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Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

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.

SUBMITTER: Tenke CE

PROVIDER: S-EPMC5181116 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

Tenke Craig E CE Kayser Jürgen J Pechtel Pia P Webb Christian A CA Dillon Daniel G DG Goer Franziska F Murray Laura L Deldin Patricia P Kurian Benji T BT McGrath Patrick J PJ Parsey Ramin R Trivedi Madhukar M Fava Maurizio M Weissman Myrna M MM McInnis Melvin M Abraham Karen K E Alvarenga Jorge J Alschuler Daniel M DM Cooper Crystal C Pizzagalli Diego A DA Bruder Gerard E GE

Psychophysiology 20170101 1

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 elect ...[more]

PMID: 28000259

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Project description:BackgroundAuditory steady-state response (ASSR) paradigms have consistently demonstrated gamma band abnormalities in schizophrenia at a 40-Hz driving frequency with both electroencephalography (EEG) and magnetoencephalography (MEG). Various time-frequency measures have been used to assess the 40-Hz ASSR, including evoked power, single trial total power, phase-locking factor (PLF), and phase-locking angle (PLA). While both EEG and MEG studies have shown power and PLF ASSR measures to exhibit excellent test-retest reliability in healthy adults, the reliability of these measures in patients with schizophrenia has not been determined.MethodsASSRs were obtained by recording EEG data during presentation of repeated 20-Hz, 30-Hz and 40-Hz auditory click trains from nine schizophrenia patients (SZ) and nine healthy controls (HC) tested on two occasions. Similar ASSR data were collected from a separate group of 30 HC on two to three test occasions. A subset of these HC subjects had EEG recordings during two tasks, passively listening and actively attending to click train stimuli. Evoked power, total power, PLF, and PLA were calculated following Morlet wavelet time-frequency decomposition of EEG data and test-retest generalizability (G) coefficients were calculated for each ASSR condition, time-frequency measure, and subject group.ResultsG-coefficients ranged from good to excellent (> 0.6) for most 40-Hz time-frequency measures and participant groups, whereas 20-Hz G-coefficients were much more variable. Importantly, test-retest reliability was excellent for the various 40-Hz ASSR measures in SZ, similar to reliabilities in HC. Active attention to click train stimuli modestly reduced G-coefficients in HC relative to the passive listening condition.DiscussionThe excellent test-retest reliability of 40-Hz ASSR measures replicates previous EEG and MEG studies. PLA, a relatively new time-frequency measure, was shown for the first time to have excellent reliability, comparable to power and PLF measures. Excellent reliability of 40 Hz ASSR measures in SZ supports their use in clinical trials and longitudinal observational studies.

Project description:Functional connectivity (FC) has become a leading method for resting-state functional magnetic resonance imaging (rs-fMRI) analysis. However, the majority of the previous studies utilized pairwise, temporal synchronization-based FC. Recently, high-order FC (HOFC) methods were proposed with the idea of computing "correlation of correlations" to capture high-level, more complex associations among the brain regions. There are two types of HOFC. The first type is topographical profile similarity-based HOFC (tHOFC) and its variant, associated HOFC (aHOFC), for capturing different levels of HOFC. Instead of measuring the similarity of the original rs-fMRI signals with the traditional FC (low-order FC, or LOFC), tHOFC measures the similarity of LOFC profiles (i.e., a set of LOFC values between a region and all other regions) between each pair of brain regions. The second type is dynamics-based HOFC (dHOFC) which defines the quadruple relationship among every four brain regions by first calculating two pairwise dynamic LOFC "time series" and then measuring their temporal synchronization (i.e., temporal correlation of the LOFC fluctuations, not the BOLD fluctuations). Applications have shown the superiority of HOFC in both disease biomarker detection and individualized diagnosis than LOFC. However, no study has been carried out for the assessment of test-retest reliability of different HOFC metrics. In this paper, we systematically evaluate the reliability of the two types of HOFC methods using test-retest rs-fMRI data from 25 (12 females, age 24.48 ± 2.55 years) young healthy adults with seven repeated scans (with interval = 3-8 days). We found that all HOFC metrics have satisfactory reliability, specifically (1) fair-to-good for tHOFC and aHOFC, and (2) fair-to-moderate for dHOFC with relatively strong connectivity strength. We further give an in-depth analysis of the biological meanings of each HOFC metric and highlight their differences compared to the LOFC from the aspects of cross-level information exchanges, within-/between-network connectivity, and modulatory connectivity. In addition, how the dynamic analysis parameter (i.e., sliding window length) affects dHOFC reliability is also investigated. Our study reveals unique functional associations characterized by the HOFC metrics. Guidance and recommendations for future applications and clinical research using HOFC are provided. This study has made a further step toward unveiling more complex human brain connectome.

Dataset Information

Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

Publications

Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

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