1062 EEG-Derived Biomarkers Predict Sleep Perception Impairment in Major Depression

Abstract Introduction Sleep perception impairment (SPI) in depression refers to a marked discrepancy between subjective and objective sleep, similar to paradoxical insomnia. Many depressed patients report poor sleep despite normal polysomnography (PSG), yet the neurophysiological basis of this misperception remains unclear. We examined whether EEG microarchitecture features differentiate depressed patients with SPI from those without SPI. Methods We included 63 adults with major depressive disorder and insomnia symptoms who underwent overnight PSG. SPI was defined as underestimating sleep by ≥60 minutes compared with PSG-derived total sleep time. Based on this criterion, 26 participants were classified as SPI and 37 as non-SPI. Continuous EEG measures were extracted, including total spectral power (0.5–40 Hz, μV²), an interhemispheric symmetry index (ratio of NREM spindle-band power between hemispheres), and high-frequency spectral ratios (e.g., beta/delta, gamma/delta). Group differences were examined, and multivariable logistic regression evaluated EEG predictors of SPI. Linear regression assessed associations with the magnitude of subjective–objective sleep discrepancy. Results Objective sleep duration was comparable between groups (~7 hours), yet SPI participants perceived significantly shorter sleep. SPI patients showed lower total EEG power (9730 ± 2767 μV² vs 12482 ± 4179 μV², p = 0.003) and reduced EEG symmetry (0.50 vs 0.51, p = 0.02). High-frequency activity was elevated in SPI: the N2 beta/delta ratio was higher in SPI (0.34 vs 0.26, p = 0.02), with similar increases in gamma/delta ratio (p = 0.01). In adjusted logistic models, higher total EEG power predicted lower SPI likelihood (OR ≈ 0.35 per 1000 μV², p < 0.05). A 0.01 increase in symmetry index was similarly protective (OR ≈ 0.47, p < 0.05). Higher beta/delta ratio was associated with greater SPI odds (approximately two-fold per 0.1 increment). Linear regression showed that greater EEG power related to a smaller subjective-objective sleep gap (β = –34 min, p = 0.04). Conclusion Depressed patients with SPI demonstrate distinct EEG microarchitecture marked by reduced slow-wave amplitude, elevated fast-frequency activity, and subtle interhemispheric asymmetry. This objectively “lighter” sleep pattern supports a cortical hyperarousal mechanism underlying sleep misperception. Continuous EEG features—particularly total power, symmetry, and spectral ratios—may serve as promising biomarkers to identify SPI and inform targeted interventions. Support (if any)