Cognitive inhibition in depression and suicidal behavior: a neuroimaging study
Bibliographic record
Abstract
BACKGROUND: Cognitive inhibition deficits have previously been found in suicide attempters. This study examined the neural basis for these deficits in depressed patients with and without a history of suicidal behavior. METHOD: Functional magnetic resonance imaging was used to measure brain activation during the Go/No-Go response inhibition task in 25 unmedicated and depressed middle-aged suicide attempters, 22 unmedicated depressed patient controls with no personal or family history of suicidal behavior, and 27 healthy controls. Whole-brain analyses were conducted with SPM12. RESULTS: Suicide attempters exhibited an elevated number of commission errors relative to both control groups. However, suicide attempters did not differ from patient controls in terms of brain activation for any contrast. Analyses showed a significant association between depression and brain activation in the left inferior frontal gyrus and medial thalamus during Go v. No-Go, and in the bilateral parietal cortex and left orbitofrontal cortex during No-Go v. baseline. These regions were correlated with psychological pain, suicidal ideation and global functioning. There was no association between brain activation and personal histories of suicidal act. CONCLUSIONS: Our study suggests that deficits in cognitive inhibition, in relation to the inferior frontal gyrus, thalamus, orbitofrontal cortex and parietal cortex, are related to the depressive state and not specifically to suicide vulnerability. We hypothesize that state-related deficits may add to trait-like cognitive impairments to facilitate suicidal acts. These different types of cognitive impairments may necessitate different therapeutic strategies for the prevention of suicide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".