Electroencephalographic Biomarkers for Major Depressive Disorder and Alcohol Use Disorder

Major Depressive Disorder (MDD) and Alcohol Use Disorder (AUD) are common neurological disorders that significantly impact physical health, family life, and work. Accurate diagnosis is essential for early intervention and treatment. However, conventional DSM-based diagnosis is subjective and susceptible to errors due to patient dishonesty or memory lapses. This study introduces a more reliable and objective diagnostic approach using effective connectivity (EC) from EEG recordings of 30 healthy controls, 30 MDD, and 30 AUD patients. EC, calculated via partial directed coherence, was used as input for an SVM model, achieving a peak classification accuracy of 95.3%, with perfect accuracy in the beta and gamma rhythms. These findings underscore EC’s potential as biomarkers for more accurate diagnosis and early intervention in neurological disorders.