An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder

Raimon H.R. Pruim; Christian F. Beckmann; Marianne Oldehinkel; Jaap Oosterlaan; Dirk Heslenfeld; Catharina A. Hartman; Pieter J. Hoekstra; Stephen V. Faraone; Barbara Franke; Jan K. Buitelaar; Maarten Mennes

doi:10.1016/j.bpsc.2018.11.014

An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder

Raimon H.R. Pruim^*, Christian F. Beckmann, Marianne Oldehinkel, Jaap Oosterlaan, Dirk Heslenfeld, Catharina A. Hartman, Pieter J. Hoekstra, Stephen V. Faraone, Barbara Franke, Jan K. Buitelaar, Maarten Mennes

^*Corresponding author for this work

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Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder, putatively induced by dissociable dysfunctional biobehavioral pathways. Here, we present a proof-of-concept study to parse ADHD-related heterogeneity in its underlying neurobiology by investigating functional connectivity across multiple brain networks to 1) disentangle categorical diagnosis-related effects from dimensional behavior-related effects and 2) functionally map these neural correlates to neurocognitive measures. Methods: We identified functional connectivity abnormalities related to ADHD across 14 networks within a large resting-state functional magnetic resonance imaging dataset (n = 409; age = 17.5 ± 3.3 years). We tested these abnormalities for their association with the categorical ADHD diagnosis and with dimensional inattention and hyperactivity/impulsivity scores using a novel modeling framework, creating orthogonalized models. Next, we evaluated the relationship of these findings with neurocognitive measures (working memory, response inhibition, reaction time variability, reward sensitivity). Results: Within the default mode network, we mainly observed categorical ADHD-related functional connectivity abnormalities, unrelated to neurocognitive measures. Clusters within the visual networks primarily related to dimensional scores of inattention and reaction time variability, while findings within the sensorimotor networks were mainly linked to hyperactivity/impulsivity and both reward sensitivity and working memory. Findings within the cerebellum network and salience network related to both categorical and dimensional ADHD measures and were linked to response inhibition and reaction time variability. Conclusions: This proof-of-concept study identified ADHD-related neural correlates across multiple functional networks, showing distinct categorical and dimensional mechanisms and their links to neurocognitive functioning.

Original language	English
Pages (from-to)	472-483
Number of pages	12
Journal	Biological Psychiatry : Cognitive Neuroscience and Neuroimaging
Volume	4
Issue number	5
Early online date	20 Dec 2018
DOIs	https://doi.org/10.1016/j.bpsc.2018.11.014
Publication status	Published - May 2019

