Electroencephalogram patterns in patients comorbid with major depressive disorder and anxiety symptoms: Proposing a hypothesis based on hypercortical arousal and not frontal or parietal alpha asymmetry

Background: Major depressive disorder (MDD) is often comorbid with anxiety disorders or symptoms. Brain hyperactivity, frontal alpha asymmetry (FAA), and parietal alpha asymmetry (PAA) have been considered as trait markers in patients with MDD. This study investigated the electroencephalogram (EEG) patterns among patients with MDD comorbid with anxiety symptoms. Methods: One hundred and thirty-five patients with MDD comorbid with anxiety (MDD group) and 135 healthy controls (HC group) were analyzed. The Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) were completed, and 19 EEG channels were measured during the resting state, depressive recall and recovery tasks, and happiness recall and recovery tasks. FAA and PAA were computed by log (F4 alpha)-log (F3 alpha) and log (P4 alpha)-log (P3 alpha). Results: The FAA and PAA indices between the two groups showed no significant differences; however, compared with the HC group, the MDD group had lower total delta and theta values, and higher total beta, low beta, and high beta values in the resting state. The total beta value positively correlated with the BDI-II and BAI scores in the MDD group. Limitations: Most patients had anxious MDD and taking prescriptions, antidepressants or benzodiazepine may affect EEG patterns. Conclusion: Compared with HCs, patients with MDD comorbid with anxiety had a higher beta activity in the entire brain region, supporting the role of brain hyperactivity, instead of FAA or PAA, as a trait marker in these patients. A neurofeedback protocol could be developed in future based on the brain hyperactivity findings.

Automated summary

This study investigated EEG patterns among patients with MDD comorbid with anxiety symptoms. Results showed that the MDD group had higher beta activity in the entire brain region, supporting the role of brain hyperactivity as a trait marker in these patients. The findings suggest the potential development of a neurofeedback protocol based on brain hyperactivity.