Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity
Ezra E. Smith1, Craig E. Tenke1,2,3Â, Patricia J. Deldin4, Madhukar H. Trivedi5, Myrna M. Weissman1,2, Randy P. Auerbach2, Gerard E. Bruder2, Diego A. Pizzagalli6,7, Jürgen Kayser1,2,3
1Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York, USA; 2Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA; 3Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, New York, USA; 4Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA; 5Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA; 6Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA; 7Center for Depression, Anxiety & Stress Research, McLean Hospital, Belmont, Massachusetts, USA; ÂAuthor Deceased
Received 26 August 2019; revised 28 August 2019; accepted 29 August 2019; published 2 October 2019.
Abstract
Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71-channel EEG recorded from 35 healthy adults at two sessions (1-week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal-to-noise ratio, participant-level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait-multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one lowvariance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component-based identification of spectral activity (CSD/eLORETA-fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.
Key Words: current source density (CSD), EEG biomarkers, frequency PCA, source localization (LORETA), theta/ alpha oscillations, validity