Rodrigo Cofré

This paper introduces a homeostatic inhibitory plasticity rule into a biophysical model to study how local adaptive processes influence global brain dynamics.

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

This study identifies four wave propagation motifs in the human brain across different states of consciousness and shows how they reconfigure in diminished and psychedelic states.

This study investigates how five psychedelic drugs affect local brain synchrony and global functional connectivity using fMRI, finding disrupted local synchrony and enhanced global connectivity across all drugs.

The paper presents a biophysically-based model simulating 5-HT2A receptor activation effects, showing increased spontaneous complexity and altered spectral power without significant change in perturbational complexity.

This study profiles neural dynamics across species during anaesthesia, finding conserved dynamical changes and linking them to molecular mechanisms.

This study benchmarks macaque brain gene expression for horizontal and vertical translation by comparing it to human gene expression and protein density.

This study identifies dynamic structure-function correlations as robust markers of consciousness in humans across different unconscious states.

This study shows that prefrontal cortex transcranial direct current stimulation alters brain dynamics in both awake and anesthetized non-human primates, affecting functional connectivity patterns and structure-function relationships.

The paper investigates how consciousness states affect brain structure-function organisation using anaesthesia and deep brain stimulation in non-human primates.

This paper develops a multivariate signal processing pipeline to build high-order brain networks from fMRI data and identifies high-order hubs associated with distinct brain systems.

This study uses empirical fMRI and computational modeling to show that nicotine increases functional segregation in the brain during attentional tasks but not at rest, linking network topology to behavior.

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.

The paper introduces FastDMF, a computationally efficient implementation of the Dynamic Mean Field model, enabling simulations of whole-brain dynamics with significantly faster performance and reduced memory usage.

The paper introduces an automated method for detecting neuronal ensembles in spiking neural networks, showing it accurately identifies ensembles in both real and synthetic 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 studies how cholinergic modulation of inhibitory interneurons affects functional integration in a whole-brain model using a human connectome.

This paper develops a mechanistic model explaining how 5HT2A-R activation increases neural entropy in the brain, showing non-uniform regional effects linked to anatomical connectivity.

This paper introduces a dimensionality reduction framework for spatio-temporal maximum entropy models of spiking networks, showing significant reduction in retinal data.