Potential neuropsychological mechanism involved in the transition from suicide ideation to action – a resting-state fMRI study implicating the insula
Bibliographic record
Abstract
BACKGROUND: Understanding the neural mechanism underlying the transition from suicidal ideation to action is crucial but remains unclear. To explore this mechanism, we combined resting-state functional connectivity (rsFC) and computational modeling to investigate differences between those who attempted suicide(SA) and those who hold only high levels of suicidal ideation(HSI). METHODS: A total of 120 MDD patients were categorized into SA group (n=47) and HSI group (n=73). All participants completed a resting-state functional MRI scan, with three subregions of the insula and the dorsal anterior cingulate cortex (dACC) being chosen as the region of interest (ROI) in seed-to-voxel analyses. Additionally, 86 participants completed the balloon analogue risk task (BART), and a five-parameter Bayesian modeling of BART was estimated. RESULTS: In the SA group, the FC between the ventral anterior insula (vAI) and the superior/middle frontal gyrus (vAI-SFG, vAI-MFG), as well as the FC between posterior insula (pI) and MFG (pI-MFG), were lower than those in HSI group. The correlation analysis showed a negative correlation between the FC of vAI-SFG and psychological pain avoidance in SA group, whereas a positive correlation in HSI group. Furthermore, the FC of vAI-MFG displayed a negative correlation with loss aversion in SA group, while a positive correlation was found with psychological pain avoidance in HSI group. CONCLUSION: In current study, two distinct neural mechanisms were identified in the insula which involving in the progression from suicidal ideation to action. Dysfunction in vAI FCs may gradually stabilize as individuals experience heightened psychological pain, and a shift from positive to negative correlation patterns of vAI-MFC may indicate a transition from state to trait impairment. Additionally, the dysfunction in PI FC may lead to a lowered threshold for suicide by blunting the perception of physical harm.
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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) | 0.001 | 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".