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October 2, 2025Open Access

Diagnosis-Optimized Dynamic Feature Learning Reveals Altered Default Mode Network Connectivity in Schizophrenia

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Authors

MSMasoud SerajiCECharles A. EllisLMLiang Ma

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Overview

Observational analysis shows significant alterations in default mode network connectivity in schizophrenia, indicating potential biomarkers.

Key Points

  • Altered DMN connectivity in schizophrenia revealed through innovative dynamic feature learning.
  • Participants with schizophrenia spent significantly more time in atypical connectivity states compared to controls.
  • Analysis utilized resting-state fMRI data from two independent cohorts to assess the DMN's connectivity dynamics.
  • Findings highlight the potential of dynamic DMN features as diagnostic biomarkers that could improve clinical assessment.

Cite This Study

Seraji et al. (2025) studied this question.

synapsesocial.com/papers/68de68ea83cbc991d0a21421https://doi.org/10.1101/2025.09.30.679557
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features2024
  2. 2Network state transitions and connectivity alterations in attention deficit/hyperactivity disorder and schizophrenia: a dynamic fMRI study2026
  3. 3Task‐based default mode network connectivity predicts cognitive impairment and negative symptoms in first‐episode schizophrenia2024 · 3 citations
  4. 4Altered Salience‐Default Mode Network Dynamics in Subclinical Depression: A Preclustering‐Based Co‐Activation Pattern Analysis2026 · 1 citations
  5. 5Altered Brain Network Dynamics in Schizophrenia Patients With Predominant Negative Symptoms: A Resting‐State <scp>fMRI</scp> Study Using Co‐Activation Pattern Analysis2025 · 3 citations