alexa EEG differences between good and poor responders to methylphenidate and dexamphetamine in children with attention-deficit hyperactivity disorder.


International Journal of Sensor Networks and Data Communications

Author(s): Clarke AR, Barry RJ, McCarthy R, Selikowitz M

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Abstract OBJECTIVES: This series of studies investigated (1) electroencephalographic (EEG) differences between good and poor responders to methylphenidate, (2) EEG differences between good and poor responders to dexamphetamine, and (3) differences in the EEGs of good responders to methylphenidate versus dexamphetamine, within samples of children with the combined type of attention-deficit/hyperactivity disorder (ADHD). METHODS: Twenty good and 20 poor responders to each of methylphenidate and dexamphetamine, based on the results of a continuous performance task, and 20 age-matched control subjects, participated in this study. EEG was recorded from 21 sites during an eyes-closed resting condition and Fourier transformed to provide estimates for total power, and absolute and relative power in the delta, theta, alpha and beta bands, and for the theta/alpha and theta/beta ratios. RESULTS: EEG differences were found between the good and poor responders to each medication. Good responders to methylphenidate had EEG profiles that suggested that they were more cortically hypoaroused than poor responders. In contrast, the good responders to dexamphetamine appeared to be more maturationally lagged than the poor responders. The two good-responder groups had EEG profiles which suggested that there were two different underlying central nervous system (CNS) dysfunctions. CONCLUSIONS: Children with the combined type of ADHD do not constitute a homogeneous clinical group, as different types of CNS dysfunction are present within this population. These results also indicate the need for medication testing to be undertaken before a child is prescribed stimulant medication for ADHD.
This article was published in Clin Neurophysiol and referenced in International Journal of Sensor Networks and Data Communications

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