For professionals

Abstract

For some patients, coma is followed by a state of unresponsiveness, while other patients develop signs of consciousness. In practice, detecting signs of consciousness can be hampered by possible impairments in the patient's motor, sensory, or cognitive abilities, resulting in a significant proportion of misdiagnosed disorders of consciousness. Task-free paradigms that are independent of the patient's sensorimotor and neurocognitive abilities can provide a solution to this challenge.

A limitation of previous research is that the vast majority of studies on the pathophysiological processes underlying disorders of consciousness have been conducted using cross-sectional designs. Here we present a study in which we obtained a total of 74 longitudinal task-free EEG measurements from 16 patients (aged 6-22 years, 12 men) suffering from severe acquired brain injury, and an additional 16 control participants based on age and education. We examined changes in amplitude and connectivity metrics of oscillating brain activity in patients during their recovery. In addition, we applied multi-class linear discriminant analysis to assess the potential diagnostic and prognostic utility of amplitude and connectivity metrics at the individual patient level.

We found that patients showed nonlinear frequency band-specific changes in spectral amplitude and connectivity metrics over the course of their recovery, changes that matched well with the frequency band-specific diagnostic value of the metric. Strikingly, connectivity during a single task-free EEG measurement predicted the level of patient recovery with an accuracy of 75% about 3 months later. Our findings demonstrate that spectral amplitude and connectivity track patient recovery in a longitudinal manner, and these metrics are robust pathophysiological markers that can be used for the automated diagnosis and prognosis of disorders of consciousness. These metrics can be obtained inexpensively at the bedside and are completely independent of the patient's neurocognitive abilities. Finally, our findings cautiously suggest that the relative preservation of thalamo-cortico-thalamic interactions may predict the later re-emergence of consciousness and thus shed new light on the pathophysiological processes underlying disorders of consciousness.

Keywords
Disorders of consciousness, Brain injury, EEG, Classification