Literature DB >> 22569197

The neurobiology of the EEG biomarker as a predictor of treatment response in depression.

Anusha Baskaran1, Roumen Milev, Roger S McIntyre.   

Abstract

The management of depression remains a constant challenge in clinical practice. This is largely due to the fact that initial treatments frequently do not lead to remission and recovery. The current treatment approach involves lengthy trial-and-error periods. It would be beneficial to have early reliable predictors to determine whether patients will respond to treatment or not. Electroencephalography (EEG) derived biomarkers namely change in the activity of EEG frequency bands, hemispheric alpha asymmetry, theta cordance, the antidepressant treatment response index (ATR) and evoked potentials have all been shown to predict response to a variety of antidepressant medications. However, the neurobiology in support of this association has been largely unexplored. In this review, we discuss biological mechanisms for each EEG derived biomarker predictive of treatment response. Validating such biomarkers will not only greatly aid clinicians in selecting antidepressant treatment for individual patients but will also provide a critical step in drug discovery.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22569197     DOI: 10.1016/j.neuropharm.2012.04.021

Source DB:  PubMed          Journal:  Neuropharmacology        ISSN: 0028-3908            Impact factor:   5.250


  36 in total

1.  An Electrophysiological Biomarker That May Predict Treatment Response to ECT.

Authors:  Katherine W Scangos; Richard D Weiner; Edward C Coffey; Andrew D Krystal
Journal:  J ECT       Date:  2019-06       Impact factor: 3.635

2.  Sex differences in equiprobable auditory Go/NoGo task: effects on N2 and P3.

Authors:  Sigita Melynyte; Osvaldas Ruksenas; Inga Griskova-Bulanova
Journal:  Exp Brain Res       Date:  2017-03-03       Impact factor: 1.972

3.  A study of N-methyl-D-aspartate receptor gene (GRIN2B) variants as predictors of treatment-resistant major depression.

Authors:  Chen Zhang; Zezhi Li; Zhiguo Wu; Jun Chen; Zuowei Wang; Daihui Peng; Wu Hong; Chengmei Yuan; Zhen Wang; Shunying Yu; Yifeng Xu; Lin Xu; Zeping Xiao; Yiru Fang
Journal:  Psychopharmacology (Berl)       Date:  2013-10-11       Impact factor: 4.530

4.  Pre-frontal control of closed-loop limbic neurostimulation by rodents using a brain-computer interface.

Authors:  Alik S Widge; Chet T Moritz
Journal:  J Neural Eng       Date:  2014-03-10       Impact factor: 5.379

5.  Frontal EEG Asymmetry as a Promising Marker of Depression Vulnerability: Summary and Methodological Considerations.

Authors:  John J B Allen; Samantha J Reznik
Journal:  Curr Opin Psychol       Date:  2015-01-02

Review 6.  Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years.

Authors:  G Voegeli; M L Cléry-Melin; N Ramoz; P Gorwood
Journal:  Drugs       Date:  2017-12       Impact factor: 9.546

7.  Predicting treatment outcome in depression: an introduction into current concepts and challenges.

Authors:  Nicolas Rost; Elisabeth B Binder; Tanja M Brückl
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-05-19       Impact factor: 5.270

Review 8.  Oscillatory serotonin function in depression.

Authors:  Ronald M Salomon; Ronald L Cowan
Journal:  Synapse       Date:  2013-05-21       Impact factor: 2.562

9.  Neurophysiological pharmacodynamic measures of groups and individuals extended from simple cognitive tasks to more "lifelike" activities.

Authors:  Alan Gevins; Cynthia S Chan; An Jiang; Lita Sam-Vargas
Journal:  Clin Neurophysiol       Date:  2012-11-26       Impact factor: 3.708

Review 10.  Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review.

Authors:  Blake Anthony Hickey; Taryn Chalmers; Phillip Newton; Chin-Teng Lin; David Sibbritt; Craig S McLachlan; Roderick Clifton-Bligh; John Morley; Sara Lal
Journal:  Sensors (Basel)       Date:  2021-05-16       Impact factor: 3.576

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