Jacobo Diego Sitt

This study uses neural field models to assess thalamocortical function in disorders of consciousness, finding reduced corticothalamic integrity in UWS compared to MCS.

This study investigates factors driving intersubject correlation (ISC) in EEG during auditory narratives, finding that acoustic features mainly drive ISC, while linguistic features like word surprisal contribute under active engagement.

This study shows that spontaneous slow waves in Disorders of Consciousness patients correlate with recovery potential and residual awareness, challenging the view of slow waves as merely a marker of impaired consciousness.

This study identifies hyper-hierarchical brain states in disorders of consciousness and links them to reduced behavioral responsiveness and altered network dynamics.

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

This study uses whole-brain modeling to show that structural brain hubs influence dynamical state transitions in disorders of consciousness.

This study shows that cognitive co-activation dominates fMRI synchrony in the awake brain but is replaced by anatomical and molecular constraints during consciousness perturbations.

This study uses large language models to annotate spontaneous thoughts from verbal reports and decodes their emotional valence from EEG data.

This study uses computational models to simulate psychedelic treatments for disorders of consciousness, finding they shift brains closer to criticality, with varying effects based on patient state.

This study investigates crossmodal prediction errors using EEG, finding sustained cortical responses and reconfigured networks compared to unimodal errors.

This paper identifies disrupted hierarchical organization in disorders of consciousness using fluctuation-dissipation theorem deviations from fMRI data.

This study analyzes EEG microstate dynamics in disorders of consciousness to identify differences in brain activity patterns between patients and healthy controls.

This study develops a personalized fMRI analysis pipeline for disorders of consciousness, identifying connectivity and local parameters as biomarkers for diagnosis and prognosis.

Inception simulates long-term recovery in Disorders of Consciousness using whole-brain models and fMRI data, showing improved patient classification and potential for capturing pharmacological effects.

The paper investigates how non-equilibrium dynamics in the brain relate to complexity in response to stimuli, finding reduced asymmetry and irreversibility in states of reduced consciousness.

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

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.

The paper shows that specific brain connectivity patterns during wakefulness enhance conscious processing of external stimuli, with mutual influence between brain dynamics and perception.

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 analyzes intracortical recordings to show exogenous attention emerges as cortical gradients, with neural activity reflecting visual attributes and response timing.

This study uses functional ultrasound imaging in awake mice to reveal brain state dynamics during cold perception, identifying new patterns of interregional connectivity and affective responses.

The paper shows that watching the same naturalistic movies leads to similar brain connectivity patterns across participants, with higher synchronization during engaging scenes.

This study investigates neural responses to interoceptive and exteroceptive attention using brain dynamics and HEP features, showing distinct patterns that can classify attentional states and assess command-following in brain-injured patients.

The paper uses intracerebral recordings and modeling to show how fronto-parietal networks mediate attention and consciousness in human perception.

This study shows Drosophila fruit flies spontaneously prefer larger numerical quantities and identifies a neuronal substrate for numerical cognition.

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 identifies distinct low-frequency EEG markers that differentiate intentional and unintentional mind-wandering during a sustained attention task.

The paper investigates how sensory target detection in the human cortex operates at local and global timescales, revealing a hierarchy of supramodal dynamics across different sensory modalities.

This paper introduces a framework using turbulent dynamics to differentiate brain states by analyzing neuroimaging data with model-free and model-based measures.

The paper investigates behavioral responses to verbal stimuli in sleep stages, finding reactivity in all stages except slow-wave sleep in healthy volunteers.