Electrocortical Profiles in Relation to Childhood Adversity and Depression Severity: A Preliminary Report
Bibliographic record
Abstract
Objective: Assessment of electroencephalographic (EEG) activity in depression has provided insights into neural profiles of the illness. However, there is limited understanding on how symptom severity and risk factors, such as childhood adversity, influence EEG features. Methods: Eyes-closed EEG was acquired in N = 28 depressed individuals being treated in a tertiary psychiatric setting. Absolute alpha, beta, theta, and delta power and inter-/intra-hemispheric coherence were examined. Relations between the Montgomery-Åsberg Depression Scale (MADRS) and Adverse Childhood Experience (ACE) Questionnaire and EEG features were assessed. Results: Individuals in the high (MADRS≥30) versus lower (MADRS ≤ 29) symptom severity group exhibited greater overall beta power, and lower Fp 1 -Fp 2 delta and theta coherence. Those with high (≥3) versus lower (≤2) ACE scores exhibited greater T 7 -T 8 beta coherence. Lowest F 3 -F 4 beta coherence was observed in those with high ACE/high depression severity. A negative correlation existed between F 8 -P 8 alpha coherence and symptom severity. Conclusions: Those with higher depression severity exhibit increased beta power, possibly reflecting a hyper-vigilant state . Depression severity and ACE history may produce subtle alterations in frontal delta/theta and temporal/frontal beta coherence regions. Significance: This is the first study to examine the neural impact of depression severity and ACE-assessed childhood trauma in depressed individuals receiving treatment in a tertiary setting, accounting for the clinical reality of the prevalence of their co-occurrence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".