Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional Connectivity

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Adolescent major depressive disorder (MDD) is associated with abnormal brain functional connectivity (FC).
• The diagnostic utility of whole-brain FC in adolescent MDD remains uncertain.

Purpose of the Study:

• To investigate the diagnostic value of whole-brain FC in adolescent MDD.
• To explore the potential of FC as a biomarker for adolescent depression.

Main Methods:

• Resting-state fMRI data from 94 adolescents with MDD and 78 controls.
• Whole-brain functional connectivity (FC) analysis using 90 regions of interest.
• Multivariate pattern analysis (MVPA) with a linear support vector machine classifier.

Main Results:

• A classifier achieved 69.18% accuracy in distinguishing MDD patients from controls using FC features.
• Key functional connections were identified within and between large-scale brain networks.
• Top predictive nodes were primarily in the default mode, salience, auditory, and sensorimotor networks.

Conclusions:

• Altered functional network connectivity is crucial in the neurobiology of adolescent MDD.
• Specific FC patterns and high-weight brain regions show potential as complementary diagnostic markers for adolescent depression.