Marilyn Gatica

The paper evaluates higher-order interaction metrics in brain connectivity using fMRI data, finding topological metrics link brain function to behavior better than pairwise models.

The paper uses multivariate information theory to analyze brain states and finds that higher-order interactions distinguish wakefulness, anaesthesia, and recovery.

This paper introduces a modified neural mass model with inhibitory synaptic plasticity to better simulate EEG and fMRI recordings during NREM sleep and capture the spectral richness of brain activity.

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 paper develops a whole-brain model to study how transcranial ultrasound stimulation (TUS) induces functional changes in the brain, identifying two mechanisms that predict plasticity-driven effects.

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 examines how transcranial ultrasound stimulation affects neural networks in macaques, showing changes in specific brain networks and network topology.

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 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.