Meet the expert of eBRAIN-Health

Prof. Deco’s team at Universitat Pompeu Fabra (UPF) is developing and applying whole-brain models for various neurological conditions. This includes the application of physics-based models to understand brain hierarchy, combining them with in silico perturbations, and using them to determine the effects of Amyloid-Beta and Tau in Alzheimer's disease. His team is primarily involved in the Work Packages focused on modelling and clinical application. In the long term, their models are expected to serve as digital twins for forecasting disease trajectories and testing therapeutic strategies in silico.

Prof. Deco’s team has achieved significant progress in advancing whole-brain computational modeling. Key findings include the identification of generative mechanisms underlying changes in brain activity, such as the development of a new thermodynamic model to understand the balance of causal interactions across different brain states. In addition, they have used whole-brain models combined with artificial perturbations to identify the most sensitive areas for stimulation, which is particularly relevant for patients with neurological conditions. Furthermore, their work has provided models that successfully describe the differential effects of Amyloid-Beta and Tau on the excitation-inhibition balance in Alzheimer’s disease. They are currently implementing personalised whole-brain models to obtain sensitive and specific neuroimaging biomarkers for Alzheimer's disease stratification based on the brain’s susceptibility to in silico perturbations.

One of the main challenges in computational neuroscience is integrating high-quality clinical and biophysical data to validate computational models. Furthermore, the computational optimization of whole-brain models for large-scale applications on platforms such as eBRAINS always poses challenges. Prof. Deco’s team overcame these hurdles through close and sustained collaboration with the clinical and technical partners within eBRAIN-Health, ensuring that the models are both biologically plausible and computationally efficient.

By developing and validating advanced computational models for various pathologies, the team provides translational simulation approaches that other researchers and clinicians can utilize. By publishing their code on eBRAINS, they are not only sharing their results but also making available the building blocks for future modeling studies, thereby strengthening the platform's capacity to advance brain healthcare in Europe.