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Distinct EEG Features and Sleep/Wake Behaviour Predict Anxiety Phenotypes in Mice
A Altunkaya1, K M Mengel1, M V Schmidt2
1Clinic for Anesthesiology and Intensive Care, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Journal of Sleep Research
|July 30, 2026
Summary
Baseline electroencephalography (EEG) and sleep patterns can predict anxiety levels. Specific EEG and sleep-wake parameters forecast distinct anxiety phenotypes, potentially identifying individuals at risk for heightened anxiety.
Area of Science:
- Neuroscience
- Sleep Science
- Animal Behavior
Background:
- Preoperative anxiety is a common clinical issue with negative surgical outcomes.
- Current anxiety assessments are subjective, highlighting the need for objective biomarkers.
Purpose of the Study:
- To investigate if baseline electroencephalography (EEG) and sleep-wake profiles predict anxiety levels in a mouse model.
- To identify objective biomarkers for anxiety prediction.
Main Methods:
- Fifty male C57BL/6N mice underwent EEG/EMG implantation and a cued fear-conditioning protocol.
- K-medoids clustering classified mice into high-anxiety (HA) or low-anxiety (LA) groups based on behavioral indices.
- Comparative analysis of baseline sleep architecture and EEG spectral analysis between groups.
Main Results:
- High-anxiety mice showed diminished REM sleep (REMS) and elevated NREMS during the dark period, with altered bout lengths.
- Spectral analysis revealed lower delta power and heightened eta/beta activity during REMS in HA mice.
- HA mice exhibited longer and higher-amplitude sleep spindles, indicating disrupted sleep microstructure and enhanced anxiety.
Conclusions:
- Specific baseline EEG and sleep-wake parameters can predict distinct anxiety phenotypes in mice.
- This research may lead to objective markers for anxiety susceptibility, relevant for clinical settings like preoperative anxiety.
