Literature DB >> 26901357

Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder.

Sebastian Olbrich, Rik van Dinteren, Martijn Arns.   

Abstract

Personalized medicine in psychiatry is in need of biomarkers that resemble central nervous system function at the level of neuronal activity. Electroencephalography (EEG) during sleep or resting-state conditions and event-related potentials (ERPs) have not only been used to discriminate patients from healthy subjects, but also for the prediction of treatment outcome in various psychiatric diseases, yielding information about tailored therapy approaches for an individual. This review focuses on baseline EEG markers for two psychiatric conditions, namely major depressive disorder and attention deficit hyperactivity disorder. It covers potential biomarkers from EEG sleep research and vigilance regulation, paroxysmal EEG patterns and epileptiform discharges, quantitative EEG features within the EEG main frequency bands, connectivity markers and ERP components that might help to identify favourable treatment outcome. Further, the various markers are discussed in the context of their potential clinical value and as research domain criteria, before giving an outline for future studies that are needed to pave the way to an electrophysiological biomarker-based personalized medicine.
© 2016 S. Karger AG, Basel.

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Year:  2016        PMID: 26901357     DOI: 10.1159/000437435

Source DB:  PubMed          Journal:  Neuropsychobiology        ISSN: 0302-282X            Impact factor:   2.328


  27 in total

1.  Resting-State Quantitative Electroencephalography Demonstrates Differential Connectivity in Adolescents with Major Depressive Disorder.

Authors:  Molly McVoy; Michelle E Aebi; Kenneth Loparo; Sarah Lytle; Alla Morris; Nicole Woods; Elizabeth Deyling; Curtis Tatsuoka; Farhad Kaffashi; Samden Lhatoo; Martha Sajatovic
Journal:  J Child Adolesc Psychopharmacol       Date:  2019-05-09       Impact factor: 2.576

2.  Inherent vulnerabilities in monoaminergic pathways predict the emergence of depressive impairments in an animal model of chronic epilepsy.

Authors:  Jesús-Servando Medel-Matus; Don Shin; Raman Sankar; Andrey Mazarati
Journal:  Epilepsia       Date:  2017-06-09       Impact factor: 5.864

Review 3.  Isolated epileptiform activity in children and adolescents: prevalence, relevance, and implications for treatment.

Authors:  Ronald J Swatzyna; Martijn Arns; Jay D Tarnow; Robert P Turner; Emma Barr; Erin K MacInerney; Anne M Hoffman; Nash N Boutros
Journal:  Eur Child Adolesc Psychiatry       Date:  2020-07-14       Impact factor: 4.785

4.  Identification of biotypes in Attention-Deficit/Hyperactivity Disorder, a report from a randomized, controlled trial.

Authors:  John E Leikauf; Kristi R Griffiths; Manish Saggar; David S Hong; Simon Clarke; Daryl Efron; Tracey W Tsang; Daniel F Hermens; Michael R Kohn; Leanne M Williams
Journal:  Pers Med Psychiatry       Date:  2017-03-18

5.  Task-Rate-Related Neural Dynamics Using Wireless EEG to Assist Diagnosis and Intervention Planning for Preschoolers with ADHD Exhibiting Heterogeneous Cognitive Proficiency.

Authors:  I-Chun Chen; Chia-Ling Chen; Chih-Hao Chang; Zuo-Cian Fan; Yang Chang; Cheng-Hsiu Lin; Li-Wei Ko
Journal:  J Pers Med       Date:  2022-04-30

6.  Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Authors:  Alik S Widge; M Taha Bilge; Rebecca Montana; Weilynn Chang; Carolyn I Rodriguez; Thilo Deckersbach; Linda L Carpenter; Ned H Kalin; Charles B Nemeroff
Journal:  Am J Psychiatry       Date:  2018-10-03       Impact factor: 18.112

7.  A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

Authors:  Wajid Mumtaz; Likun Xia; Mohd Azhar Mohd Yasin; Syed Saad Azhar Ali; Aamir Saeed Malik
Journal:  PLoS One       Date:  2017-02-02       Impact factor: 3.240

8.  Predicting sex from brain rhythms with deep learning.

Authors:  Michel J A M van Putten; Sebastian Olbrich; Martijn Arns
Journal:  Sci Rep       Date:  2018-02-15       Impact factor: 4.379

9.  Using EEG to Predict Clinical Response to Electroconvulsive Therapy in Patients With Major Depression: A Comprehensive Review.

Authors:  Louis Simon; Martin Blay; Filipe Galvao; Jerome Brunelin
Journal:  Front Psychiatry       Date:  2021-06-24       Impact factor: 4.157

10.  Feasibility of Repeated Assessment of Cognitive Function in Older Adults Using a Wireless, Mobile, Dry-EEG Headset and Tablet-Based Games.

Authors:  Esther C McWilliams; Florentine M Barbey; John F Dyer; Md Nurul Islam; Bernadette McGuinness; Brian Murphy; Hugh Nolan; Peter Passmore; Laura M Rueda-Delgado; Alison R Buick
Journal:  Front Psychiatry       Date:  2021-06-25       Impact factor: 4.157

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