Advances over the past two decades in functional neuroimaging have provided new
diagnostic and prognostic tools for patients with severe brain injury. Some of the most …

Artificial intelligence and machine learning can assist in clinical decision-making, including
the diagnosis, prognosis, and therapy for patients with disorders of consciousness. The …

Background To investigate patients with disorders of consciousness (DoC) for residual
awareness, guidelines recommend quantifying glucose brain metabolism using positron …

Importance Among the most impactful neurologic assessments is that of
neuroprognostication, defined here as the prediction of neurologic recovery from disorders …

Objective. Combining magnetic resonance imaging (MRI) and electroencephalography
(EEG) provides a powerful tool for investigating brain function at varying spatial and …

Aims There is limited research on predicting the recovery of consciousness in patients with
acute disorders of consciousness (aDOC). The purpose of this study is to investigate the …

Background Identifying covert consciousness in intensive care unit (ICU) patients with coma
and other disorders of consciousness (DoC) is crucial for treatment decisions, but sensitive …

Cognitive motor dissociation (CMD) is characterized by a dissociation between volitional
brain responses and motor control, detectable only through techniques such as …

Background In intensive care patients with disorders of consciousness, the pupillary light
reflex is a measure of pupillary parasympathetic function. By contrast, the pupillary light-off …

Background Identifying patients likely to regain consciousness early on is a challenge. The
assessment of consciousness levels and the prediction of wakefulness probabilities are …