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. 2025 Jul;34(7):2253-2267.
doi: 10.1007/s00787-025-02638-4. Epub 2025 Jan 18.

Disentangling the neural underpinnings of response inhibition in disruptive behavior and co-occurring ADHD

Gülhan Saraçaydın  1 , Daan van Rooij  2   3 , Renee Kleine-Deters  1 , Marieke Messchendorp  1 , Jilly Naaijen  2   3 , María José Penzol  4 , Mireia Rosa  5 , Pascal-M Aggensteiner  6 , Sarah Baumeister  6 , Nathalie Holz  6 , Tobias Banaschewski  6 , Melanie Saam  7 , Ulrike M E Schulze  7 , Arjun Sethi  8 , Michael Craig  8 , Josefina Castro-Fornieles  9 , Celso Arango  4 , Susanne Walitza  10   11 , Julia Werhahn  10   11 , Daniel Brandeis  6   10   11 , Barbara Franke  12   13 , I Hyun Ruisch  14 , Jan K Buitelaar  2   15 , Andrea Dietrich #  1 , Pieter J Hoekstra #  1
Affiliations

Disentangling the neural underpinnings of response inhibition in disruptive behavior and co-occurring ADHD

Gülhan Saraçaydın et al. Eur Child Adolesc Psychiatry. 2025 Jul.

Abstract

While impaired response inhibition has been reported in attention-deficit/hyperactivity disorder (ADHD), findings in disruptive behavior disorders (DBDs) have been inconsistent, probably due to unaccounted effects of co-occurring ADHD in DBD. This study investigated the associations of behavioral and neural correlates of response inhibition with DBD and ADHD symptom severity, covarying for each other in a dimensional approach. Functional magnetic resonance imaging data were available for 35 children and adolescents with DBDs (8-18 years old, 19 males), and 31 age-matched unaffected controls (18 males) while performing a performance-adjusted stop-signal task. No significant association was found between behavioral performance and symptom severities. However, contrasting successful inhibition with failed inhibition revealed that DBD and ADHD symptom severity was associated with greater activation in the right inferior frontal regions and reduced activation in the bilateral striatal regions, respectively. During successful inhibition versus go-trials, ADHD symptom severity was associated with the left lateral occipital cortex activation. The contrast of failed inhibition versus go-trials revealed reduced activation in the right frontal and left parietal regions associated with DBD symptom severity while ADHD symptom severity was associated with bilateral precunei, dorsolateral prefrontal and left posterior parietal regions. Except for the right inferior frontal regions during successful versus failed inhibition, all clusters were also found to be inversely associated with the other dimension of interest (i.e., DBD or ADHD symptoms). Opposite direction of the associations between DBD and ADHD symptom severity, and fronto-parietal and fronto-striatal activation suggest unique contributions of DBD and ADHD to the neural correlates of response inhibition.

Keywords: Attention-deficit/hyperactivity disorder; Dimensional approach; Disruptive behavior disorder; Functional magnetic resonance imaging; Response inhibition.

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Conflict of interest statement

Declarations. Competing interests: Tobias Banaschewski served in an advisory or consultancy role for Actelion, Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg GmbH, Shire, and Infectopharm. He received conference support or speaker’s fee by Lilly, Medice, and Shire. He received royalities from Hogrefe, Kohlhammer, CIP Medien, Oxford University Press; the present work is unrelated to these relationships. Ulrike M.E. Schulze received funding by the EU FP7 Programme and actually serves an unpaid ethics advisor for two other EU-funded projects. She received speaker’s fee from Shire. Celso Arango has been a consultant to or has received honoraria or grants from Acadia, Ambrosseti, Caja Navarra, CIBERSAM, Fundación Alicia Koplowitz, Forum, Instituto de Salud Carlos III, Gedeon Richter, Janssen Cilag, Lundbeck, Merck, Ministerio de Ciencia e Innovación, Ministerio de Sanidad, Ministerio de Economía y Competitividad, Mutua Madrileña, Otsuka, Roche, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovio and Takeda. Daniel Brandeis serves as an unpaid scientific advisor for an EU-funded Neurofeedback trial unrelated to the present work. Barbara Franke received an educational speaking fee from Shire and Medice. Jan K. Buitelaar has been consultant to/member of advisory board of and/or speaker for Janssen Cilag BV, Eli Lilly, Takeda/Shire, Roche, Medice, Angelini, Novartis and Servier. He is not an employee of any of these companies, nor a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents, and royalties. I. Hyun Ruisch is an employee of Drug Target ID, Ltd., but his activities at this company do not constitute competing interests with regard to this paper. The other authors do not report any biomedical financial interests or potential conflicts of interest.

