Cognitive Neuroscience


Alzheimer’s & dementia




Formal publication: March 2024

Authors: Coronel-Oliveros, C., Gómez, R. G., Ranasinghe, K., Sainz-Ballesteros, A., Legaz, A., Fittipaldi, S., Cruzat, J., Herzog, R., Yener, G., Parra, M., Aguillon, D., Lopera, F., Santamaria-Garcia, H., Moguilner, S., Medel, V., Orio, P., Whelan, R., Tagliazucchi, E., Prado, P., & Ibañez, A

Abstract: Introduction: Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost-effective technique for studying dementia globally, but lacks mechanistic models and produces non-replicable results.

Methods: We developed a generative whole-brain model that combines EEG source-level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls).

Results: Metaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings.

Discussion: The results provide a novel agenda for developing mechanistic model-inspired characterization and therapies in clinical, translational, and computational neuroscience settings.