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The comparative effectiveness of electroencephalographic indices in predicting response to escitalopram therapy in depression: A pilot study

Abstract

BACKGROUND: This study aims to compare the effectiveness of EEG frequency band activity including interhemispheric asymmetry and prefrontal theta cordance in predicting response to escitalopram therapy at 8-weeks post-treatment, in a multi-site initiative. METHODS: Resting state 64-channel EEG data were recorded from 44 patients with a diagnosis of major depressive disorder (MDD) as part of a larger, multisite discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). Clinical response was measured at 8-weeks post-treatment as change from baseline Montgomery-Asberg Depression Rating Scale (MADRS) score of 50% or more. EEG measures were analyzed at (1) pre-treatment baseline (2) 2 weeks post-treatment and (3) as an ''early change" variable defined as change in EEG from baseline to 2 weeks post-treatment. RESULTS: At baseline, treatment responders showed elevated absolute alpha power in the left hemisphere while non-responders showed the opposite. Responders further exhibited a cortical asymmetry in the parietal region. Groups also differed in pre-treatment relative delta power with responders showing greater power in the right hemisphere over the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to the right and the opposite was noted for non-responders. A reverse pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reductions in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance. CONCLUSIONS: Hemispheric asymmetries in the alpha and delta bands at baseline and at 2 weeks post-treatment have moderately strong predictive utility in predicting response to antidepressant treatment.

Authors

Baskaran A; Farzan F; Milev R; Brenner CA; Alturi S; McAndrews MP; Blier P; Evans K; Foster JA; Frey BN

Journal

Journal of Affective Disorders, Vol. 227, , pp. 542–549

Publisher

Elsevier

Publication Date

February 1, 2018

DOI

10.1016/j.jad.2017.10.028

ISSN

0165-0327

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