Craig E Tenke1, Jürgen Kayser2, Jorge E Alvarenga3, Karen S Abraham3, Virginia Warner4, Ardesheer Talati5, Myrna M Weissman5, Gerard E Bruder6. 1. Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians & Surgeons, New York, NY, USA. 2. Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians & Surgeons, New York, NY, USA. Electronic address: kayserj@nyspi.columbia.edu. 3. Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA. 4. Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA; Mailman School of Public Health, Columbia University, New York, NY, USA. 5. Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians & Surgeons, New York, NY, USA; Mailman School of Public Health, Columbia University, New York, NY, USA. 6. Division of Cognitive Neuroscience, New York State Psychiatric Institute, New York, NY, USA; Department of Psychiatry, Columbia University College of Physicians & Surgeons, New York, NY, USA.
Abstract
OBJECTIVE: We previously identified posterior EEG alpha as a potential biomarker for antidepressant treatment response. To meet the definition of a trait biomarker or endophenotype, it should be independent of the course of depression. Accordingly, this report evaluated the temporal stability of posterior EEG alpha at rest. METHODS: Resting EEG was recorded from 70 participants (29 male; 46 adults), during testing sessions separated by 12 ± 1.1 years. EEG alpha was identified, separated and quantified using reference-free methods that combine current source density (CSD) with principal components analysis (PCA). Measures of overall (eyes closed-plus-open) and net (eyes closed-minus-open) posterior alpha amplitude and asymmetry were compared across testing sessions. RESULTS: Overall alpha was stable for the full sample (Spearman-Brown [rSB] = .834, Pearson's r = .718), and showed excellent reliability for adults (rSB = .918; r = 0.848). Net alpha showed acceptable reliability for adults (rSB = .750; r = .600). Hemispheric asymmetries (right-minus-left hemisphere) of posterior overall alpha showed significant correlations, but revealed acceptable reliability only for adults (rSB = .728; r = .573). Findings were highly comparable between 29 male and 41 female participants. CONCLUSIONS: Overall posterior EEG alpha amplitude is reliable over long time intervals in adults. SIGNIFICANCE: The temporal stability of posterior EEG alpha oscillations at rest over long time intervals is indicative of an individual trait.
OBJECTIVE: We previously identified posterior EEG alpha as a potential biomarker for antidepressant treatment response. To meet the definition of a trait biomarker or endophenotype, it should be independent of the course of depression. Accordingly, this report evaluated the temporal stability of posterior EEG alpha at rest. METHODS: Resting EEG was recorded from 70 participants (29 male; 46 adults), during testing sessions separated by 12 ± 1.1 years. EEG alpha was identified, separated and quantified using reference-free methods that combine current source density (CSD) with principal components analysis (PCA). Measures of overall (eyes closed-plus-open) and net (eyes closed-minus-open) posterior alpha amplitude and asymmetry were compared across testing sessions. RESULTS: Overall alpha was stable for the full sample (Spearman-Brown [rSB] = .834, Pearson's r = .718), and showed excellent reliability for adults (rSB = .918; r = 0.848). Net alpha showed acceptable reliability for adults (rSB = .750; r = .600). Hemispheric asymmetries (right-minus-left hemisphere) of posterior overall alpha showed significant correlations, but revealed acceptable reliability only for adults (rSB = .728; r = .573). Findings were highly comparable between 29 male and 41 female participants. CONCLUSIONS: Overall posterior EEG alpha amplitude is reliable over long time intervals in adults. SIGNIFICANCE: The temporal stability of posterior EEG alpha oscillations at rest over long time intervals is indicative of an individual trait.
Authors: Gerard E Bruder; James P Sedoruk; Jonathan W Stewart; Patrick J McGrath; Frederic M Quitkin; Craig E Tenke Journal: Biol Psychiatry Date: 2007-12-03 Impact factor: 13.382
Authors: Xuejun Hao; Ardesheer Talati; Stewart A Shankman; Jun Liu; Jurgen Kaiser; Craig E Tenke; Virginia Warner; David Semanek; Priya J Wickramaratne; Myrna M Weissman; Jonathan Posner Journal: Biol Psychiatry Cogn Neurosci Neuroimaging Date: 2017-10
Authors: Craig E Tenke; Jürgen Kayser; Connie Svob; Lisa Miller; Jorge E Alvarenga; Karen Abraham; Virginia Warner; Priya Wickramaratne; Myrna M Weissman; Gerard E Bruder Journal: Biol Psychol Date: 2017-01-22 Impact factor: 3.251
Authors: Jürgen Kayser; Craig E Tenke; Connie Svob; Marc J Gameroff; Lisa Miller; Jamie Skipper; Virginia Warner; Priya Wickramaratne; Myrna M Weissman Journal: Front Hum Neurosci Date: 2019-12-17 Impact factor: 3.169
Authors: Akina Umemoto; Lidia Y X Panier; Sally L Cole; Jürgen Kayser; Diego A Pizzagalli; Randy P Auerbach Journal: J Psychiatr Res Date: 2021-07-08 Impact factor: 5.250