Enhanced smoking cue salience associated with depression severity in nicotine-dependent individuals: a preliminary fMRI study
Bibliographic record
Abstract
The association between cigarette smoking and depression has been well documented; however, little research has been done to elucidate the neurobiological substrates of this highly prevalent comorbidity. We used multiple linear regression analysis to evaluate the relationship between depression severity as assessed by the Hamilton Depression Rating Scale (HAMD) and blood oxygen level-dependent (BOLD) responses to visual smoking cues in drug-free nicotine-dependent smokers (n=18). Two functional magnetic resonance imaging (fMRI) scans were completed over a single study day, following overnight smoking abstinence (pre-smoking scan) and after cigarette reinstatement (post-smoking scan). During the pre-smoking scan positive correlations between BOLD activity and HAMD scores were observed in areas of the mesocorticolimbic dopaminergic system [inferior frontal gyrus, middle frontal gyrus (MFG), hippocampus (HC), anterior cingulate gyrus] and areas of the visuospatial attention circuit (medial occipital lobe, middle cingulate cortex, superior frontal gyrus, angular gyrus). During the post-smoking scan positive correlations were observed in areas of the brain implicated in drug expectancy (MFG), memory (HC), attentional motivation (posterior cingulate cortex), and visual processing and attention (precuneus). These preliminary findings demonstrate that smokers with higher depression severity attribute greater incentive salience to smoking-related cues and this is especially pronounced during periods of acute abstinence. Such enhanced salience of smoking cues, even after smoking a cigarette, may play a critical role both in the maintenance of smoking in depression and in greater levels of nicotine dependence seen in this patient population.
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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".