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Thalamic Volumes and Functional Networks Linked With Self-Regulation Dysfunction in Major Depressive Disorder.

Zhang Ling1, He Cancan1, Liu Xinyi1

  • 1Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Jiangsu Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing, Jiangsu, China.

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Self-regulation dysfunction is linked to major depressive disorder (MDD). Thalamic functional networks in MDD patients predict regulatory behaviors and depressive severity, offering potential biomarkers.

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canonical correlation analysismajor depression disordernetwork‐based statistic‐predictself‐regulationthalamic subnuclei

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Self-regulation (SR) dysfunction is a significant risk factor for major depressive disorder (MDD).
  • The precise neural mechanisms underlying SR deficits in MDD are not fully understood.

Purpose of the Study:

  • To investigate the neural substrates of self-regulation linking to major depressive disorder.
  • To explore the relationship between thalamic functional connectivity and regulatory behaviors in MDD patients.

Main Methods:

  • Recruited 68 healthy controls and 75 MDD patients for regulatory orientation assessments using the Regulatory Focus Questionnaire (RFQ) and Regulatory Mode Questionnaire (RMQ).
  • Analyzed nodal intra- and inter-network functional connectivity (FC) of thalamic subnuclei (TS) and AAL brain regions.
  • Employed Pearson's correlation, mediation analysis, Canonical Correlation Analysis (CCA), and Network-based Statistics with machine learning.

Main Results:

  • MDD patients showed significant correlations between thalamic subnuclei (TS) volume/FC and behavioral subscales, despite no group-level volumetric differences.
  • Inter-network FC between the right superior frontal gyrus and left supplementary motor area mediated the link between RFQ/RMQ subscales and depressive severity.
  • Thalamic functional subnetworks accurately predicted RFQ/RMQ subscales and psychomotor retardation in MDD individuals.

Conclusions:

  • Provided neurological evidence for the impact of self-regulation on depressive severity in MDD.
  • Identified potential biomarkers for identifying SR-based risk phenotypes in MDD.