Predictive Value of Slow and Fast EEG Oscillations for Methylphenidate Response in ADHD

Author:

Sari Gokten Emel1,Tulay Emine Elif2ORCID,Beser Birsu3,Elagoz Yuksel Mine1,Arikan Kemal4ORCID,Tarhan Nevzat45,Metin Baris4

Affiliation:

1. Department of Child and Adolescent Psychiatry, NPIstanbul Brain Hospital, Istanbul, Turkey

2. Technology Transfer Office, Uskudar University, Istanbul, Turkey

3. Neuroscience Department, Istanbul University, Istanbul, Turkey

4. Department of Psychology, Faculty of Humanities and Social Sciences, Uskudar University, Istanbul, Turkey

5. Department of Psychiatry, NPIstanbul Brain Hospital, Istanbul, Turkey

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is characterized by symptoms of inattention and/or hyperactivity and impulsivity. In the current study, we obtained quantitative EEG (QEEG) recordings of 51 children aged between 6 and 12 years before the initiation of methylphenidate treatment. The relationship between changes in the scores of ADHD symptoms and initial QEEG features (power/power ratios values) were assessed. In addition, the children were classified as responder and nonresponder according to the ratio of their response to the medication (>25% improvement after medication). Logistic regression analyses were performed to analyze the accuracy of QEEG features for predicting responders. The findings indicate that patients with increased delta power at F8, theta power at Fz, F4, C3, Cz, T5, and gamma power at T6 and decreased beta powers at F8 and P3 showed more improvement in ADHD hyperactivity symptoms. In addition, increased delta/beta power ratio at F8 and theta/beta power ratio at F8, F3, Fz, F4, C3, Cz, P3, and T5 showed negative correlations with Conners’ score difference of hyperactivity as well. This means, those with greater theta/beta and delta/beta powers showed more improvement in hyperactivity following medication. Theta power at Cz and T5 and theta/beta power ratios at C3, Cz, and T5 have significantly classified responders and nonresponders according to the logistic binary regression analysis. The results show that slow and fast oscillations may have predictive value for treatment response in ADHD. Future studies should seek for more sensitive biomarkers.

Publisher

SAGE Publications

Subject

Neurology (clinical),Neurology,General Medicine

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