3 min readHere’s what you’ll learn when you read this story:
- Anesthesia is an important tool for exploring human consciousness, but scientists still aren’t quite sure how it works, despite using it on patients for 170 years.
- A new study analyzes the brain under anesthesia to understand how oscillatory modes reorganize as the brain moves through four levels of consciousness: wakefulness, light sedation, deep sedation, and recovery.
- Using data about these oscillatory dynamics, machine learning algorithms correctly identified the consciousness level of patients 72 percent of the time.
For decades, one of the best tools for probing the nature of human consciousness has been medicine’s most reliable method for switching it off: anesthesia. While scientists have used various drugs for this knock-out effect for around 170 years, they have yet to pinpoint the precise mechanism that causes total unconsciousness. That can lead to medical complications, as it’s tricky to know just how deeply someone is—or isn’t—under.
Now, a pair of studies (both published this year) are attempting to unravel this mystery. In the first, published in the journal Frontiers in Computational Neuroscience, scientists used fMRI technology to scan the brains of 17 healthy adults who were gradually sedated (with propofol) through four levels of consciousness—awake, light sedation, deep sedation, and recovery. They also tested the brain’s auditory responsiveness at each level by playing a five-minute clip from the 2009 film Taken.
The hope was to better understand the relationship between these levels of consciousness and the brain’s oscillatory modes. And eventually, the scientists found that anesthesia doesn’t act as an on/off switch—instead, it works by altering oscillatory modes across the brain.
“Our findings [reveal] a significant decrease in the frequency of low-frequency modes encompassing the visual and somatomotor regions and, conversely, an increase in the frequency of high-frequency modes encompassing limbic regions as consciousness levels decline,” the authors wrote. In other words, as consciousness recedes, there is a weakening of the slow, large-scale oscillations that integrate sensory input and coordinate motor processing across large-scale brain networks. At the same time, there is an increased level of fast, local activity in the emotion and memory centers of the brain, suggesting fragmented processing. And as anesthesia takes hold, sounds are still detected in the primary auditory cortex, but those signals are no longer moved into higher-order regions of the brain—they remain stymied in the unconscious brain.
Amazingly, researchers were able to model these changes and accurately create a machine-learning algorithm that could correctly identify a person’s conscious state 72 percent of the time, based only on vectors from an fMRI spatial index matrix.
Moreover—unlike traditional spectral analysis methods like the fast Fourier transform (FFT), which only reveals the temporal frequencies present in a system—the model identified frequencies corresponding to what are known as the eigenmodes of the system, capturing both the temporal and spatial nature of the oscillations. The analysis shed new light on “the intricate relationship between brain activity and consciousness levels [by] examining how shifts from wakefulness to deep sedation manifest in the brain’s dynamic oscillations and responses to external stimuli,” the authors wrote. “The identified patterns of brain activity serve as a basis for classifying consciousness levels, demonstrating the potential for novel diagnostic and monitoring tools in this field.”
A second study, published in the journal Cell Reports Medicine in late January, identified the distinct brain-wave pattern that marks the brain’s slide into unconsciousness, which could help anesthesiologists gauge levels of sedation with more precision. Using electroencephalogram (EEG) graphs, the researchers found that the low-frequency rhythms of the brain’s large-scale networks collapse under propofol. As the brain slides into unconsciousness, both sensory-motor and conscious processing break down and are replaced by locally synchronous activity. Adding to one of the main insights of the fMRI study, the EEG research also shows that auditory inputs are detected, but fail to propagate into the higher‑order cortex. The researchers explain that this is because under anesthesia, the brain’s feedforward-feedback channels (specifically, the electrical oscillation patterns called the alpha, beta, and gamma pathways) are uncoupled.
Together, these studies imply that consciousness means the integration of widely-separated regions of the brain, particularly through large-scale, low-frequency oscillations that broadcast sensory signals into higher-order brain regions. When those rhythms collapse and brainwave activity becomes locally synchronized, our reportable experience stops—and so does consciousness. The long-standing mystery of anesthesia is slowly unraveling and giving way to a detailed picture of the dynamic rhythms that form our conscious experience.
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Darren lives in Portland, has a cat, and writes/edits about sci-fi and how our world works. You can find his previous stuff at Gizmodo and Paste if you look hard enough.