Dynamic reconfiguration of frequency-specific cortical coactivation patterns during psychedelic and anesthetized states induced by ketamine

Abstract

Recent neuroimaging studies have demonstrated that spontaneous brain activity exhibits rich spatiotemporal structure that can be characterized as the exploration of a repertoire of spatially distributed patterns that recur over time. The repertoire of brain states may reflect the capacity for consciousness, since general anesthetics suppress and psychedelic drugs enhance such dynamics. However, the modulation of brain activity repertoire across varying states of consciousness has not yet been studied in a systematic and unified framework. As a unique drug that has both psychedelic and anesthetic properties depending on the dose, ketamine offers an opportunity to examine brain reconfiguration dynamics along a continuum of consciousness. Here we investigated the dynamic organization of cortical activity during wakefulness and during altered states of consciousness induced by different doses of ketamine. Through k-means clustering analysis of the envelope data of source-localized electroencephalographic (EEG) signals, we identified a set of recurring states that represent frequency-specific spatial coactivation patterns. We quantified the effect of ketamine on individual brain states in terms of fractional occupancy and transition probabilities and found that ketamine anesthesia tends to shift the configuration toward brain states with low spatial variability. Furthermore, by assessing the temporal dynamics of the occurrence and transitions of brain states, we showed that subanesthetic ketamine is associated with a richer repertoire, while anesthetic ketamine induces dynamic changes in brain state organization, with the repertoire richness evolving from a reduced level to one comparable to that of normal wakefulness before recovery of consciousness. These results provide a novel description of ketamine's modulation of the dynamic configuration of cortical activity and advance understanding of the neurophysiological mechanism of ketamine in terms of the spatial, temporal, and spectral structures of underlying whole-brain dynamics.

Keywords: Electroencephalography; General anesthesia; Ketamine; Psychedelic.

Fig. 1.

Schematic overview of the analysis pipeline. The 128-channel EEG data of 15 subjects during baseline, subanesthetic and anesthetic ketamine, as well as recovery period, were preprocessed in sensor space and concatenated for the analysis. Cortical sources were estimated using the weighted minimum norm estimation (wMNE) method, followed by the extraction of regional time series by averaging the cortical activity across voxels within each of the 100 regions based on the Yeo atlas. Each region can be matched to one of the seven resting-state networks (RSNs): FPN, frontoparietal network, DMN, default mode network, DAT, dorsal attention network, LIM, limbic network, VAT, ventral attention network, SOM sensorimotor network, and VIS, visual network. Band-limited envelope data were derived from Hilbert transformation and aggregated across all studied periods and subjects. K-means clustering algorithm was applied to generate a discrete set of brain states and the state time series for each studied period and subject. The spectral and spatial properties of the brain states, the temporal dynamics of state time series and their alterations with different dosing of ketamine were subsequently characterized.

Fig. 2.

Brain states represent distinct spectral and spatial coactivation patterns in spontaneous cortical activity. (A) Ten brain states, identified by k-means clustering of the band-limited envelope data from 15 subjects during four periods (baseline, ketamine subanesthesia, ketamine anesthesia, and recovery), were sorted according to their specificity for baseline and anesthesia (i.e., the difference in probability of a brain state occurring within baseline and anesthesia periods). (B) Spectral and spatial distribution for each brain state, defined as the centroid of each cluster normalized by the standard deviation of all samples that were assigned to the same cluster. (C) Cosine similarity between each brain state in the dominant frequency band with seven canonical resting-state networks defined in the Yeo atlas, with positive (red) and negative (blue) values corresponding to high and low (above and below average) amplitude activity, respectively.

Fig. 3.

Temporal characteristics of the brain states and the effect of ketamine on state occurrence dynamics. (A) Fractional occupancy, defined as the fraction of time spent in each brain state. (B) The mean dwell time, defined as the average amount of time spent in each state before transitioning out of that state. (C) The mean interval time, defined as the average amount of time spent between consecutive visits to a certain state. (D) Fractional occupancy in each brain state across the studied period of baseline, subanesthesia, anesthesia, and recovery. The height of the colored bar and errorbar denote the mean and SD of the values across subjects. (E) Changes in the entropy that measures the distribution of fractional occupancy of brain states across the studied periods. For each subject, the anesthesia period was equally divided into four segments, and the state occupancy and entropy values were calculated for each segment individually. In A–C and E, the central line and edges on each box indicate the median and the interquartile range (IQR) of the values across the subjects, the whiskers extend to the most extreme values, and the outliers are marked as red crosses. In D,E, * indicates statistically significant difference relative to baseline (Bonferroni corrected p < 0.05, linear mixed model analysis).

Fig. 4.

The effects of ketamine on state transition dynamics. (A) Group average state transition matrix for each of the studied periods, with each off-diagonal element indicating the probability of transitioning from any state in each row to another state in the given column, while the element on the diagonal line indicates the probability of staying in a certain state. The elements with + indicate the state transitions with the probability statistically higher than those of random transitioning by permutating the temporal order while keeping the occupancy of the states (FDR-adjusted p < 0.05). (B) Group average state transition matrix from the retained state time series after removing the state stays. The elements with + indicate the state transitions with the probability statistically higher than average transition rate (1/90 in this study) (FDR-adjusted p < 0.05, Wilcoxon signed rank test). (C) Changes in state persistence and transition probabilities in subanesthesia, anesthesia, and recovery relative to baseline. Each node indicates a brain state, with different colors denoting statistically higher (red), lower (blue), or no changes (black) in the probability of staying in that state (FDR-adjusted p < 0.05, Wilcoxon signed rank test). The directed arrows in red (blue) denoted statistically higher (lower) probability for that transition (FDR-adjusted p < 0.05, Wilcoxon signed rank test). (D) Changes of transition rate. (E,F) Changes in entropy values associated with state persistence and transition probabilities (E) or state transition probabilities only (F). In D–F, * indicates statistically significant difference relative to baseline (Bonferroni corrected p < 0.05, linear mixed model analysis).