Association of QEEG Findings with Clinical Characteristics of OCD: Evidence of Left Frontotemporal Dysfunction
Bibliographic record
Abstract
OBJECTIVE: Our objectives were 1) to determine hemispheric asymmetry and regional differences on the EEGs of patients with obsessive-compulsive disorder (OCD); and 2) to investigate the effects of sex, treatment response, illness duration, and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores on quantitative electroencephalographic (QEEG) measurements. METHOD: We recorded EEGs (12-channel) from 22 unmedicated patients with OCD but no depression and from 20 age- and sex-matched control subjects. All patients and control subjects underwent detailed neurological and psychiatric evaluations including the Hamilton Depression Rating Scale (HDRS) and Y-BOCS. RESULTS: QEEG revealed higher frequencies of slow-wave bands and lower frequencies of alpha activity at predominantly left frontotemporal localization in patients with OCD, compared with control subjects. Analysis of variance of QEEG parameters and clinical characteristics showed that sex had a significant effect on delta and alpha frequencies of frontotemporal areas during hyperventilation (HV). Increasing total Y-BOCS score correlated positively with increased frequencies of right parietal delta activity and decreased frequencies of right frontotemporal alpha activity during HV. A significantly increased left frontal slow-wave activity and decreased beta activity during HV in treatment responders led us to consider that frontal lobe functions were better in this group of patients. Illness duration had no important effect on QEEG. CONCLUSION: Patients with OCD showed important frontotemporal dysfunction, predominantly in the left hemisphere. This was particularly evident in female subjects and in treatment responders. QEEG may be beneficial in understanding the neurobiological basis of OCD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".