Differences in resting state and task-based EEG measures between patients with major depressive disorder and healthy controls

• Published in: Clinical neurophysiology Vol. 173; pp. 190 - 198
• Main Authors: Kovacevic, Natasha, Meghdadi, Amir, Berka, Chris, Saad, Ziad S., Kolb, Hartmuth C., de Boer, Peter, Furey, Maura, Miller, Silke
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.05.2025
• Subjects: Adult; Anxiety; Depression; Depressive Disorder, Major - diagnosis; Depressive Disorder, Major - physiopathology; Depressive Disorder, Major - psychology; EEG; Electroencephalogram; Electroencephalography - methods; Emotions - physiology; ERP; Facial Recognition - physiology; Female; Humans; Major depressive disorder; Male; Middle Aged; N170; Neurology; Power spectrum; Rest - physiology; Signature; Young Adult; ERP; Electroencephalogram; EEG; Signature; N170; Depression; Anxiety; Major depressive disorder; Power spectrum
• ISSN: 1388-2457; 1872-8952; 1872-8952
• DOI: 10.1016/j.clinph.2025.03.022

[Display omitted] •EEG during rest and active tasks can discriminate between depressed and healthy groups and predict symptom severity.•In attentional task, elevated P200 amplitude predicts severity of depression.•EEG signatures from different tasks indicate links with distinct facets of major depressive disorder. Assessing depression in psychiatry relies on subjective measures that may not adequately reflect the disorder’s biology. Electroencephalography offers an objective and scalable approach for gathering data with potential for characterizing major depressive disorder. We explore the potential of a combination of EEG-based neurocognitive measures for the characterization of depression. Resting state measures and electrophysiological responses during emotional faces recognition and a three-choice vigilance task, were examined in a sample of depressed patients and healthy controls. The findings revealed differences in resting state spectral power measures in the theta, alpha, and beta ranges. Relative alpha power in eyes open condition was decreased in patients and the degree of reduction was correlated with the severity of both anxiety and depressive symptoms. The N170 face component of the evoked responses to emotional faces captured depression-related emotional bias towards sad faces. The three-choice vigilance task demonstrated depression-related attentional behavioral deficits, and an increase in P200 amplitude which was also associated with greater depression severity. The three paradigms revealed distinct and complementary EEG signatures of depression. Our findings suggest the benefits of utilizing objective measures for enhancing our understanding and treatment of the disorder.