Traumatic stress reactivity promotes excessive alcohol drinking and alters the balance of prefrontal cortex-amygdala activity
Bibliographic record
Abstract
Post-traumatic stress disorder (PTSD) and alcoholism are highly comorbid in humans and have partially overlapping symptomatic profiles. The aim of these studies was to examine the effects of traumatic stress (and stress reactivity) on alcohol-related behaviors and neuronal activation patterns. Male Wistar rats were trained to respond for alcohol, were exposed to predator odor (bobcat urine) paired with context and were tested for short- and long-term avoidance of the predator odor-paired context, alcohol self-administration and compulsivity of alcohol responding. Rats were re-exposed to the odor-paired context for western blot analysis of ERK phosphorylation in subregions of the medial prefrontal cortex (mPFC) and the amygdala. Rats that avoided the predator-paired chamber (Avoiders) exhibited persistent avoidance up to 6 weeks post conditioning. Avoiders exhibited increases in operant alcohol responding over weeks, as well as more compulsive-like responding for alcohol adulterated with quinine. Following re-exposure to the predator odor-paired context, Avoiders and Non-Avoiders exhibited unique patterns of neuronal activation in subregions of the mPFC and the amygdala, which were correlated with changes in avoidance and alcohol drinking. Furthermore, activity of upstream regions was differentially predictive of downstream regional activity in the Avoiders versus Non-Avoiders. An animal model for assessing the effect of traumatic stress on alcohol drinking reveals individual differences in neuronal activation patterns associated with re-exposure to traumatic stress-related stimuli, and may provide insight into the neural mechanisms underlying excessive alcohol consumption in humans with PTSD.
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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) | 0.001 | 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".