Inhibitory deficits for negative information in persons with major depressive disorder
Bibliographic record
Abstract
BACKGROUND: Within Beck's cognitive model of depression, little is known about the mechanism(s) by which activated self-schemas result in the production of negative thoughts. Recent research has demonstrated that inhibitory dysfunction is present in depression, and this deficit is likely valence-specific. However, whether valence-specific inhibitory deficits are associated with increased negative cognition and whether such deficits are specific to depression per se remains unexamined. The authors posit the theory that inhibitory dysfunction may influence the degree to which activated self-schemas result in the production of depressive cognition. METHOD: Individuals with major depressive disorder (MDD, n=43) versus healthy (n=36) and non-depressed anxious (n=32) controls were assessed on the Prose Distraction Task (PDT), a measure of cognitive inhibition, and the Stop-Signal Task (SST), a measure of motor response inhibition. These two tasks were modified in order to present emotionally valenced semantic stimuli (i.e. negative, neutral, positive). RESULTS: Participants with MDD demonstrated performance impairments on the PDT, which were most pronounced for negatively valenced adjectives, relative to both control groups. Moreover, these impairments correlated with self-report measures of negative thinking and rumination. Conversely, the performance of the MDD participants did not differ from either control group on the SST. CONCLUSIONS: Implications of these findings for understanding the mechanisms underlying the development and maintenance of depressive cognition are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".