643. RESTING-STATE FUNCTIONAL CONNECTIVITY ASSOCIATIONS WITH SUICIDAL IDEATION SEVERITY IN TREATMENT-RESISTANT DEPRESSION
Bibliographic record
Abstract
Abstract Background Suicidal ideation is an important modifiable risk factor for suicide in major depressive disorder and understanding its neurobiological underpinnings has important clinical implications. We used resting-state functional magnetic resonance imaging to investigate functional connectivity correlates of suicidal ideation severity in patients with treatment-resistant depression. Aims & Objectives Primary objective was to utilize resting-state functional magnetic resonance imaging techniques to investigate functional connectivity correlates of suicidal ideation severity in patients with difficult-to-treat depression. Method The sample was comprised of n=41 patients with treatment-resistant depression and a lifetime history of suicidal ideation and n=47 age- and sex- matched controls. Resting-state functional magnetic resonance imaging data was acquired at 3T and analyzed using the CONN Functional Connectivity toolbox. A whole-brain-network-based statistics approach was used with 58 preselected regions of interest. Past-week suicidal ideation severity was measured using the Columbia Suicide Severity Rating Scale (C-SSRS). Results Group-level network based statistics analysis comparing patients and controls identified one significant cluster of connections comprising 11 regions of interest and 12 connections, all depicting lower functional connectivity in patients (pFWE=0.001). Correlational network based statistics analysis identified one significant cluster of connections associated with suicidal ideation severity centered on the right posterior parietal cortex (pFWE=0.02). Patients with higher suicidal ideation severity scores had lower functional connectivity between the right posterior parietal cortex and left anterior insula (pFDR=0.07), and bilateral temporooccipital middle temporal gyrus (left: pFDR=0.03, right: pFDR=0.08). All findings were significant when controlling for depression severity. Discussion & Conclusions Our findings support existing evidence of resting-state functional connectivity differences between treatment-resistant depression and controls and shows a significant cluster of connections centered on the right posterior parietal cortex functional network, with connections showing significant negative correlations with suicidal ideation severity. These findings provide valuable insight into the neural underpinnings of suicidal ideation in treatment-resistant depression.
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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 | 0.002 |
| 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) | 0.003 | 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".