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Record W2996536076 · doi:10.1101/19013193

Multimodal neuroimaging and suicidality in a US population-based sample of school-aged children

2019· preprint· en· W2996536076 on OpenAlexaff
Pablo Vidal‐Ribas, Delfina Janiri, Gaëlle E. Doucet, Narun Pornpattananangkul, Dylan M. Nielson, Sophia Frangou, Argyris Stringaris

Bibliographic record

VenuemedRxiv · 2019
Typepreprint
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of Health
KeywordsNeuroimagingPsychologySuicidal ideationPsychopathologyPopulationClinical psychologyPsychiatryPoison controlMedicineInjury prevention

Abstract

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Abstract Importance Suicide deaths and suicidality are considered a public health emergency, yet their brain underpinnings remain elusive. Objective To examine individual, environmental, and clinical characteristics, as well as multimodal brain imaging correlates of suicidality in a US population-based sample of school-aged children. Design Cross-sectional analysis of the first wave of data from the Adolescent Brain Cognitive Development study Setting Multicenter population-based study Participants Children aged 9-10 years from unreferred, community samples with suicidality data available (n=7,994). Following quality control, we examined structural magnetic resonance imaging (sMRI) (n=6,238), resting state functional MRI (rs-fMRI) (n=4,134), and task-based fMRI (range n=4,075 to 4,608). Exposure Lifetime suicidality, defined as suicidal ideation, plans and attempts reported by children or/and caregivers. Main Outcomes and Measures Multimodal neuroimaging analyses examined differences with Welch’s t-test and Equivalence Tests, with observed effect sizes (ES, Cohen’s d ) and their 90% confidence interval (CI) < |0.15|. Predictive values were examined using the area under precision-recall curves (AUPRC). Measures included, cortical volume and thickness, large-scale network connectivity and task-based MRI of reward processing, inhibitory control and working memory. Results Among the 7,994 unrelated children (3,757 females [47.0%]), those will lifetime suicidality based on children (n=684 [8.6%]; 276 females [40.4%]), caregiver (n=654 [8.2%]; 233 females [35.6%]) or concordant reports (n=198 [2.5%]; 67 females [33.8%]), presented higher levels of social adversity and psychopathology on themselves and their caregivers compared to never-suicidal children (n=6,854 [85.7%]; 3,315 females [48.3%]). A wide range of brain areas was associated with suicidality, but only one test (0.06%) survived statistical correction: children with caregiver-reported suicidality had a thinner left bank of the superior temporal sulcus compared to never-suicidal children (ES=-0.17, 95%CI -0.26, -0.08, p FDR =0.019). Based on the prespecified bounds of |0.15|, ∼48% of the group mean differences for child-reported suicidality comparisons and a ∼22% for parent-reported suicidality comparisons were considered equivalent. All observed ES were relatively small ( d ≤|0.20|) and with low predictive value (AUPRC≤0.10). Conclusion and Relevance Using commonly-applied neuroimaging measures, we were unable to find a discrete brain signature related to suicidality in youth. There is a great need for improved approaches to the neurobiology 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 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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.326
Teacher spread0.287 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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