Benjamin Rohaut

The paper investigates whether traveling waves in attention networks reflect top-down attention signals or are a byproduct of sustained attention, finding they align with the intrinsic rhythms of engaged sensory systems.

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

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 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.

This study shows that tDCS applied to the prefrontal cortex improves behavior and EEG markers of consciousness in some DoC patients.

The paper uses MRI and machine learning to predict consciousness recovery and functional outcomes after haemorrhagic stroke by analyzing deep brain lesions.

The paper introduces a new behavioral tool called 'DoC-feeling' that uses aggregated nursing staff assessments to detect the Minimally Conscious State with high accuracy.