Consciousness is a peculiar, even supernatural idea. From three pounds of flesh emerges an awareness of the body that houses it and the world around it. We all recognize consciousness when we see it, but what is it, really? And where does it go when it’s gone? Neuroscience doesn’t have the tools to answer these questions—if they’re really possible to answer at all—but in a hospital, doctors need to be able to diagnose consciousness. They need to know if a patient with a brain injury is aware of himself or surroundings. This diagnosis is still mostly made with a simple bedside exam. Is the patient following commands? Is he gesturing or verbalizing purposefully, etc.?
For patients at the edge of consciousness—not lucid but not comatose either—defining the state of consciousness is difficult. Purposeless movements and sounds can look a lot like purposeful ones. Awareness comes and goes. In many, a high stakes diagnosis will be made. The patient is either in a minimally conscious state, where there’s some likelihood of recovery, or the patient is given a diagnosis of unresponsive wakefulness syndrome, where the actions are deemed random and purposeless and there’s little hope of recovery. Troublingly, these diagnoses are mixed up in as many as 40% of cases.
With a great deal at stake, a recent study in the journal Brain tries to give doctors a little help. The article details a machine learning algorithm that distinguishes unresponsive wakefulness syndrome from a minimally conscious state using EEG brainwave recordings. The algorithm, if put into use, would take some of the guesswork out of this diagnosis, and likely perform better than most human doctors. But diagnosing state-of-mind with an algorithm raises ethical concerns. How comfortable are we with turning over this kind of life-or-death diagnosis to a machine, especially since our handle on consciousness, as an idea, is so minimal?
Looking into the brain for traces of consciousness is not a new idea. For decades, researchers have been studying how brain scanning techniques like PET and fMRI could be used to study the edge of consciousness. In a landmark 2014 study, PET scans showed that brains could respond to cues in some patients given a (mis)diagnosis of unresponsive wakefulness syndrome. What’s more is that the patients with an active PET scan were more likely to make a meaningful recovery.
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