Patterns of Regional Brain Activity in Alcohol‐Dependent Subjects
Bibliographic record
Abstract
BACKGROUND: Electroencephalographic (EEG) measures of hemispheric asymmetry in anterior brain activity have been related to a variety of indices of psychopathology and emotionality. However, little is known about patterns of frontal asymmetry in alcohol-dependent (AD) samples. It is also unclear whether psychiatric comorbidity in AD subjects accounts for additional variance in frontal asymmetry, beyond a diagnosis of AD alone. METHODS: We compared 193 AD subjects with 108 control subjects on resting brain activity in anterior and posterior regions, as indexed by asymmetries in alpha band power in the left and right hemispheres. Within the AD group alone, we examined whether comorbid major depressive disorder (MDD) or antisocial personality disorder (ASPD) had effects on regional asymmetry. RESULTS: Compared with control subjects, AD subjects exhibited lower left, relative to right, cortical activation in anterior regions. Evidence that comorbidity in AD subjects accounted for further variance in EEG asymmetry was mixed; AD subjects with comorbid ASPD were not significantly different from those without ASPD, while AD subjects with a lifetime history of MDD showed less asymmetry in anterior regions than those without MDD. CONCLUSIONS: Our findings indicate that AD subjects exhibit a pattern of frontal asymmetry similar to that found in other psychiatric groups. Results examining the effects of comorbidity in AD on EEG asymmetry were inconclusive. The implications of our findings for future work are described.
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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 | 0.000 |
| 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".