Maria Grazia Puxeddu

The paper analyzes the Drosophila connectome to reveal hierarchical community structures and identifies functional circuit archetypes.

The paper simulates sensory signal propagation in the Drosophila connectome to study modality-specific cascades and neuron classification based on dynamic response profiles.

This paper adapts network control theory to model spatially diffuse input signals in the human brain, showing reduced energy for state transitions and matching existing neurobiological maps.

This paper introduces a community detection algorithm for functional brain networks that accounts for higher-order interactions and identifies redundant modules, revealing new organizational patterns in the transmodal cortex.

The paper analyzes time-varying synergy and redundancy dominance in fMRI BOLD signals during rest, finding that whole-brain synergy is rare and that optimized subsets show recurrent functional systems.

The paper investigates how connectome architecture supports dual communication modes, showing that modular networks enable within-module diffusion and between-module routing across multiple organisms.

The paper analyzes a larval Drosophila connectome to identify hierarchical communities linked to cell type and function, revealing assortative and non-assortative interactions and rich-club structures.

This paper investigates the relationship between anatomical and functional modular organization of the human brain using a novel multi-layer framework across multiple subjects.