Demonstrating test‐retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response. (January 2017) - Tenke, Craig E.; Kayser, Jürgen; Pechtel, Pia; Webb, Christian A.; Dillon, Daniel G.; Goer, Franziska; Murray, Laura; Deldin, Patricia; Kurian, Benji T.; McGrath, Patrick J.; Parsey, Ramin; Trivedi, Madhukar; et al.
Abstract: Growing evidence suggests that loudness dependency of auditory evoked potentials (LDAEP) and resting EEG alpha and theta may be biological markers for predicting response to antidepressants. In spite of this promise, little is known about the joint reliability of these markers, and thus their clinical applicability. New standardized procedures were developed to improve the compatibility of data acquired with different EEG platforms, and used to examine test‐retest reliability for the three electrophysiological measures selected for a multisite project—Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). Thirty‐nine healthy controls across four clinical research sites were tested in two sessions separated by about 1 week. Resting EEG (eyes‐open and eyes‐closed conditions) was recorded and LDAEP measured using binaural tones (1000 Hz, 40 ms) at five intensities (60–100 dB SPL). Principal components analysis of current source density waveforms reduced volume conduction and provided reference‐free measures of resting EEG alpha and N1 dipole activity to tones from auditory cortex. Low‐resolution electromagnetic tomography (LORETA) extracted resting theta current density measures corresponding to rostral anterior cingulate (rACC), which has been implicated in treatment response. There were no significant differences in posterior alpha, N1 dipole, or rACC theta across sessions. Test‐retest reliability was .84 for alpha, .87 for N1 dipole, and .70 for theta rACC current density. The demonstration of good‐to‐excellent reliability for these measures provides a template for future EEG/ERP studies from multiple testing sites, and an important step for evaluating them as biomarkers for predicting treatment response.