P.095 Smoking behaviour change is associated with altered functional brain connectivity in older adults
Bibliographic record
Abstract
Background: Smoking is the leading cause of preventable morbidity worldwide and therefore developing effective smoking cessation strategies is a public health priority. However, what brain networks support maintenance of smoking cessation in the long term remains unexplored. Methods: We analyzed the baseline resting-state fMRI data acquired in 23 smokers (Mage = 61.52 ± 3.7) who were followed longitudinally in a cohort of cognitively normal older adults. Self-reported smoking status and amount were recorded at baseline and repeated after 4 years. We investigated the effect of smoking behaviour change on functional brain connectivity using seed-to-voxel approach. We examined a-priori regions of interest (ROIs) including the reward network (ventromedial prefrontal cortex (vMPFC) and ventral striatum) and the right insula. These ROIs are promising target mechanisms given prior behavioural research linking it to smoking cessation. Results: Our results revealed that reduced smoking was associated with reduced connectivity between ventral striatum and middle frontal gyrus and enhanced connectivity between right insula and middle temporal gyrus (voxel p <0.001, cluster p<0.05 FDR corrected). However, change in smoking did not reveal any significant effects in the vMPFC. Conclusions: Our findings suggest that successful smoking behaviour change is associated with altered reward network and insular functional connectivity in the long term.
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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) | 0.003 | 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".