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Brain Imaging

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Related Experiment Video

Updated: May 6, 2026

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

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Mapping Intersubject Variability in Functional Connectivity in Gray and White Matter to Predict Suicide Risk Among

Wanying Jing¹, Lei Yang², Yuting Guo³

¹Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China (W.J., K.C., F.D., Y.S., H.X., H.M., T.C., N.M.).

Academic Radiology

|August 8, 2025

Summary

Intersubject variability in functional connectivity (IVFC) of gray matter and white matter effectively predicts suicide risk in major depressive disorder (MDD). This finding offers a novel approach for identifying individuals with MDD who may be at higher risk for suicidal behaviors.

Keywords:

Functional Connectivity Gray Matter Intersubject Variability Machine Learning Major Depressive Disorder White Matter

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Area of Science:

Neuroscience
Psychiatry
Medical Imaging

Background:

Suicide is a severe complication of major depressive disorder (MDD).
Predicting suicidal behavior is critical for reducing suicide rates.
Previous studies linked gray matter (GM) and white matter (WM) intersubject variability in functional connectivity (IVFC) to suicide rates in MDD patients.

Purpose of the Study:

To systematically investigate the predictive efficacy of GM-WM IVFC for assessing suicide risk in individuals with MDD.
To evaluate the potential of IVFC as a biomarker for suicidal ideation (SI) and suicide attempt (SA).

Main Methods:

The study included 178 MDD patients (18 with SI, 23 with SA, 51 non-suicidal [NS]) and 173 healthy controls (HCs).
IVFC values were calculated and filtered using t-test and LASSO.
Support vector machine (SVM) and eXtreme Gradient Boosting (XGBoost) models were used to predict SI and SA categories by fusing GM and WM IVFC values.

Main Results:

IVFC demonstrated excellent predictive capabilities for SI (AUC: SVM = 0.951, XGBoost = 0.917) and SA (AUC: SVM = 0.956, XGBoost = 0.959).
Fused gray matter-white matter IVFC (GM-WM IVFC) achieved the highest predictive accuracy.
Significant differences in IVFC were observed among the SI, SA, and NS groups.

Conclusions:

GM-WM IVFC possesses substantial predictive power for suicide risk in individuals with MDD.
This finding highlights the potential of IVFC as a neuroimaging biomarker for suicide risk assessment in MDD.