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Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias

INTRODUCTION: Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic tran...

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Detalles Bibliográficos
Autores principales: Monteverdi, Anita, Palesi, Fulvia, Schirner, Michael, Argentino, Francesca, Merante, Mariateresa, Redolfi, Alberto, Conca, Francesca, Mazzocchi, Laura, Cappa, Stefano F., Cotta Ramusino, Matteo, Costa, Alfredo, Pichiecchio, Anna, Farina, Lisa M., Jirsa, Viktor, Ritter, Petra, Gandini Wheeler-Kingshott, Claudia A. M., D’Angelo, Egidio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419271/
https://www.ncbi.nlm.nih.gov/pubmed/37577354
http://dx.doi.org/10.3389/fnagi.2023.1204134
Descripción
Sumario:INTRODUCTION: Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission. METHODS: We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer’s disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel in vivo pathological hallmarks. RESULTS: The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles. DISCUSSION: These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.