Maria Luisa Saggio

This study uses computational modeling to show that seizure spread depends on the dynamotype, with specific patterns of brain activity at onset affecting recruitment likelihood and speed.

This paper investigates the unfolding of the Doubly Degenerate Bogdanov-Takens bifurcation using spherical and planar surfaces, revealing new bifurcation topologies and transitions relevant to neural dynamics.

This paper introduces a modular neural mass model incorporating neuromodulation, specifically dopamine dynamics, and analyzes its effects on oscillatory states.

This paper introduces Virtual Brain Twins (VBTs) as personalized digital brain models that integrate structural and functional data to improve understanding of brain function and support personalized treatment.

The paper analyzes the Epileptor model using bifurcation theory to understand how parameter changes can produce different seizure types and how an additional mechanism affects its dynamics.

This paper develops a mean-field model of neuronal populations incorporating ion-exchange mechanisms to simulate brain activity and validate its effects through in vitro experiments.

This paper introduces a taxonomy of seizure dynamotypes based on bifurcation theory and applies it to EEG data, identifying 16 dynamotypes and their variations across patients.