Uncovering the Secrets of Neurodegenerative Dementias Using Virtual Brain Simulations

Published on July 28, 2023

Imagine if we could use virtual reality to reveal the hidden mysteries of the brain! Well, scientists have done just that with neurodegenerative dementias. By creating virtual brain simulations, they were able to uncover specific parameters in Alzheimer’s disease and frontotemporal dementia that were previously unknown. These simulations allowed them to compare the brain networks of patients with these diseases to healthy individuals, providing insights into the unique alterations caused by each condition. Interestingly, each patient also showed their own individual patterns of network parameters, which correlated with their cognitive abilities, clinical features, and medications. This personalized approach could potentially lead to more tailored therapeutic strategies for treating dementias.

To learn more about this groundbreaking research and delve into the fascinating world of virtual brain simulations, check out the full article!

IntroductionNeural 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.MethodsWe 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.ResultsThe 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.DiscussionThese TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

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