Distinct <scp>EEG</scp> Features and Sleep/Wake Behaviour Predict Anxiety Phenotypes in Mice

Preoperative anxiety is a prevalent clinical problem linked to adverse surgical outcomes, including elevated pain, prolonged hospital stays and increased risk of postoperative delirium. Current assessments rely heavily on subjective measures, necessitating objective biomarkers. We investigated whether baseline electroencephalography (EEG) and sleep-wake profiles can predict anxiety levels in a mouse model. Fifty male C57BL/6N mice were implanted with EEG and electromyography (EMG) electrodes, recorded for 24 h post-recovery before undergoing a cued fear-conditioning protocol. Six behavioural indices, capturing freezing during tone and intertone epochs in both conditioning and retrieval, were used in k-medoids clustering to classify mice into high-anxiety or low-anxiety groups. Comparative analysis revealed pronounced group differences in baseline sleep architecture. HA mice exhibited diminished rapid eye movement sleep (REMS) proportions and elevated NREMS in the dark period, alongside altered bout lengths. Spectral analysis underscored lower delta (0.5-2 Hz) power in high-anxiety mice, with heightened eta/beta (~15-30 Hz) activity during REMS suggesting aberrant cortical arousal. Moreover, high-anxiety mice showed significantly longer and higher-amplitude sleep spindles, reinforcing the interplay between disrupted sleep microstructure and enhanced anxiety-like responses. These findings illustrate that specific EEG and sleep-wake parameters prior to a conditioned stimulus can forecast distinct anxiety phenotypes in a widely used inbred mouse model. Although our study focuses on fundamental mechanisms in laboratory animals, this line of research may lead to objective markers of anxious behaviour susceptibility in broader contexts, potentially identifying individuals at higher risk for heightened anxiety in clinically relevant settings, for example, preoperative anxiety.