Probing Neurophysiological Processes Related to Self-Referential Processing to Predict Improvement for Depressed Adolescents Receiving Cognitive Behavioral Therapy.

Abstract

Background: Cognitive Behavior Therapy (CBT) is a gold standard approach for treating major depressive disorder (MDD) among adolescents. However, nearly half of adolescents receiving CBT do not improve. In order to personalize treatment, it is essential to identify objective markers that predict treatment responsiveness. Toward addressing this aim, this study investigated neurophysiological processes related to self-referential processing that predicted CBT response among depressed, female adolescents.

Methods: At baseline, female adolescents ages 13-18-years-old (N=80) completed a comprehensive clinical assessment, and a self-referential encoding task was administered while electroencephalogram (EEG) data were recorded. Baseline EEG data were utilized to identify oscillatory differences between healthy (HC, n=38) and depressed (MDD, n=42) adolescents. Following the baseline assessment, depressed youth received up to 12-weeks of CBT. Baseline differences in EEG oscillations between healthy and depressed youth were used to guide CBT prediction analysis. Cluster-based event-related spectral perturbation analysis (ERSP) probed theta and alpha event-related synchronization/desynchronization (ERS/ERD) response to negative and positive words.

Results: Baseline analyses showed that, relative to the healthy adolescents, depressed youth exhibited higher levels of frontal theta ERS and a greater posterior alpha ERD. Multilevel modeling identified primary neural pre-treatment predictors of treatment response: greater theta ERS in the right prefrontal cortex (PFC) after the onset of negative words and lower alpha ERD in both the right PFC and posterior cingulate cortex (PCC). ERS and ERD associations with treatment response remained significant, with baseline depressive and anxiety symptoms included as covariates in all analyses.

Conclusions: Consistent with prior research, results highlighted that relative to healthy youth, depressed adolescents are characterized by prominent theta synchronization and alpha desynchronization over PFC and PCC, respectively. Cluster-based ERSP analysis also identified key mechanisms underlying depression-related self-referential processing that predicted improved symptoms during the CBT course. Ultimately, a better characterization of the neural underpinnings of adolescent depression and its treatment may lead to more personalized interventions.