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Updated: May 24, 2026

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
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Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis.

Ling-Li Zeng1, Hui Shen, Li Liu

  • 1College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, People's Republic of China.

Brain : a Journal of Neurology
|March 16, 2012
PubMed
Summary
This summary is machine-generated.

Resting-state functional connectivity MRI accurately identified major depressive disorder patients with 94.3% accuracy. Key brain network differences highlight potential biomarkers for diagnosing depression.

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Major depressive disorder (MDD) is associated with altered brain activity.
  • Resting-state functional connectivity (rs-fMRI) magnetic resonance imaging (MRI) reveals group differences in brain networks between MDD patients and healthy controls.

Purpose of the Study:

  • To investigate whole-brain rs-fMRI connectivity patterns in MDD patients.
  • To test the feasibility of identifying MDD individuals from healthy controls using rs-fMRI data.

Main Methods:

  • Multivariate pattern analysis (MVPA) was used to classify 24 MDD patients and 29 healthy controls.
  • Leave-one-out cross-validation and permutation tests assessed classifier performance.

Main Results:

  • A classification accuracy of 94.3% was achieved (P < 0.0001), with 100% identification of MDD patients.
  • Discriminative functional connections were predominantly within/across default mode, affective, visual networks, and the cerebellum.
  • Key regions with high discriminative power included the amygdala, anterior cingulate cortex, parahippocampal gyrus, and hippocampus.

Conclusions:

  • Altered resting-state networks in MDD contribute to emotional and cognitive disturbances.
  • Specific brain regions play crucial roles in the pathophysiology of major depression.
  • Whole-brain rs-fMRI shows potential as an effective biomarker for clinical diagnosis of MDD.