Cited by 35Attention Deficit Hyperactivity DisorderAutism Spectrum Disorder ResearchDevelopmental and Educational Neuropsychology

Brainmarker-I Differentially Predicts Remission to Various Attention-Deficit/Hyperactivity Disorder Treatments: A Discovery, Transfer, and Blinded Validation Study

Open access
Voetterl, Helena, van Wingen, Guido, Michelini, Giorgia, Griffiths, Kristi R., Gordon, Evian, DeBeus, Roger, Korgaonkar, Mayuresh S., Loo, Sandra K. +9 more·2023·Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

Abstract

BACKGROUND: Attention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates. METHODS: The biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored. RESULTS: Retrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively. CONCLUSIONS: This study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.bpsc.2022.02.007

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Studies identifying data-driven subgroups of patients characterized by different EEG profiles, which appear associated with various clinical characteristics and different rates of treatment response, demonstrate this.

    “This is demonstrated by studies identifying data-driven subgroups of patients characterized by different EEG profiles, which appear associated with various clinical characteristics 75 and different rates of treatment response 76,77 .”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 8

  1. Garcia Pimenta M, Brown T, Arns M, Enriquez-Geppert S (2021): Treatment efficacy and clinical effectiveness of EEG neurofeedback as a personalized and multimodal treatment in ADHD: A critical review. Neuropsychiatr Dis Treat 17:637-648.
  2. Olbrich S, van Dinteren R, Arns M (2015): Personalized medicine: Review and perspectives of promising baseline EEG biomarkers in major depressive disorder and attention deficit hyperactivity disorder. Neuropsychobiology 72:229-240.
  3. Klimesch W (1999): EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Res Brain Res Rev 29:169-195.
  4. Van Doren J, Arns M, Heinrich H, Vollebregt MA, Strehl U, Loo SK (2019): Sustained effects of neurofeedback in ADHD: A systematic review and meta-analysis. Eur Child Adolesc Psychiatr 28:293-305.
  5. van Dijk H, van Wingen G, Denys D, Olbrich S, van Ruth R, Arns M (2022): The two decades brainclinics research archive for insights in neurophysiology (TD-BRAIN) database. Sci Data 9:333. Blinded Validation of an ADHD Stratification Biomarker Biological Psychiatry: Cognitive Neuroscience and Neuroimaging January 2023; 8:52-60 www.sobp.org/BPCNNI 59 Biological Psychiatry: CNNI
  6. Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. (2020): SciPy 1.0: Fundamental algorithms for scientific computing in Python [published correction appears in Nat Methods 2020; 17:352]. Nat Methods 17:261-272.
  7. Musser ED, Backs RW, Schmitt CF, Ablow JC, Measelle JR, Nigg JT (2011): Emotion regulation via the autonomic nervous system in chil- dren with attention-deficit/hyperactivity disorder (ADHD) [published correction appears in J Abnorm Child Psychol 2018; 46:655-657]. J Abnorm Child Psychol 39:841-852.
  8. Corlier J, Carpenter LL, Wilson AC, Tirrell E, Gobin AP, Kavanaugh B, Leuchter AF (2019): The relationship between individual alpha peak frequency and clinical outcome with repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD). Brain Stimul 12:1572-1578. Blinded Validation of an ADHD Stratification Biomarker 60 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging January 2023; 8:52-60 www.sobp.org/BPCNNI Biological Psychiatry:

Cited by

Sorted by citations

Authors
Voetterl, H., van Wingen, G., Michelini, G., Griffiths, K. R., Gordon, E., DeBeus, R., Korgaonkar, M. S., Loo, S. K., Palmer, D., Breteler, R., Denys, D., Arnold, L. E., du Jour, P., van Ruth, R., Jansen, J., van Dijk, H., & Arns, M.
Affiliations
  • Maastricht University (NL)
  • University of California, Los Angeles (US)
  • The University of Sydney (AU)
  • University of North Carolina at Asheville (US)
  • Radboud University Nijmegen (NL)
  • Amsterdam University Medical Centers (NL)
  • The Ohio State University (US)
Corresponding author
  • Voetterl, Helena
  • Arns, Martijn
Venue
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Publisher
Elsevier BV
Published
2023-01
Volume
8
Issue
1
Pages
52-60
ISSN
2451-9022 (ISSN-L)
OpenAlex
W4220782567
Cited by
35
References
6
Citations by year
2026: 7 · 2025: 5 · 2024: 8 · 2023: 10 · 2022: 5
FWCI
4.58
Type
journal article
Language
en
Open access
Locations
  • Biological Psychiatry Cognitive Neuroscience and Neuroimaging (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion, cc-by)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
  • Pure Amsterdam UMC (submittedVersion, cc-by)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
  • Research Publications (Maastricht University) (submittedVersion, cc-by)
Funders
  • Takeda Pharmaceutical Company
  • National Institute of Mental Health
  • Seaside Therapeutics
  • Pfizer
  • Shire
  • Roche
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, treatment response prediction, biomarkers, resting-state EEG, methylphenidate, neurofeedback, sleep coaching, guanfacine, atomoxetine, treatment stratification, personalized treatment, remission
MeSH terms
Atomoxetine Hydrochloride, Attention Deficit Disorder with Hyperactivity, Humans, Male, Methylphenidate, Retrospective Studies, Treatment Outcome

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review