Antonio Jiménez-Marín

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 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.

This study uses partial correlation on fMRI data to better align functional connectivity with structural connectivity, showing improved matches with regularization and thresholding.

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 extends lesion network mapping to a multimodal approach using functional and structural connectivity maps to predict sensorimotor behavior in stroke patients.

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

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.

The paper was withdrawn due to methodological concerns that altered the main conclusion about gene-cholesterol cascades and brain connectivity in autistic patients.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

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.