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• Ketamine is an anesthetic drug with dissociative properties. • Ketamine induces highly structured oscillations that may be used to monitor drug-induced altered arousal. • Surface electroencephalogram oscillations are unlikely to underly ketamine-induced dissociation. Ketamine is an anesthetic drug associated with dissociation. Decreased electroencephalogram alpha (8–13 Hz) and low-beta (13–20 Hz) oscillation power have been associated with ketamine-induced dissociation. We aimed to characterize surface electroencephalogram signatures that may serve as biomarkers for dissociation. We analyzed data from a single-site, open-label, high-density surface electroencephalogram study of ketamine anesthesia (2 mg/kg, n = 15). We assessed dissociation longitudinally using the Clinician Administered Dissociation States Scale (CADSS) and administered midazolam to attenuate dissociation and enable causal inference. We analyzed electroencephalogram power and global coherence with multitaper spectral methods. Mixed effects models were used to assess whether power and global coherence signatures of ketamine could be developed into dissociation-specific biomarkers. Compared to baseline, ketamine unresponsiveness was associated with increased frontal power between 0.5 to 9.3 Hz, 12.2 to 16.6 Hz, and 24.4 to 50 Hz. As subjects transitioned into a responsive but dissociated state (mean CADSS ± SD, 22.1 ± 17), there was a decrease in power between 0.5 to 10.3 Hz and 11.7 to 50 Hz. Midazolam reduced dissociation scores (14.3 ± 11.6), decreased power between 4.4 to 11.7 Hz and increased power between 14.2 to 50 Hz. Our mixed-effects model demonstrated a quadratic relationship between time and CADSS scores. When models (frontal power, occipital power, global coherence) were reanalyzed with midazolam and electroencephalogram features as covariates, only midazolam was retained. Ketamine is associated with structured electroencephalogram power and global coherence signatures that may enable principled anesthetic state but not dissociation monitoring. A neurophysiological biomarker for dissociation may lead to a better understanding of neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]