Resting EEG Measures of Brain Arousal in a Multisite Study of Major Depression

Abstract

Several studies have found upregulated brain arousal during 15-minute EEG recordings at rest in depressed patients. However, studies based on shorter EEG recording intervals are lacking. Here we aimed to compare measures of brain arousal obtained from 2-minute EEGs at rest under eyes-closed condition in depressed patients and healthy controls in a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). We expected that depressed patients would show stable and elevated brain arousal relative to controls. Eighty-seven depressed patients and 36 healthy controls from four research sites in the United States were included in the analyses. The Vigilance Algorithm Leipzig (VIGALL) was used for the fully automatic classification of EEG-vigilance stages (indicating arousal states) of 1-second EEG segments; VIGALL-derived measures of brain arousal were calculated. We found that depressed patients scored higher on arousal stability ( Z = -2.163, P = .015) and A stages (dominant alpha activity; P = .027) but lower on B1 stages (low-voltage non-alpha activity, P = .008) compared with healthy controls. No significant group differences were observed in Stage B2/3. In summary, we were able to demonstrate stable and elevated brain arousal during brief 2-minute recordings at rest in depressed patients. Results set the stage for examining the value of these measures for predicting clinical response to antidepressants in the entire EMBARC sample and evaluating whether an upregulated brain arousal is particularly characteristic for responders to antidepressants.

Keywords: EEG-vigilance; EMBARC; VIGALL 2.1; brain arousal regulation; electroencephalogram; major depressive disorder.

Conflict of interest statement

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: In the last three years, the authors report the following financial disclosures, for activities unrelated to the current research: Dr. Hegerl: Dr. Hegerl was an advisory board member for Lilly, Lundbeck, Servier, Takeda and Otsuka; a consultant for Bayer and Nycomed; and a speaker for Bristol-Myers Squibb, Medice Arzneimittel, Novartis, and Roche. Dr. Fava: Dr. Fava reports the following lifetime disclosures: http://mghcme.org/faculty/faculty-detail/maurizio_fava. Dr. McInnis: Dr. McInnis received funding from the NIMH and consulting fees from Janssen and Otsuka Pharmaceuticals. Dr. Trivedi: Dr. Trivedi reports the following lifetime disclosures: research support from the Agency for Healthcare Research and Quality, Cyberonics Inc., National Alliance for Research in Schizophrenia and Depression, National Institute of Mental Health, National Institute on Drug Abuse, National Institute of Diabetes and Digestive and Kidney Diseases, Johnson & Johnson, and consulting and speaker fees from Abbott Laboratories Inc., Akzo (Organon Pharmaceuticals Inc.), Allergan Sales LLC, Alkermes, AstraZeneca, Axon Advisors, Brintellix, Bristol-Myers Squibb Company, Cephalon Inc., Cerecor, Eli Lilly & Company, Evotec, Fabre Kramer Pharmaceuticals Inc., Forest Pharmaceuticals, GlaxoSmithKline, Health Research Associates, Johnson & Johnson, Lundbeck, MedAvante Medscape, Medtronic, Merck, Mitsubishi Tanabe Pharma Development America Inc., MSI Methylation Sciences Inc., Nestle Health Science-PamLab Inc., Naurex, Neuronetics, One Carbon Therapeutics Ltd., Otsuka Pharmaceuticals, Pamlab, Parke-Davis Pharmaceuticals Inc., Pfizer Inc., PgxHealth, Phoenix Marketing Solutions, Rexahn Pharmaceuticals, Ridge Diagnostics, Roche Products Ltd., Sepracor, SHIRE Development, Sierra, SK Life and Science, Sunovion, Takeda, Tal Medical/Puretech Venture, Targacept, Transcept, VantagePoint, Vivus, and Wyeth-Ayerst Laboratories. Dr. Weissman: funding from NIMH, the National Alliance for Research on Schizophrenia and Depression (NARSAD), the Sackler Foundation, and the Templeton Foundation; royalties from the Oxford University Press, Perseus Press, the American Psychiatric Association Press, and MultiHealth Systems. Dr. Pizzagalli: funding from NIMH and the Dana Foundation; consulting fees from Akili Interactive Labs, BlackThorn Therapeutics, Boehreinger Ingelheim, Pfizer, and Posit Science. Dr. Kayser: funding from NIMH and the John F. Templeton foundation. All other authors report no financial conflicts.

Figures

Figure 1.

Flowcharts of the preprocessing pipeline (a) for continuous EEG of the EMBARC study, reproduced with permission from publisher and (b) preceding the EEG-vigilance staging with VIGALL 2.1.

Figure 2.

Decision criteria of the Vigilance Algorithm Leipzig (VIGALL) used in the current study. Classification of vigilance stages is based on power in four regions of interest (ROIs; frontal, parietal, temporal, and occipital lobes). For these ROIs, current density power is calculated using low-resolution electromagnetic tomography (LORETA) for the alpha and delta/theta band. Prior to classification, alpha frequency and amplitude level is individually adapted, based on a 10-second epoch with prominent alpha activity (default range 7.5–12.5 Hz). For the respective epoch, the individual center of gravity for the alpha frequency and mean power in the occipital ROI are calculated. Based on this frequency, the alpha range (individual frequency ±2 Hz) is determined. Occipital alpha power is used to determine the individual alpha threshold as cutoff value in the classification of A and B2/3 stages.

Figure 3.

Time course of scored EEG-vigilance over 120 consecutive 1-second segments in (a) a patient with major depressive disorder and (b) a healthy control subject. To obtain EEG-vigilance scores, consecutive 1-second EEG segments were classified using the Vigilance Algorithm Leipzig into five different EEG-vigilance stages: A1, A2, A3, B1, B2/3 (based on frequency bands and source localization with LORETA). Each staged segment was assigned a number ranging from 6 (highest Stage A1) to 2 (lowest Stage B2/3).

Figure 4.

Time course of (a) mean EEG-vigilance of eight 15-second intervals and (b) frequency distribution of the arousal stability scores in depressed patients (n = 87) and healthy controls (n = 36). Error bars indicate ± 1SE.