Figures

Fig. 1
Fig. 1
(A) Brain regions that were positively correlated with ADHD symptom severity scores during successful inhibition versus successful go trials, shown in radiologic view with the right brain shown on the left; (B) A partial regression plot for the multiple linear regression model reflecting the partial correlation coefficient between parameter estimates extracted from the cluster shown in (A), and symptom severity scores after adjustment for sex, age, IQ, scanning site, and the other respective score dimension. Points represent the partial residuals, the solid line indicates predicted values from the model, and the gray area indicates 95% confidence interval of the predicted values. For comprehensiveness, we also showed the relation between the cluster parameter estimates and the other disorder (so in case of a DBD-associated cluster, we also showed the link with ADHD scores and vice versa), therefore each plot shows 2 line graphs. See also Table 2 for an overview of the clusters identified in this contrast
Fig. 2
Fig. 2
(A) Brain regions (two clusters) that were negatively correlated with DBD scores (upper and middle cross-sections) and brain regions (four clusters) that were positively correlated with ADHD scores (lower cross-section) during failed inhibition versus successful go trials, shown in radiologic view with the right brain shown on the left; (B) Partial regression plots for the multiple linear regression models reflecting the partial correlation coefficient between parameter estimates extracted from the clusters associated with DBD (left two plots) and ADHD (right four plots) symptom severity scores and shown in (A), and symptom severity scores after adjustment for sex, age, IQ, scanning site, and the other respective score dimension. Points represent the partial residuals, the solid lines indicate predicted values from the models, and the gray areas indicate 95% confidence interval of the predicted values. For comprehensiveness, we also showed the relation between the cluster parameter estimates and the other disorder (so in case of a DBD-associated cluster, we also showed the link with ADHD scores and vice versa), therefore each plot shows 2 line graphs. See also Table 2 for an of the overview clusters identified in this contrast
Fig. 3
Fig. 3
(A) Brain regions that were positively correlated with DBD (upper) and negatively correlated with ADHD scores (lower) during successful inhibition versus failed inhibition, shown in radiologic view with the right brain shown on the left; (B) Partial regression plots for the multiple linear regression models reflecting the partial correlation coefficient between parameter estimates extracted from the clusters associated with DBD (upper) and ADHD (lower) symptom severity scores and shown in (A), and symptom severity scores after adjustment for sex, age, IQ, scanning site, and the other respective score dimension. Points represent the partial residuals, the solid lines indicate predicted values from the models, and the gray areas indicate 95% confidence interval of the predicted values. For comprehensiveness, we also showed the relation between the cluster parameter estimates and the other disorder (so in case of a DBD-associated cluster, we also showed the link with ADHD scores and vice versa), therefore each plot shows 2 line graphs. See also Table 2 for an overview of the clusters identified in this contrast
See this image and copyright information in PMC

References

    1. Canino G, Polanczyk G, Bauermeister JJ, Rohde LA, Frick PJ (2010) Does the prevalence of CD and ODD vary across cultures? Soc Psychiatry Psychiatr Epidemiol 45(7):695–704. 10.1007/s00127-010-0242-y - PMC - PubMed
    1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th edition-text revision (DSM-IV-TR). Washington (DC): The Association (2000) ISBN: 0890420254
    1. Loeber R, Burke JD, Lahey BB, Winters A, Zera M (2000) Oppositional defiant and conduct disorder: a review of the past 10 years, part I. J Am Acad Child Adolesc Psychiatry 39(12):1468–1484. 10.1097/00004583-200012000-00007 - PubMed
    1. Maughan B, Rowe R, Messer J, Goodman R, Meltzer H (2004) Conduct Disorder and oppositional defiant disorder in a national sample: developmental epidemiology. J Child Psychol Psychiatry 45(3):609–621. 10.1111/j.1469-7610.2004.00250.x - PubMed
    1. Diamond A (2013) Executive functions. Ann Rev Psychol 64(1):135–168. 10.1146/annurev-psych-113011-143750 - PMC - PubMed

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