Cambridge: When patients are put under general anaesthesia, their brain activity frequently slows as they fall asleep. Higher anaesthetic medication dosages can cause an even deeper state of unconsciousness called burst suppression, which is associated with cognitive deficits once the patient awakens.
A recent MIT study that examined the EEG patterns of patients under anaesthesia showed brain wave characteristics that might aid anesthesiologists in determining when patients are moving into that deeper level of unconsciousness. This may allow them to keep patients from entering that condition, lowering the risk of postoperative brain damage.
One of these distinctive patterns emerged in the brain’s alpha waves (which have a frequency of eight to 14 cycles per second). Once patients became unconscious, these waves started to wax and wane in amplitude. As patients went deeper into unconsciousness, the pattern of this waxing and waning in amplitude, or amplitude modulation, continually changed.
“If you track this modulation as it gets deeper or shallower, you have a very principled way to track the level of unconsciousness under anaesthesia,” says Emery Brown, the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience and a member of MIT’s Picower Institute for Learning and Memory and the Institute for Medical Engineering and Science.
Brown is the senior author of the new study, which appears this week in the Proceedings of the National Academy of Sciences. The lead authors of the paper are Picower Institute research scientist Elie Adam, Ohyoon Kwon ’20, and graduate student Karla Montejo.
Brain waves, which are generated by synchronized neuronal activity, oscillate at different frequencies depending on what kind of task the brain is performing. When the brain is strongly engaged in mental activity, it produces higher-frequency beta (15-30 hertz) and gamma (greater than 30 hertz) oscillations, which are believed to help organize information and enhance communication between different brain regions.
Commonly used anaesthesia drugs such as propofol have a significant effect on these oscillations. During anaesthesia induced by propofol or other anaesthetics that increase the effectiveness of GABAergic inhibitory receptors in the brain, the brain enters a state of unconsciousness known as slow-delta-alpha (SDA). This state is characterized by slow (0.1-1 hertz), delta (1-4 hertz) and alpha (8-14 hertz) oscillations.
With higher doses of these anaesthetic drugs, the brain can fall into an even deeper state of unconsciousness. When in this state, known as burst suppression, EEG recordings from the brain show long periods of inactivity, punctuated by brief bursts of low-amplitude oscillations.
When patients enter this state, they are more likely to experience postoperative confusion, delirium, and memory loss. These effects, which can last for hours, days, weeks, or months, are more common in elderly patients.
SDA and burst suppression produce distinctive EEG patterns that have been well-studied. However, they have been studied as separate brain states; what happens during the transition between the two states is less clear. That transition is what the MIT team set out to analyze in this study.
To do that, the researchers studied 10 healthy volunteers and 30 patients who were undergoing surgery. Most of the patients received propofol intravenously, and the rest received sevoflurane, a commonly used anaesthetic gas. Both of these drugs act on GABA receptors in the brain, which reduce neuron excitability.
As the dosage of propofol was increased, patients showed two distinctive patterns of change in their EEGs. The first pattern was seen in the alpha waves, which started to wax and wane. As the dose increased, waxing was shortened and waning was prolonged, until the patient reached the state of burst suppression.
“You can see a very strong modulation, which is always there. As the modulation gets to be more profound, it eventually flattens out, and that's when the brain reaches the deeper state,” Brown said. (ANI)
