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Record W4413284839 · doi:10.1093/ijnp/pyaf052.333

643. RESTING-STATE FUNCTIONAL CONNECTIVITY ASSOCIATIONS WITH SUICIDAL IDEATION SEVERITY IN TREATMENT-RESISTANT DEPRESSION

2025· article· en· W4413284839 on OpenAlexaff
Patricia Burhunduli, Zhuo Fang, Katie L. Vandeloo, Farzana Sharmin, Pierre Blier, Jennifer L. Phillips

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsSuicidal ideationDepression (economics)Functional connectivityResting state fMRIPsychologyClinical psychologyTreatment-resistant depressionPsychiatryMedicineNeuroscienceMajor depressive disorderSuicide preventionPoison controlMedical emergencyCognition

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.055
GPT teacher head0.429
Teacher spread0.374 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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