Dataset Information

Effects of methylphenidate on the ERP amplitude in youth with ADHD: A double-blind placebo-controlled cross-over EEG study.

ABSTRACT: Methylphenidate (MPH) is a first line drug for attention-deficit/hyperactivity disorder (ADHD), yet the neuronal mechanisms underlying the condition and the treatment are still not fully understood. Previous EEG studies on the effect of MPH in ADHD found changes in evoked response potential (ERP) components that were inconsistent between studies. These inconsistencies highlight the need for a well-designed study which includes multiple baseline sessions and controls for possible fatigue, learning effects and between-days variability. To this end, we employ a double-blind placebo-controlled cross-over study and explore the effect of MPH on the ERP response of subjects with ADHD during a Go/No-Go cognitive task. Our ERP analysis revealed significant differences in ADHD subjects between the placebo and MPH conditions in the frontal-parietal region at 250ms-400ms post stimulus (P3). Additionally, a decrease in the late 650ms-800ms ERP component (LC) is observed in frontal electrodes of ADHD subjects compared to controls. The standard deviation of response time of ADHD subjects was significantly smaller in the MPH condition compared to placebo and correlated with the increased P3 ERP response in the frontoparietal electrodes. We suggest that mental fatigue plays a role in the decrease of the P3 response in the placebo condition compared to pre-placebo, a phenomenon that is significant in ADHD subjects but not in controls, and which is interestingly rectified by MPH.

SUBMITTER: Rubinson M

PROVIDER: S-EPMC6544236 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Effects of methylphenidate on the ERP amplitude in youth with ADHD: A double-blind placebo-controlled cross-over EEG study.

Rubinson Mica M Horowitz Itai I Naim-Feil Jodie J Gothelf Doron D Levit-Binnun Nava N Moses Elisha E

PloS one 20190531 5

Methylphenidate (MPH) is a first line drug for attention-deficit/hyperactivity disorder (ADHD), yet the neuronal mechanisms underlying the condition and the treatment are still not fully understood. Previous EEG studies on the effect of MPH in ADHD found changes in evoked response potential (ERP) components that were inconsistent between studies. These inconsistencies highlight the need for a well-designed study which includes multiple baseline sessions and controls for possible fatigue, learnin ...[more]

PMID: 31150439

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Project description:Attention deficit hyperactivity disorder (ADHD) is a frequent neurodevelopmental disorder that often persists into adulthood. Methylphenidate (MPH) is the first-line treatment for ADHD; however, despite its wide usage, little is known about its neurometabolic effects. Until now, no randomized and blinded clinical trials have been conducted addressing the neurometabolic signals of MPH administration in adults with ADHD. In the current study, the authors investigated how MPH intake and group psychotherapy (GPT) influence brain neurometabolism over the course of three months. The authors hypothesized a decrease in the anterior cingulate cortex (ACC) glutamate concentration following MPH administration. This study was part of a double-blind multicenter trial (Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS)) investigating the effects of MPH and GPT in patients with adult ADHD. Using single-voxel magnetic resonance spectroscopy (MRS) of the pregenual ACC and the left cerebellar hemisphere (CHL), we investigated the concentration of glutamate plus glutamine (Glx), N-acetyl-aspartate, creatine, total choline containing compounds, and myo-inositol in patients before and after 12 weeks of treatment. Neither MPH nor GPT significantly influenced the Glx concentration or any of the other metabolite concentrations in the ACC and CHL after 12 weeks. Therefore, contrary to the hypothesis, no change in the prefrontal Glx signal was detected after MPH treatment. Given that MRS does not differentiate between glutamate in the synaptic cleft and in neuronal tissue, MPH-induced down-regulation of glutamatergic neurotransmission in the ACC might only affect the concentration of glutamate in the synaptic cleft, while the general availability of glutamate in the respective neuronal tissue might be unaffected by MPH intake. The observed lack of any MPH-induced normalization in metabolite concentrations is less surprising, considering that the baseline sample did not significantly differ from a healthy control group. Future studies of other regions, such as the basal ganglia, and the use of novel methods, such as whole brain MRS and multimodal imaging approaches, are necessary.

Project description:ObjectiveSleep problems is the most common side effect of methylphenidate (MPH) treatment in ADHD youth and carry potential to negatively impact long-term self-regulatory functioning. This study aimed to examine whether applying machine learning approaches to pre-treatment demographic, clinical questionnaire, environmental, neuropsychological, genetic, and neuroimaging features can predict sleep side effects following MPH administration.MethodThe present study included 83 ADHD subjects as a training dataset. The participants were enrolled in an 8-week, open-label trial of MPH. The Barkley Stimulant Side Effects Rating Scale was used to determine the presence/absence of sleep problems at the 2nd week of treatment. Prediction of sleep side effects were performed with step-wise addition of variables measured at baseline: demographics (age, gender, IQ, height/weight) and clinical variables (ADHD Rating Scale-IV (ADHD-RS) and Disruptive Behavior Disorder rating scale) at stage 1, neuropsychological test (continuous performance test (CPT), Stroop color word test) and genetic/environmental variables (dopamine and norepinephrine receptor gene (DAT1, DRD4, ADRA2A, and SLC6A2) polymorphisms, blood lead, and urine cotinine level) at stage 2, and structural connectivities of frontostriatal circuits at stage 3. Three different machine learning algorithms ((Logistic Ridge Regression (LR), support vector machine (SVM), J48) were used for data analysis. Robustness of classifier model was validated in the independent dataset of 36 ADHD subjects.ResultsClassification accuracy of LR was 95.5% (area under receiver operating characteristic curve (AUC) 0.99), followed by SVM (91.0%, AUC 0.85) and J48 (90.0%, AUC 0.87) at stage 3 for predicting sleep problems. The inattention symptoms of ADHD-RS, CPT response time variability, the DAT1, ADRA2A DraI, and SLC6A2 A-3081T polymorphisms, and the structural connectivities between frontal and striatal brain regions were identified as the most differentiating subset of features. Validation analysis achieved accuracy of 86.1% (AUC 0.92) at stage 3 with J48.ConclusionsOur results provide preliminary support to the combination of multimodal classifier, in particular, neuroimaging features, as an informative method that can assist in predicting MPH side effects in ADHD.

Dataset Information

Effects of methylphenidate on the ERP amplitude in youth with ADHD: A double-blind placebo-controlled cross-over EEG study.

Publications

Effects of methylphenidate on the ERP amplitude in youth with ADHD: A double-blind placebo-controlled cross-over EEG study.

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