Gustavo Deco

This study shows LSD reduces directed information hierarchy in the brain by balancing signal sending and receiving, as measured by MEG data.

This paper investigates the long-term effects of psilocybin on fronto-striatal-thalamic circuit dynamics and connectivity using longitudinal fMRI data and computational modeling.

This study uses computational whole-brain modeling to show that competitive interactions in mammalian connectomes enhance computational capacity and fit brain dynamics better than cooperative-only models.

The paper uses whole-brain models to simulate the effects of serotonergic psychedelics on disorders of consciousness, showing they can shift brain dynamics toward conscious states.

This study uses off-equilibrium fluctuation-dissipation theorem to analyze brain dynamics in Alzheimer's disease, finding increased deviations in MCI and decreased deviations in AD, suggesting potential biomarkers for early detection.

This study compares power and connectivity-based sEEG biomarkers for identifying seizure-onset zones in temporal lobe epilepsy, finding that power-based methods generally perform better but both can achieve similar results with optimal parameter tuning.

This study shows that DMT alters connectome harmonics, increasing their repertoire entropy and correlating with subjective experience intensity over time.

This study examines how thalamocortical interactions shape neural variability during stimulus perception in monkeys, revealing distinct dynamics across brain regions.

This paper uses computational models to simulate brain perturbations in disorders of consciousness, showing that transitions to healthy brain states can be achieved through targeted stimulation.

The paper shows that combining rare long-range connections with local connectivity improves the capture of functional brain dynamics compared to geometry alone.

This study examines how brain network dynamics change across menstrual cycle phases and how age and progesterone levels influence these changes in healthy women.

This study uses intrinsic ignition analysis on rs-fMRI data to show reduced dynamical complexity and node-metastability in Alzheimer's disease, linked to Amyloid-β and tau pathology.

This study examines how the pace of pubertal maturation affects brain organization by linking skeletal age stages to resting-state EEG entropy production.

This study examines dynamic functional connectivity in neonatal brains using fMRI and links it to neurodevelopmental outcomes in early childhood.

This paper models the transient brain state changes induced by DMT using a time-dependent whole-brain model and fMRI data, showing heightened reactivity in specific brain regions correlated with serotonin receptor density.

The paper measures brain irreversibility in ferrets during different behavioral states to reveal functional hierarchies in cortical dynamics.

The paper uses generative whole-brain models trained on healthy data to predict functional connectivity changes in stroke patients by incorporating lesion-induced structural disconnections.

The paper identifies brain regions and networks predictive of response to psilocybin therapy for treatment-resistant depression using whole-brain modeling and dynamic sensitivity analysis.

This paper uses causal mechanistic modeling to show that meditation can be induced by artificial perturbations in specific brain networks, revealing distinct whole-brain dynamics during meditation compared to rest.

This study models the differential effects of Amyloid-Beta and Tau on neuronal activity in Alzheimer's Disease, finding A{beta} dominance in early stages and Tau dominance in later stages.

This study examines how mindfulness meditation affects brain dynamics by analyzing changes in harmonic complexity, revealing both immediate and long-term effects on brain state and trait characteristics.

This paper uses a turbulent dynamics framework to analyze whole-brain fMRI data from TBI patients and healthy controls, showing reduced synchronization and reactivity during recovery.

HADES framework analyzes spacetime activity patterns in the brain, showing reduced low-frequency harmonic modes during DMT-induced states, indicating changes in functional hierarchy.

This paper reveals the structural connectivity architecture of the human brain, showing that subcortical regions are central hubs critical for global signal propagation.

The paper compares two models for simulating brain activity across modalities, showing they can replicate functional connectivity and dynamics but with varying performance across modalities.

The paper estimates the whole-cortex excitation-inhibition ratio using fMRI and shows it declines during youth, with lower ratios linked to better cognitive performance in children.

The paper maps brain states of reduced consciousness into a low-dimensional space using whole-brain modeling and deep learning, revealing an orderly trajectory from wakefulness to brain injury.

The paper shows inhibitory neurons are essential for forming and maintaining modular neural structures after learning through synaptic adaptation.

The paper uses computational modeling to identify key brain regions for personalized neurostimulation strategies to improve cognitive interventions in Alzheimer's disease.

This paper shows complex spatiotemporal brain dynamics emerge from transverse instabilities in large-scale neural models.