Dynamic Electrocortical States and Paradoxical Complexity during Desflurane Anesthesia

How general anesthesia alters the dynamics of electrocortical activity is crucial to understand the neural mechanisms of unconsciousness. Local cortical activity undergoes spontaneous transitions at constant anesthetic concentration. The spatial organization and temporal dynamics of state transitions in large-scale electrocortical activity is incompletely understood.

Epidural electrocorticogram was recorded from the right hemisphere in 8 rats (14 experiments) using chronically implanted 32-channel flexible electrode arrays during desflurane anesthesia at 6, 4, 2, and 0 concentrations, each maintained for 1 h. Cortical states were identified by principal component analysis of power spectrograms followed by density-based clustering simultaneously across all concentrations. State-specific spatiotemporal complexity was quantified by the normalized Lempel-Ziv algorithm to capture signal variability beyond spectral effects. Temporal dynamics were assessed by state occurrence, dwell times, and transition probabilities.

Cortical activity was organized into a set of discrete states, six of which were characterized by increased delta power and decreased complexity that broadly tracked anesthetic depth. The seventh state deviated from this progression, exhibiting reduced delta power ( P < 0.001) and elevated complexity ( P < 0.001) despite occurring during deep anesthesia. The cortex spontaneously transitioned between states approximately every 2 min (mean dwell time, 136.55 s), following structured, nonrandom dynamics primarily within light- or deep-anesthesia states (false discovery rate-corrected P < 0.05), with a mild tendency to transition from deep to light states ( P = 0.0039), consistent with anesthetic emergence.

In the absence of external stimuli at constant anesthetic concentration, the cortex transitions between multiple states, indicating that the relationship between drug concentration and cortical activity is not static but involves spontaneous dynamics including paradoxically activated states during deep anesthesia. The results provide insight into anesthesia-induced brain dynamics that may inform strategies for monitoring, modulating, and facilitating recovery from general anesthesia.