Chronic alcohol exposure differentially modulates structural and functional properties of amygdala: A cross‐sectional study
Bibliographic record
Abstract
Abstract Animal models have shown that chronic alcohol exposure is associated with persistent neuroadaptations in amygdala synaptic function, whereas human studies have consistently reported amygdala grey‐matter volume (GMV) reductions in alcohol dependent patients (ADP). We hypothesised that chronic alcohol use associated with neuroadaptations may entail a reconfiguration of the amygdala's functional interactions and that these mechanisms may be affected by structural atrophy. We compared amygdala resting state functional connectivity (RSFC) using a whole brain seed‐based approach and amygdala GMV in abstinent ADP ( n = 20) and healthy controls (HC; n = 39), balanced for age, gender and levels of head motion. The potential moderating influence of age, cumulative alcohol exposure, abstinence length and head motion was further examined in the two groups separately using correlational analyses. We found increased amygdala RSFC with substantia nigra/ventral tegmental area (SN/VTA) in ADP compared with HC. As expected, amygdala GMV was lower in ADP. Multiple regression analyses of the ADP group showed that amygdala‐SN/VTA RSFC increases were primarily associated with cumulative alcohol exposure rather than age, whereas amygdala GMV reductions were primarily associated with age rather than cumulative alcohol exposure. The same association between age and amygdala GMV was not observed amongst HC. Importantly, amygdala GMV and amygdala‐SN/VTA RSFC were uncorrelated in ADP, and neither measure was correlated with abstinence length. These results suggest that chronic alcohol exposure is associated with persistent elevations in amygdala‐SN/VTA RSFC and accelerated age‐related grey‐matter atrophy through potentially distinct mechanisms.
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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 | 0.001 |
| 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) | 0.000 | 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".