Local cortical dynamics of burst suppression in the anaesthetized brain

Abstract

Burst suppression is an electroencephalogram pattern that consists of a quasi-periodic alternation between isoelectric 'suppressions' lasting seconds or minutes, and high-voltage 'bursts'. It is characteristic of a profoundly inactivated brain, occurring in conditions including hypothermia, deep general anaesthesia, infant encephalopathy and coma. It is also used in neurology as an electrophysiological endpoint in pharmacologically induced coma for brain protection after traumatic injury and during status epilepticus. Classically, burst suppression has been regarded as a 'global' state with synchronous activity throughout cortex. This assumption has influenced the clinical use of burst suppression as a way to broadly reduce neural activity. However, the extent of spatial homogeneity has not been fully explored due to the challenges in recording from multiple cortical sites simultaneously. The neurophysiological dynamics of large-scale cortical circuits during burst suppression are therefore not well understood. To address this question, we recorded intracranial electrocorticograms from patients who entered burst suppression while receiving propofol general anaesthesia. The electrodes were broadly distributed across cortex, enabling us to examine both the dynamics of burst suppression within local cortical regions and larger-scale network interactions. We found that in contrast to previous characterizations, bursts could be substantially asynchronous across the cortex. Furthermore, the state of burst suppression itself could occur in a limited cortical region while other areas exhibited ongoing continuous activity. In addition, we found a complex temporal structure within bursts, which recapitulated the spectral dynamics of the state preceding burst suppression, and evolved throughout the course of a single burst. Our observations imply that local cortical dynamics are not homogeneous, even during significant brain inactivation. Instead, cortical and, implicitly, subcortical circuits express seemingly different sensitivities to high doses of anaesthetics that suggest a hierarchy governing how the brain enters burst suppression, and emphasize the role of local dynamics in what has previously been regarded as a global state. These findings suggest a conceptual shift in how neurologists could assess the brain function of patients undergoing burst suppression. First, analysing spatial variation in burst suppression could provide insight into the circuit dysfunction underlying a given pathology, and could improve monitoring of medically-induced coma. Second, analysing the temporal dynamics within a burst could help assess the underlying brain state. This approach could be explored as a prognostic tool for recovery from coma, and for guiding treatment of status epilepticus. Overall, these results suggest new research directions and methods that could improve patient monitoring in clinical practice.

Keywords: general anaesthesia; human; intracranial electroencephalogram; neurophysiology.

Figures

Figure 1

The state of burst suppression can be limited to a local cortical region. (A) Reconstructed MRI for Patient A, showing grid electrode locations. Arrows mark the channels that are displayed in panels B and C. (B) Example time-series in different cortical regions where all channels are in burst suppression, but bursts are asynchronous in different regions. (C) Example from later in recording in the same regions as A: channel 55 is in burst suppression, whereas channels 17 and 12 are not. The state of burst suppression is therefore not necessarily cortex-wide. (D) Zoomed-in example from Patient B of the burst suppression probability (BSP) changing over time: initially most channels have a high burst suppression probability, but then a subset of channels exit burst suppression (e.g. channel 44) whereas other channels maintain high burst suppression probabilities (e.g. channel 5 remains in burst suppression with a burst suppression probability >0.5). (E) Standard deviation of the burst suppression probability across all channels from panel B: the increasing standard deviation demonstrates that the burst suppression probabilities in different cortical regions are becoming uncoupled as they diverge into different states.

Figure 2

Bursts can occur in limited areas of cortex. (A) Instantaneous amplitude across all grid channels. The burst at 42 s involves all channels, but the burst at 5 s occurs in only a small subset of electrodes, indicating that a limited cortical region is bursting. (B) Histogram shows the number of grid channels participating in each burst across four patients: many bursts are global, but there is a long leftward tail to the distribution, demonstrating the frequent occurrence of local bursts.

Figure 3

Burst timing is heterogeneous across cortex. (A) Example trace from Patient C: the burst in channel 32 starts hundreds of milliseconds before the bursts in channels 36 and 34. (B) Plot of mean difference in burst onset times between electrodes shows that there are substantial timing differences in burst onsets between distant electrodes, with distant electrodes showing larger gaps in burst timing. Blue lines are mean and standard error, red stars mark distances that are significantly different than pairs 1 cm apart (n = 233 electrodes in four patients). (C) Probability that two electrodes are both bursting (total time where both electrodes burst, normalized by total time that either electrode has a burst.) Probability decreases with distance, demonstrating that distant electrodes are less likely to be simultaneously in a burst state.

Figure 4

Principal components analysis demonstrates that bursts are spatially clustered. (A) Reconstruction of the grid electrode placement in Patient D. (B) Each panel shows one of the first four principal components from Patient D, and the colour variation across the grid demonstrates how burst probability is locally differentiated. Each of the components is significantly spatially clustered (P < 0.05), demonstrating that burst properties are anatomically clustered and differ in distant cortical regions.

Figure 5

Bursts recover the spectral dynamics of propofol general anaesthesia. Average spectra (±standard error) within a burst, across all channels (n = 374 electrodes in five patients), categorized by anatomical location. Plot shows that the bursts contain increased slow power relative to the awake state, and a frontal alpha oscillation.

Figure 6

The alpha rhythm decelerates over the course of the burst. Average spectra across all channels with an alpha oscillation (n = 160 electrodes in five patients) show that there is a significant decrease in peak frequency between the early (0–1.5 s) and late (1.5–3 s) portions of a burst.