Parsing heterogeneity in attention‐deficit hyperactivity disorder using EEG ‐based subgroups
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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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Given the complexity and heterogeneity of neurodevelopmental disorders in terms of pathophysiology, it is highly unlikely that biomarker applications based on a single parameter will be meaningful in clinical practice.
“Arguably, given the complexity and heterogeneity of neurodevelopmental disorders in terms of pathophysiology, it is highly unlikely that biomarker applications based on a single parameter will be meaningful in clinical practice 44-47 .”
From Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review (2023) · cites this paper as [45]
The Discussion says no single EEG measure differentiates children with and without ADHD, supporting the concern about a single diagnostic biomarker. But the claim extends that finding to neurodevelopmental disorders generally and to all clinical applications; the Discussion and Conclusion say EEG measures may still be useful for predicting treatment response or developmental outcomes. (LLM, conf=0.88)
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Self-citation
- Authors
- Loo, S. K., McGough, J. J., McCracken, J. T., & Smalley, S. L.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Loo, Sandra K.
- Venue
- Journal of Child Psychology and Psychiatry
- Publisher
- Wiley
- Published
- 2017-09-18
- Volume
- 59
- Issue
- 3
- Pages
- 223-231
- ISSN
- 0021-9630 (ISSN-L)
- 1469-7610
- PMC
- PMC5812789
- OpenAlex
- W2756093477
- Cited by
- 73
- References
- 31
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 6 · 2023: 6 · 2022: 11 · 2021: 7 · 2020: 9 · 2019: 10 · 2018: 7 · 2017: 1
- FWCI
- 6.06
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Child Psychology and Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (MH58277, NS054124, MH077248)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
- Keywords
- attention deficit hyperactivity disorder, ADHD heterogeneity, resting-state EEG, latent class analysis, spectral power, slow-wave activity, delta and theta power, alpha and beta power, externalizing problems, internalizing problems, emotional dysregulation, cognitive impairment, children, biomarkers
- MeSH terms
- Adolescent, Adolescent Behavior, Affective Symptoms, Attention Deficit Disorder with Hyperactivity, Behavioral Symptoms, Child, Child Behavior, Female, Humans, Male, Brain Waves, Cognitive Dysfunction
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