“[T]he leap in understanding regarding cortical dynamics with changing propofol concentrations takes us one step closer to understanding the mechanisms of anesthesia and their differences from sleep.”
IN this issue of Anesthesiology, Pullon et al.1 provide an elegant description of the fade in information flow over the surface of the brain that accompanies change in behavioral responsiveness with propofol. Using data from 16 volunteers, the authors show that incremental increases in the plasma concentration of propofol are associated with an abrupt change in electroencephalogram (EEG) connectivity with loss and, recovery, of responsiveness. Data were analyzed using Granger Causality, which is a sophisticated statistical approach to analyzing multiple time series of data (such as multiple EEG channels), and asking whether data in one series (e.g., in one EEG channel) can forecast data in another series (e.g., another EEG channel). Perhaps a bit of a misnomer (true causality is not inferred), it asks whether data are temporally related. In this context, Granger Causality is a measure of whether data in one EEG channel provide statistically significant information about future data in a different EEG channel. This is a methodology that goes beyond simple correlations, typically used in functional magnetic resonance imaging (functional connectivity), and hence is often referred to as effective connectivity. For the EEG, investigating effective connectivity allows us to more clearly describe the direction of the information flow across the scalp. Hence, Pullon et al.1 have mapped out the changes in information flow with increasing and decreasing propofol concentrations leading to loss, and recovery, of responsiveness. Studying a bidirectional effect on responsiveness is a major strength of this study. Although accumulating evidence shows that the loss and recovery of responsiveness may have differing underlying mechanisms,2 much more data are required in humans to support this concept and understand the associated shift in cortical dynamics.
The authors found changes in Granger Causality from lateral and anterior to medial and posterior electrodes with changing responsiveness, and they link this theoretically to changes in the subjects “connectedness to the environment.” The link to sensory disconnection3 seems appropriate given early data suggesting that activity in more lateral brain regions was associated with consciousness of external stimuli, whereas the more midline “Default Mode” structures were associated with introspection.4 The authors’ careful approach is important because we do not know the conscious state of these subjects. Given that propofol is associated with dreaming,5 it is entirely possible that the subjects were dreaming and disconnected from their environment in this study, rather than unconscious.3 More detailed enquiry about the conscious state of the individuals when they lose responsiveness is required to test hypotheses specifically relating to consciousness (i.e., whether subjects experience anything3 ).
What makes this article so unique is the description of abrupt changes in individual subject connectivity trajectories with change in responsiveness. These individual subject trajectories give us confidence that the results may be more widely applicable. The fact the changes occurred with loss, and reversed with return, of responsiveness is intriguing and argues for some mirror-image changes in cortical dynamics that may be associated with consciousness. Another striking finding is that it is the loss of coordinated slow activity in the brain that appeared to best match the loss, and return, of responsiveness. Granger Causality in the delta band decreased, and recovered, with behavioral responsiveness in a remarkably consistent manner across subjects and electrodes.1 The changes were most prominent in, but not restricted to, the delta band. The authors also note that similar effects were present in the faster alpha and beta bands. Alpha and beta bands are thought to play important roles in “feedback connectivity” where information flows from higher-order to lower-order cortex.6 Hence, these changes in these faster frequencies appear consistent with many theories for the importance of feedback connectivity in consciousness.7 However, the actual biologic significance of delta connectivity in wakefulness (and hence its decrease under propofol) is less clear. Wakefulness is not typically thought of as a delta dominant condition, and less than 1 Hz delta is rarely considered an important biologic marker in other settings. Of course, this does not mean that delta changes are without meaning but does imply that more research is required to understand the full significance of these changes.
Propofol-induced changes in Granger Causality suggest that there is a lack of coordination in slow (less than 1 Hz) delta activity. These data are somewhat reminiscent of the work of Murphy et al.,8 who found delta activity to be uncoordinated under propofol. Overall these observations would also seem to argue against a small group of structures coordinating delta waves during propofol sedation (as is proposed to occur during natural sleep). These changes may be mediated by direct modulation of cortex,9 rather than impairment of function of subcortical conductors such as higher-order thalamus.10 Indeed, the slow delta rhythm appears to be of cortical origin,9 and because the electroencephalogram samples such a small quantity of cortex, it appears most likely that the authors have discovered an elegant cortical correlate of loss of responsiveness under propofol.
Given extensive evidence that anaesthetics “hijack” the sleep circuitry at subcortical levels to induce hypnosis,11 the differences described in activity at the level of cortex are intriguing and may explain why anesthetics may induce a much less arousable state than sleep. Not only would this explain a key feature of anesthesia, it (theoretically) could provide a substrate for monitoring the depth of anesthesia. Unfortunately, given the amount of data required for these connectivity analyses (especially for very slow electroencephalogram bands), it is unlikely that these approaches would have the necessary temporal resolution for a depth of anesthesia monitor. Furthermore, although the individual subject trajectories give us confidence in the findings and suggest that these findings may have external validity, we do not know whether these changes occur with standard anesthetic practices (such as polypharmacy or volatile anesthesia). It is also important to note that, given the noise evident in the operating room, such as diathermy, it is unclear whether Granger Causality metrics may be reliable in clinical situations. Hence, although it is unlikely that this article will herald a new generation of depth of anesthesia monitors, the leap in understanding regarding cortical dynamics with changing propofol concentrations in humans takes us one step closer to understanding the mechanisms of anesthesia and their differences from sleep.
The author is not supported by, nor maintains any financial interest in, any commercial activity that may be associated with the topic of this article.