Sevoflurane Alters Spatiotemporal Functional Connectivity Motifs That Link Resting-State Networks during Wakefulness

Abstract

Background: The spatiotemporal patterns of correlated neural activity during the transition from wakefulness to general anesthesia have not been fully characterized. Correlation analysis of blood-oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) allows segmentation of the brain into resting-state networks (RSNs), with functional connectivity referring to the covarying activity that suggests shared functional specialization. We quantified the persistence of these correlations following the induction of general anesthesia in healthy volunteers and assessed for a dynamic nature over time. Methods: We analyzed human fMRI data acquired at 0 and 1.2% vol sevoflurane. The covariance in the correlated activity among different brain regions was calculated over time using bounded Kalman filtering. These time series were then clustered into eight orthogonal motifs using a K-means algorithm, where the structure of correlated activity throughout the brain at any time is the weighted sum of all motifs. Results: Across time scales and under anesthesia, the reorganization of interactions between RSNs is related to the strength of dynamic connections between member pairs. The covariance of correlated activity between RSNs persists compared to that linking individual member pairs of different RSNs. Conclusions: Accounting for the spatiotemporal structure of correlated BOLD signals, anesthetic-induced loss of consciousness is mainly associated with the disruption of motifs with intermediate strength within and between members of different RSNs. In contrast, motifs with higher strength of connections, predominantly with regions-pairs from within-RSN interactions, are conserved among states of wakefulness and sevoflurane general anesthesia.

Keywords: Kalman filtering; dynamic functional connectivity; resting-state functional MRI; sevoflurane; spatiotemporal analysis.

Figure 1

Schematic of spatiotemporal decomposition of dynamic functional connectivity. (A) Functional connectivity over time. (B) Average FC over entire scan time. (C) Temporal and spatial motifs obtained from spatiotemporal analyses.

Figure 2

(A) Average correlation matrices (0 and 1.2%). (B) Standard error of mean (SEM) of average correlation matrices. (C) Similarity across average correlation matrices (0 and 1.2%) for entire data. (D) SEM of Similarity across average correlation matrices for entire data. (E) Similarity across average correlation matrices (0 and 1.2%) for subsampled data. (F) SEM of Similarity across average correlation matrices for subsampled data.

Figure 3

Changes in the average FC over subjects during the transition from wakefulness (0% sevoflurane) to anesthesia (1.2% sevoflurane). (A) The lower triangle shows the average FC over subjects at 0%, while the upper triangle demonstrates the difference of average FC at both conditions (0–1.2%) for each region pair. (B) Changes in the average FC for both conditions (1.2–0%) as a function of the average FC at 0%. (C) The average FC at 1.2% vs. average FC at 0%.

Figure 4

(A) Second spatial motif for 0 and 1.2%. (B) Second spatial motifs on brain surface with nodes and edges for 0%. (C) Second spatial motifs on brain surface with nodes and edges for 1.2%. Second temporal motif for (D) 0% and (E) 1.2%. (F) Third spatial motif for 0 and 1.2%. (G) Third spatial motifs on brain surface with nodes and edges for 0%. (H) Third spatial motifs on brain surface with nodes and edges for 1.2%. Second temporal motif for (I) 0% and (J) 1.2%. Blue vertical lines in the traces of the temporal motifs denote transitions of data contributed by individual participants.

Figure 5

Temporal motifs for 0 and 1.2% sevoflurane. Blue vertical lines in the traces of the temporal motifs denote transitions of data contributed by individual participants.

Figure 6

Spatial motifs for 0 and 1.2% sevoflurane.

Figure 7

Analysis of spatial motifs. (A) Bar plot of the cardinality percentage of each motif for both condition (0 and 1.2%). Error bars stand for SEM. Average similarity (B) and SEM of average similarity (C) between motifs, for 8 different window size, by computing the correlation of spatial component of each motif. (C) Standard error of similarity between motifs. Average similarity (D) and SEM of average similarity (E) between motifs calculated from each individual at 0% sevoflurane. Average similarity (F) and SEM of average similarity (G) between motifs calculated from each individual at 1.2% sevoflurane.