Brain Marker Links Stress and Nicotine Abstinence
Bibliographic record
Abstract
BACKGROUND: Subjective stress is a well-documented predictor of early smoking relapse, yet our understanding of stress and tobacco use is limited by reliance on self-reported measures of stress. We utilized a validated functional neuroimaging paradigm to examine whether stress exposure during early abstinence alters objective measures of brain function. METHODS: Seventy-five participants underwent blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) during the Montreal Imaging Stress Task (MIST) on two occasions: once during smoking satiety and once following biochemically confirmed 24-hour abstinence (order counterbalanced). The primary outcome measure was brain response during stress (vs. control) blocks of the MIST, assessed using whole-brain analysis corrected for multiple comparisons using clusters determined by Z ≥ 3.1. RESULTS: Abstinence (vs. satiety) was associated with significantly increased activation in the left inferior frontal gyrus, a brain region associated with inhibitory control. Abstinence-induced change in brain response to stress was positively associated with change in self-reported stress. CONCLUSIONS: This study provides objective evidence that the brain response to stress is altered during the first 24 hours of a quit attempt compared to smoking satiety. IMPLICATIONS: These results point to the potential value of inoculating smokers with stress management training prior to a quit attempt.
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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".