Leonardo Dalla Porta

This study evaluates how neural complexity metrics relate to network architecture by simulating neural dynamics across diverse network structures and analyzing both observational and perturbational measures.

This paper models post-lesional slow waves in brain networks, identifying mechanisms for their generation and propagation.

The paper identifies criticality signatures in cortical networks during synchronization onset, showing both intra- and inter-hemispheric coordination patterns.

This paper develops a multiscale computational framework to study how brain criticality at local and global scales interacts through structural connectivity.

This study uses a whole-brain model to show that cholinergic heterogeneity enhances synchronization and information flow in brain dynamics.

This study shows that reducing h-current in cortical networks increases neuronal responsiveness and alters slow oscillation dynamics by extending both Up and Down states and reducing oscillation frequency.

The paper develops a mean-field formalism to predict the collective dynamics of large networks of complex spiking neurons, linking population models to electrophysiology.

The paper shows that the cerebral cortex operates near a critical phase transition in spiking variability, with critical exponents distinct from mean-field directed percolation.

The paper revisits the CROS model to show that exponents governing neuronal avalanches and long-range correlations vary continuously near a critical transition, matching experimental M/EEG variability.