI using independent component analysis (ICA) to determine the functional connectivity (FC) between networks in chronic migraine (CM) patients and their correlation with clinical features. METHODS: Twenty CM patients without preventive therapy or acute medication overuse underwent 3T MRI scans and were compared to a group of 20 healthy controls (HC). We used MRI to collect RS data in 3 selected networks, identified using group ICA: the default mode network (DMN), the executive control network (ECN), and the dorsal attention system (DAS). RESULTS: Compared to HC, CM patients had significantly reduced functional connectivity between the DMN and the ECN. Moreover, in patients, the DAS showed significantly stronger FC with the DMN and weaker FC with the ECN. The higher the severity of headache, the increased the strength of DAS connectivity, and the lower the strength of ECN connectivity. CONCLUSION: These results provide evidence for large-scale reorganization of functional cortical networks in chronic migraine. They suggest that the severity of headache is associated with opposite connectivity patterns in frontal executive and dorsal attentional networks.
OBJECTIVE: We investigated resting-state (RS)-fMRI using independent component analysis (ICA) to determine the functional connectivity (FC) between networks in chronic migraine (CM) patients and their correlation with clinical features. METHODS: Twenty CMpatients without preventive therapy or acute medication overuse underwent 3T MRI scans and were compared to a group of 20 healthy controls (HC). We used MRI to collect RS data in 3 selected networks, identified using group ICA: the default mode network (DMN), the executive control network (ECN), and the dorsal attention system (DAS). RESULTS: Compared to HC, CMpatients had significantly reduced functional connectivity between the DMN and the ECN. Moreover, in patients, the DAS showed significantly stronger FC with the DMN and weaker FC with the ECN. The higher the severity of headache, the increased the strength of DAS connectivity, and the lower the strength of ECN connectivity. CONCLUSION: These results provide evidence for large-scale reorganization of functional cortical networks in chronic migraine. They suggest that the severity of headache is associated with opposite connectivity patterns in frontal executive and dorsal attentional networks.