Refining EEG Biomarkers in ADHD for Diagnosis and Treatment Response Monitoring

Saturday, May 16, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
S. Loo, Psychiatry and Biobehavioral Sciences, UCLA David Geffen School of Medicine, Los Angeles, CA
Background: There is marked heterogeneity in the behavioral, cognitive, and neural presentations of children diagnosed with attention-deficit/hyperactivity disorder (ADHD).  This heterogeneity presents research and clinical challenges when trying to identify putative risk genes, define core deficits and recommend optimal treatment interventions for children with ADHD.  Electroencephalograpy (EEG) is a strong candidate biomarker due to its high heritability and strong familial clustering, diagnostic utility, and sensitivity to treatment response. In addition, the first EEG biomarker for ADHD diagnosis was recently approved by the US Food and Drug Administration (FDA).  While this diagnostic advancement may represent a milestone in general acceptance of using EEG as a quantitative assessment of brain function, further refinement of EEG biomarkers that better account for clinical heterogeneity and neurodevelopmental changes need to be developed.

Objectives: We will review the vast EEG literature in ADHD leading to the development of the FDA approved EEG biomarker as well as subsequent literature suggesting further refinement is needed. We will then present data from EEG studies of children with and without ADHD as well as EEG correlates of medication response among children with ADHD.

Methods: The sample consisted of 179 participants with ADHD and 93 non-clinical, healthy comparison children, aged 7- to 14-years old.  All children received a baseline assessment consisting of semi-structured diagnostic interviews, comprehensive neurocognitive testing and EEG recording. Children with ADHD were then randomized to one of three medication conditions: d-methylphenidate, guanfacine, or their combination. Behavior, cognitive function and EEG during resting state and cognitive activation were measured at baseline and optimal dose for each medication group. Separate analyses for EEG markers that accurately identify children with ADHD diagnosis and that are associated with treatment response were conducted.

Results: First, we tested the FDA approved EEG biomarker (i.e., theta/beta ratio; THBR) for accuracy in ADHD diagnosis. The THBR did not differ significantly between children with ADHD and healthy comparison children. ADHD subtype and psychiatric comorbidities such as disruptive behavior disorders and depression have opposing and significant mediating effects on the THBR. Next, we tested multiple EEG features measured during a working memory task for association with ADHD diagnosis. This data yielded information about cortical mechanisms underlying working memory deficit and developmental course of these mechanisms in ADHD. Prediction of ADHD using multiple EEG measures was moderately high and suggested this may be a promising direction. Finally, we analyzed medication effects on EEG measures for the three medication groups and identified several markers for positive medication treatment response.     

Conclusions: The data presented suggest that multivariate EEG biomarkers may be useful indices of ADHD diagnosis, developmental course of disorder, and treatment response. The insights gained from these results may inform similar efforts in other neurodevelopmental disorders such as autism spectrum disorder (ASD).