Fabio Pasqualetti

Using network control theory to study the dynamics of the structural connectome

This paper introduces a framework for applying network control theory to the human structural connectome to study neural dynamics and control energy, controllability, and their correlations with behavior and mental health.

Pathological and metabolic underpinnings of energetic inefficiency in temporal lobe epilepsy

This study uses network control theory to analyze energy dynamics in temporal lobe epilepsy, finding increased control energy requirements and metabolic asymmetry in affected brain regions.

Brain network dynamics fingerprints are resilient to data heterogeneity

The paper investigates how scanning factors affect brain network dynamics in multi-site fMRI data and identifies factors that influence variability in subject-specific dynamical patterns.

Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth

The paper uses network control theory to show that structural brain networks mature during adolescence to reduce the energy cost of activating the frontoparietal system, supporting executive function development.

Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia

The paper shows working memory involves brain-wide state switching, with dopamine D1/D2 receptor expression affecting stability and state transitions, and schizophrenia linked to altered network control properties.

White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions

This paper uses network control theory to model how white matter tracts guide electrical stimulation in the brain, showing that real white matter structures better predict state transitions than artificial models.