Sebastiano Stramaglia

Bridging Higher-Order Information Theory and Neuroimaging: A Voxel-Wise O-Information Framework

This paper introduces a voxel-wise O-information framework to analyze high-order functional interactions in neuroimaging data, revealing age-related changes in default mode network redundancy.

Brain structural modules associated to functional high-order interactions in the human brain

This study investigates the coupling between structural connectivity and high-order functional interactions in the human brain, finding that structural networks are associated with both redundant and synergistic functional interactions.

Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain

The paper provides open datasets and code to study multi-scale relationships between structural, functional, and neuro-genetic aspects of the human brain.

The structure of anticorrelated networks in the human brain

The paper analyzes anticorrelated networks in the human brain using neuroimaging data, finding increased cerebellar anticorrelation in older adults.

Linking hubness, embryonic neurogenesis, transcriptomics and diseases in human brain networks

The paper links hubness in brain networks to embryonic neurogenesis, showing that earlier-born nodes become stronger hubs and are associated with genes related to neurological diseases.

Hyperconnectivity of the default mode network in multiorgan dysfunction syndrome

This study identifies hyperconnectivity of the default mode network in MODS patients without apparent brain damage, suggesting functional brain network alterations post-ICU discharge.

Connectome preprocessing by Consensus Clustering increases separability in group neuroimaging studies

The paper proposes using consensus clustering on brain connectivity matrices to improve subgroup separation in neuroimaging studies by reducing intra-group variability.

Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data

The paper uses machine learning to compare brain network configurations in task-based and resting-state fMRI data, finding that task-related areas show consistent connectivity patterns while others differ.

Interaction information along lifespan of the resting brain dynamics reveals a major redundant role of the default mode network

The paper calculates interaction information from fMRI data to examine redundancy and synergy in brain networks across lifespan, finding high redundancy in the default mode network and balanced redundancy-synergy patterns.

What the structural-functional connectome reveals about brain aging: The key role of the fronto-striatal-thalamic circuit and the rejuvenating impact of physical activity

The paper estimates brain-connectome age using structural and functional connectivity data and finds physical activity reduces this estimated age.

Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease

The paper uses diffusion-tensor brain networks from ADNI data to compare connectivity patterns across Alzheimer’s disease severity stages, finding progressive disconnections in memory-related and other brain networks.

Visibility graphs for fMRI data: multiplex temporal graphs and their modulations across resting state networks

This paper applies visibility graphs to fMRI data to analyze collective dynamics across resting state networks.