Person:

Eskandar, Emad

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.

Why seizures spontaneously terminate remains an unanswered fundamental question of epileptology. Here we present evidence that seizures self-terminate via a discontinuous critical transition or bifurcation. We show that human brain electrical activity at various spatial scales exhibits common dynamical signatures of an impending critical transition—slowing, increased correlation, and flickering—in the approach to seizure termination. In contrast, prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. To support these results, we implement a computational model that demonstrates that alternative stable attractors, representing the ictal and postictal states, emulate the observed dynamics. These results suggest that self-terminating seizures end through a common dynamical mechanism. This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature.

Brain activity is characterized by oscillatory activity that spans at least two orders of magnitude. Previous investigations of the spatiotemporal dynamics of this wide range of oscillatory behavior has led to the concept that long-range intercortical interactions are expressed in low-frequency patterns while higher frequencies reflect more local intracortical connectivity. This inverse relationship between frequency and spatial coherence is seen as one of a small number of nearly universal rules governing brain activity. While there is substantial evidence for this proposition, there are surprisingly few direct, quantitative investigations of this phenomenon, especially in human cortex. To more completely characterize the spatial characteristics of ongoing brain activity, we investigated the coherence in di erent brain states- awake and sleep, at di erent frequencies, and with respect to a wide range of distances using standard pial surface macroelectrode arrays (1 cm spacing in an 8x8 cm grid), mesogrids (5 mm spacing), microgrids (1 mm spacing), and microelectrode arrays (400 micron spacing in 4x4mm arrays). As expected, we found that correlations and coherence decreases as a function of increasing interelectrode distance and as a function of frequency. We observed a robust linear relationship up until 1 cm; for distances 1 cm and greater, the relationship was largely non-linear. This relationship was not strongly a ected by speci ccortical lobe, nor was the overall coherence signi cantly di erent between awake and asleep states. These data are congruent with the overall notion that frequency and spatial relationships are inversely related with faster frequencies being more focal and provides an important quantitative assessment of that relationship with implications for the spatial scale of neural processing and recordings.

Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these “Motifs” were compared between sleeps preceding the waking period (“Sleep-Pre”) when the Motifs were identified, and those following (“Sleep-Post”). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.