Intracortical myelin in individuals with alcohol use disorder: An initial proof‐of‐concept study
Bibliographic record
Abstract
INTRODUCTION: Disruption of cortical gray matter and white matter tracts are well-established markers of alcohol use disorder (AUD), but less is known about whether similar differences are present in intracortical myelin (ICM, i.e., highly myelinated gray matter in deeper cortical layers). The goal of this study was to provide initial proof-of-concept for using an optimized structural magnetic resonance imaging (MRI) sequence to detect differences in ICM in individuals with AUD compared to control participants reporting drinking within recommended guidelines. METHODS: This study used an optimized 3T MRI sequence for high intracortical contrast to examine ICM-related MRI signal in 30 individuals with AUD and 33 healthy social drinkers. Surface-based analytic techniques were used to quantify ICM-related MRI signal in 20 bilateral a priori regions of interest based on prior cortical thickness studies, and exploratory vertex-wise analyses were examined using Cohen's d effect size. RESULTS: The global distribution of ICM-related signal was largely comparable between groups. Region of interest analysis indicated that AUD group exhibited greater ICM-related MRI signal in precuneus, ventromedial prefrontal cortex, posterior cingulate, middle anterior cingulate, middle/posterior insula, and dorsolateral prefrontal cortex (Cohen's ds = 0.50-0.75). Four regions (right precuneus, ventromedial prefrontal cortex, posterior cingulate and left dorsolateral prefrontal cortex) remained significant (p < .05) after covarying for smoking status. CONCLUSION: These findings provide initial evidence of ICM differences in a moderately sized sample of individuals with AUD compared to controls, although the inflation of type 1 error rate necessitates caution in drawing conclusions. Robustly establishing these differences in larger samples is necessary. The cross-sectional design cannot address whether the observed differences predate AUD or are consequences of heavy alcohol consumption.
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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 | 0.000 | 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) | 0.000 | 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".