Measuring consciousness in the clinic
 

Last updated: 9/1/23

I wrote the majority of this post as prep work on the plane to a conference largely about anesthesia and methods to monitor consciousness in human patients. I went to the conference in search of pragmatic approaches to measuring consciousness and to get a feel for how the field thinks. The below is unpolished and a work-in-progress. I added anecdotes from clinicians and researchers I’ve talked to + some takeaways about the field.


There are a lot of theories of consciousness circulating academic discourse — a recent count places it at over 30, with the more popular including Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNW). Yet, neurologists and anesthesiologists are faced with the problem of inferring consciousness in their patients every day, and the majority of them attempt to do so with much simpler tools than these theories require.

Background

Measures of consciousness are usually tested first on healthy patients in varying states (waking, various depths of sleep, anesthetized, etc), and then extended to patients with disorders of consciousness (DoCs). Several of these have been developed to monitor anesthetic depth during medical procedures or to evaluate consciousness and potential for recovery in patients with DoCs. I mostly focus on neurological techniques, excluding simple physiological measures like pupil dilation, body temperature, heart rate, etc.


DoCs are defined pretty broadly — the NHS describes a DoC as a state where consciousness has been affected by damage to the brain. So, this could range from a coma in which a patient is totally unresponsive to split brain patients in which precepts presented to left and right sense organs are only perceived by one half of the brain.


DoCs are tricky because self-report is often compromised. Measuring consciousness typically depends on comparing neurological data to self-report or behavior. A clinician or researcher may look at EEG data for example and compare that to the patient’s behavior or verbal description of their state. But, there are cases where a patient appears unconscious, but their cognition isn’t compromised (usually called locked-in syndrome). This is where (imo) the interesting research happens in the field — what do we do when we can’t depend on self-report? For more on how to think through this question, I’d check out No-Report Paradigms: Extracting the True Neural Correlates of Consciousness and my favorite experimental paper on this topic A new no-report paradigm reveals that face cells encode both consciously perceived and suppressed stimuli.

‍Perturbational Complexity Index

It seems like the Perturbational Complexity Index (PCI) may be the most effective existing measure of consciousness in patients with DoCs. The clinicians I spoke to at this conference weren’t familiar with PCI although several researchers were.  As far as I know, PCI hasn’t been actually translated to the clinic (except perhaps in the cases of clinicians who participate in PCI research) although I think the creators are pushing for that.


The basic idea is that brain activity is thought to be less complex during unconsciousness. PCI works by perturbing the brain (typically the superior frontal and/or parietal cortex) with transcranial magnetic stimulation (TMS), recording the resultant electrical activity, and then calculating its normalized Lempel-Ziv complexity (a popular measure of compressibility). In the standard clinical setting, doctors use non-invasive methods, so activity is typically measured with EEG.