0960 Unraveling Sleep EEG-ECG Interactions in Major Depression: Preliminary Results of a Coherence Analysis
Bibliographic record
Abstract
Abstract Introduction In addition to common sleep disturbances, major depression involves intricate interactions between the cardiovascular and central nervous systems, underscoring the multidimensional nature of its pathophysiology. This study investigates how brain and heart activity interact across sleep states and brain topography in the context of depression. Methods Simultaneous sleep electrocardiograms (ECG) and electroencephalograms (EEG: F3, C3, and O1) were extracted from the polysomnograms of 50 individuals diagnosed with major depression and 50 controls. Following artifact removal, a coherence metric based on cross-power spectral density between the ECG and EEG was developed to characterize brain-heart connections in the 0.015-4 Hz delta and 4-8 Hz theta bands. Statistical analysis including bootstrapping, t-tests, analysis of variance, and multiple comparison tests were utilized to identify significant differences in brain-heart coherence between the depressed and healthy groups. Results Preliminary results show that, in NREM sleep within the theta band, individuals with depression showed significantly higher mean of ECG-EEG coherence values (MCV) compared to healthy controls across all EEG channels. MCVs for the depression and control group respectively were: 0.576±0.014 vs. 0.563±0.014 in F3, 0.545 ± 0.006 vs. 0.540±0.008 in C3, and 0.574±0.014 vs. 0.563±0.012 in O1 (p< 0.0001). No significant group difference was observed during REM sleep. Furthermore, irrespective of depression status, the MCV in O1 was significantly higher in NREM compared to REM sleep for the full spectrum between the delta and theta bands (p< 0.00001). In contrast, MCV in F3 and C3 did not significantly differ between NREM and REM sleep. In the delta band, regardless of depression status, the MCV was significantly lower in C3 compared to F3 and O1 during NREM sleep, but during REM sleep MCV was significantly higher in C3 than in O1 (p< 0.0001). Conclusion The higher brain-heart coherence linked to theta activity during NREM sleep we observed in people with depression may suggest stronger interactions between autonomic and cortical arousal. This could be one of the factors worsening sleep during depression. Beyond generating new insights about pathophysiological mechanisms underlying the high comorbidity between sleep, cardiovascular, and mental disorders, this may inform further work to identify multi-systemic biomarkers of depression. Support (if any)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".