Brain Waves During Sleep May Predict Coma Recovery

Research from Columbia University and NewYork-Presbyterian suggests that brain waves associated with sleep may help predict recovery in unresponsive patients with recent brain injuries. The study, which examined electroencephalogram (EEG) recordings from 226 comatose patients, found that the presence of sleep spindles – brief bursts of brain activity during sleep – was linked to a higher likelihood of regaining consciousness and functional independence.

The challenge of detecting consciousness

Previous studies have shown that up to a quarter of patients who appear unresponsive after a brain injury may retain some level of hidden consciousness. Advanced EEG techniques can detect cognitive motor dissociation, a condition where patients can understand and process commands but are unable to physically respond. However, these tests can be challenging to implement and may not always provide definitive results.

In search of a more practical approach, the researchers focused on sleep patterns. Brain circuits involved in sleep regulation also play a role in consciousness, suggesting that monitoring sleep activity could offer insights into a patient’s recovery potential.

Sleep spindles as a predictive marker

During their analysis, the researchers identified well-defined sleep spindles in about one-third of the patients. These spindles were more common in patients with cognitive motor dissociation and appeared to precede signs of consciousness detected by more complex EEG testing.

“The electrical activity during sleep looks relatively chaotic, and then occasionally in some patients, these very organized, fast frequencies appear.”

Dr. Jan Claassen.

Patients with both sleep spindles and cognitive motor dissociation were more likely to recover. By hospital discharge, 76% of these individuals showed signs of consciousness. A year later, 41% had regained neurological function, allowing them to perform daily tasks with minimal assistance. In contrast, only 7% of patients without spindles or cognitive motor dissociation achieved similar recovery outcomes.

“We’re at an exciting crossroad in neurocritical care where we know that many patients appear to be unconscious, but some are recovering without our knowledge. We're starting to lift the lid a little bit and find some signs of recovery as it's happening.”

Dr. Jan Claassen.

While the presence of sleep spindles correlated with better recovery, the absence of these brain waves did not rule out the possibility of improvement. Some patients without detectable spindles still regained consciousness, highlighting the need for additional predictive measures.

Implications for patient care

Although this study does not establish a causal relationship between sleep spindles and recovery, it raises the possibility that improving sleep conditions in intensive care units could support better outcomes. The ICU environment, with its constant noise and interruptions, may disrupt natural sleep patterns, potentially affecting brain recovery.

“I see these spindles as a way to direct more sophisticated testing to the patients most likely to benefit. The techniques are not ready for use in clinical practice yet, but this is something that we’re actively working on right now.” 

Dr. Jan Claassen.

The findings are relevant only for patients with recent injuries rather than those with long-term disorders of consciousness. Researchers aim to refine these methods further before they can be incorporated into routine clinical practice.

Reference: Carroll EE, Shen Q, Kansara V, et al. Sleep spindles as a predictor of cognitive motor dissociation and recovery of consciousness after acute brain injury. Nat Med. 2025. doi: 10.1038/s41591-025-03578-x

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source. Our press release publishing policy can be accessed here.

This content includes text that has been generated with the assistance of AI. Technology Networks' AI policy can be found here.