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Exploring Brain Network Dynamics in Suicide Attempt Survivors Using EEG Microstate Analysis.

Qin Liu¹, Xingqu Wu², Peng Fang³

¹Department of Nursing, Air Force Medical University (The Fourth Military Medical University), Xi'an, Shaanxi, China.

Brain Topography

|December 18, 2025

Summary

This summary is machine-generated.

Brain network dynamics differ between suicide attempt survivors and those with suicidal ideation. Microstate analysis of EEG data suggests distinct neural patterns may serve as biomarkers for suicidal behavior.

Keywords:

EEG microstate Large-scale brain network Suicide attempt survivors

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Area of Science:

Neuroscience
Psychiatry
Brain Network Analysis

Background:

Neural network connectivity deviations are observed in individuals with suicidal ideation (SI).
Understanding the specific brain network dynamics in suicide attempt (SA) survivors is crucial.

Purpose of the Study:

To explore and differentiate the neural network dynamics between SA survivors and individuals with SI.
To investigate potential neurobiomarkers for distinguishing suicidal behavior.

Main Methods:

Recruited 31 SA survivors, 33 individuals with SI, and 33 normal controls (NP).
Collected 64-channel resting-state EEG recordings.
Conducted microstate analysis on EEG data to assess brain network dynamics.

Main Results:

Both SA survivors and SI groups showed increased coverage and occurrence of microstates A and B compared to NP.
SA survivors exhibited distinct microstate patterns (increased D and E occurrence/coverage, shorter C, D, E durations) compared to the SI group.
Higher suicide risk correlated with increased occurrence and coverage of microstates D and E.

Conclusions:

Microstate dynamics in SA survivors are significantly different from those with SI.
These distinct microstate patterns may serve as potential neurobiomarkers for differentiating suicidal behavior and SI.
Further research with longitudinal designs is needed to confirm predictive capacity.