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February 6, 2026CNS Neuroscience & TherapeuticsOpen Access

Altered Salience‐Default Mode Network Dynamics in Subclinical Depression: A Preclustering‐Based Co‐Activation Pattern Analysis

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Authors

BZBo ZhangZYZhinan YuFYFeifan Yan

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Overview

Functional connectivity analysis reveals dynamic network changes in subclinical depression, suggesting new neuroimaging markers.

Key Points

  • The study aims to investigate the dynamic interactions among core brain networks in individuals with subclinical depression.
  • Collected resting-state fMRI data from subjects with subclinical depression and healthy controls.
  • Developed a preclustering-based co-activation pattern method to analyze network dynamics.
  • Utilized machine learning to assess the potential of network dynamics for clinical diagnosis.
  • Individuals with subclinical depression showed decreased dwell time in the salience network (SN).
  • Increased transition frequency from SN to default mode network (DMN) correlated with depressive severity.
  • An ensemble learning model achieved 96.44% accuracy in distinguishing subclinical depression from healthy controls.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/698585bd8f7c464f23009505https://doi.org/10.1002/cns.70736
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