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Parsing heterogeneity in attention-deficit hyperactivity disorder using EEG-based subgroups. | LitMetric

Parsing heterogeneity in attention-deficit hyperactivity disorder using EEG-based subgroups.

J Child Psychol Psychiatry

Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.

Published: March 2018

AI Article Synopsis

  • The study analyzed resting EEG profiles in 781 children (620 with ADHD, 161 control) to identify subgroups based on brain activity.
  • A five-class solution showed that four classes displayed elevated spectral power related to different behaviors and cognitive abilities.
  • The findings suggest that EEG profiles are diverse and may serve as better markers for ADHD treatment response rather than definitive diagnosis.

Article Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous condition for which multiple efforts to characterize brain state differences are underway. The objective of this study was to identify distinct subgroups of resting electroencephalography (EEG) profiles among children with and without ADHD and subsequently provide extensive clinical characterization of the subgroups.

Methods: Latent class analysis was used with resting state EEG recorded from a large sample of 781 children with and without ADHD (N = 620 ADHD, N = 161 Control), aged 6-18 years old. Behavioral and cognitive characteristics of the latent classes were derived from semistructured diagnostic interviews, parent completed behavior rating scales, and cognitive test performance.

Results: A five-class solution was the best fit for the data, of which four classes had a defining spectral power elevation. The distribution of ADHD and control subjects was similar across classes suggesting there is no one resting state EEG profile for children with or without ADHD. Specific latent classes demonstrated distinct behavioral and cognitive profiles. Those with elevated slow-wave activity (i.e. delta and theta band) had higher levels of externalizing behaviors and cognitive deficits. Latent subgroups with elevated alpha and beta power had higher levels of internalizing behaviors, emotion dysregulation, and intact cognitive functioning.

Conclusions: There is population-level heterogeneity in resting state EEG subgroups, which are associated with distinct behavioral and cognitive profiles. EEG measures may be more useful biomarkers of ADHD outcome or treatment response rather than diagnosis.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5812789PMC
http://dx.doi.org/10.1111/jcpp.12814DOI Listing

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