Optimizing model complexity of whole-brain models and digital twins for neurological applications

Whole-brain neural mass models can effectively simulate neural activity, however the elevated model complexity of some implementations might hinder their translation to clinical practice, e.g. for digital twin applications. In this talk we will talk about different strategies to choose the optimal level of complexity and critically evaluate potential added benefit of more sophisticated heterogeneous models. These results might facilitate the translation of models to clinical applications with minimally required model complexity, while maintaining the same accuracy for predictions.

Contatto:
paola.antonietti@polimi.it