Ibai Palacio Diez

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.

This study uses resting-state functional connectivity to track network-level changes in brain tumour patients before and after surgery, finding persistent alterations and preoperative segregation predicting cognitive recovery.

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.

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

The paper identifies two subtypes of autism based on functional connectivity, linking hyperconnectivity to excitation-inhibition imbalance in 42% of patients.

This paper builds a whole-brain computational model to show that age-related changes in high-order functional interactions are explained by variations in the connectome.

This study examines how amyloid-β and tau pathologies affect brain functional connectivity in preclinical Alzheimer's disease carriers, finding distinct dysconnectivity patterns in specific brain regions.

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.

The paper analyzes structural and dynamical functional connectivity in cerebellar networks and finds lower variability in dynamical functional connectivity in the posterior cerebellum compared to other brain regions.

The paper identifies transcriptional signatures of synaptic vesicle genes associated with neurodegeneration in Myotonic Dystrophy Type I using transcriptome and brain imaging data.

This study uses O-Information to analyze how high-order statistical interdependencies in fMRI data change with age, finding increased redundancy in older adults across brain regions.

The paper was withdrawn due to methodological concerns that altered the main conclusion about gene-cholesterol cascades and brain connectivity in autistic patients.

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

This study uses non-motor features and genetic variants to cluster Lewy body diseases, identifying distinct patient groups with different clinical and cognitive profiles.

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

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.

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

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.