Zengxin Qi

This study investigates whether statistical learning occurs in patients with impaired consciousness by analyzing their ability to extract regularities from an artificial language using EEG frequency tagging.

The paper identifies cortical hubs associated with consciousness recovery in UWS patients and finds the anterior precuneus is a key region.

The paper identifies higher-order sensorimotor brain hubs that correlate with consciousness levels across different unconscious states using resting-state fMRI data.

The paper investigates intrinsic neural timescales in different behavioural states and finds that sensory deficits are associated with prolonged neural timescales, while motor deficits do not show such changes.

This study evaluates whether R-fMRI indices can differentiate brain tumors from normal tissue and finds that ALFF and VMHC, with Z-standardization, are effective in this task.