Potential Neural Pathway for Explaining Suicidal Behaviour: Does it Exist?
Bibliographic record
Abstract
Suicide is a major health problem, with a lack of decline in suicide rates over the past few decades suggesting existing treatment methods are not effective enough in dealing with suicidal behaviour. A review of the existing neuroimaging literature on suicidal behaviour suggests that a core, “skeleton” neural pathway exists in that a majority of suicidal individuals tend to have structural and functional alterations in the ACC, PFC (more specifically the OFC) and insular cortex. This proposed pathway is able to explain the two main cognitive-behavioural characteristics observed in suicidal individuals: increased impulsivity and impaired decision-making, and emotional dysregulation. Abnormalities in other brain regions may exist in suicidal individuals depending on certain characteristics; most notably, the presence of a comorbid mental disorder may be correlated with impairments of specific brain structures depending on the disorder that is present. Future neuroscientific and psychological research should aim to increase the replicability of neuroimaging studies, determine the extent of the impact a comorbid mental disorder has on the observed location of neural abnormalities in the brain, and to unify the definitions of terminology used in the study of suicide to increase validity and compatibility across suicidology research.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".