Funding

This work was supported by National Institutes of Health Grant No. R01MH62873 (to SVF), Netherlands Organisation for Scientific Research (NWO) Large Investment Grant No. 1750102007010 (to JKB), ZonMW Addiction: Risk Behaviour and Dependency Grant No. 60-60600-97-193 (to JKB), NWO Brain & Cognition: An Integrative Approach Grant No. 433-09-242 (to JKB), NWO National Initiative Brain & Cognition Grant No. 056-13-015 (to JKB), European Union Seventh Framework Programme (FP7/2007-2013) TACTICS Grant No. 278948 (to JKB) ; Radboud University Medical Centre, University Medical Centre Groningen, Accare, and VU University Amsterdam; the K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Norway (to SVF); the European Community Seventh Framework Programme (FP7/2007-2013) Grant Nos. 602805 (Aggressotype) (to SVF and BF) and 602450 (IMAGEMEND) (to BF); National Institute of Mental Health Grant No. R01MH094469 (to SVF); NWO Brain & Cognition Excellence Program Grant No. 433-09-229 (to BF), Vici Grant No. 016-130-669 (to BF); the European Community Horizon 2020 Programme (H2020/2014–2020) Grant No. 643051 (MiND) (to BF); ENIGMA Consortium Grant No. U54 EB020403 (to BF) from the BD2K Initiative of a cross–National Institutes of Health partnership; the European Research Council, under European Union FP7/ERC Grant No. 327340 (BRAIN FINGERPRINT) (to MM); NWO-Vidi Grant No. 864-12-003 (to CFB); and Wellcome Trust UK Strategic Award Grant No. 098369/Z/12/Z (to CFB) . We acknowledge the Department of Pediatrics of the VU University Medical Centre for the opportunity to use the mock scanner for preparation of our participants. CFB is co-founder and CEO of SBGneuro Ltd. JO has received an unrestricted investigator-initiated research grant from Shire . PJH has received an unrestricted research grant from Shire and has been member of the advisory boards of Shire and Eli Lilly. SVF has received consulting income, travel expenses and/or research support from Pfizer , Shire , Akili Interactive Labs , Otsuka Pharmaceutical , VAYA Pharma , SynapDx , and Alcobra Pharma and research support from the National Institutes of Health . His institution is seeking a patent for the use of sodium-hydrogen exchange inhibitors in the treatment of attention-deficit/hyperactivity disorder. He has also received consulting fees from, was on advisory boards for, or participated in continuing medical education programs sponsored by Shire , Alcobra, Otsuka, Ortho-McNeil-Janssen Pharmaceuticals, Novartis, Pfizer, and Eli Lilly. SVF receives royalties from books published by Guilford Press ( Straight Talk About Your Child’s Mental Health ) and Oxford University Press ( Schizophrenia: The Facts ). BF has received educational speaking fees from Merz and Shire. JKB has been a consultant to/member of advisory boards of and/or a speaker for Janssen-Cilag BV, Eli Lilly, Shire, Novartis, Roche, Lundbeck, Medice, and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. The other authors report no biomedical financial interests or potential conflicts of interest.

Funders	Funder number
Alcobra Pharma
European Community Horizon 2020 Programme
European Union FP7/ERC	327340
FP7/2007
K.G. Jebsen Centre for Research
Mind	U54 EB020403
NWO-VIDI	864-12-003
Radboud University Medical Centre
SBGneuro Ltd
SynapDx
University Medical Centre Groningen
VAYA Pharma
VU University Medical Centre
National Institutes of Health	R01MH62873
National Institute of Mental Health	016-130-669, R01MH094469, 433-09-229
Eli Lilly and Company
Pfizer
Shire
Wellcome Trust	098369/Z/12/Z
Horizon 2020 Framework Programme	643051
Seventh Framework Programme	602805, 602450, 278948
European Research Council
ZonMw	60-60600-97-193, 433-09-242, 056-13-015
Vrije Universiteit Amsterdam
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	1750102007010
Shire
Seventh Framework Programme
Universitair Medisch Centrum Groningen
Radboud Universitair Medisch Centrum
Otsuka Pharmaceutical
Servier

Keywords

Attention-deficit/hyperactivity disorder
Categorical-dimensional analysis
Connectivity
Neural networks
Neuropsychology
Resting-state functional magnetic resonance imaging
rfMRI

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An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit,Hyperactivity DisorderFinal published version, 1.53 MBLicence: Article 25fa Dutch Copyright Act

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Pruim, R. H. R., Beckmann, C. F., Oldehinkel, M., Oosterlaan, J., Heslenfeld, D., Hartman, C. A., Hoekstra, P. J., Faraone, S. V., Franke, B., Buitelaar, J. K., & Mennes, M. (2019). An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry : Cognitive Neuroscience and Neuroimaging, 4(5), 472-483. https://doi.org/10.1016/j.bpsc.2018.11.014

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title = "An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder",

abstract = "Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder, putatively induced by dissociable dysfunctional biobehavioral pathways. Here, we present a proof-of-concept study to parse ADHD-related heterogeneity in its underlying neurobiology by investigating functional connectivity across multiple brain networks to 1) disentangle categorical diagnosis-related effects from dimensional behavior-related effects and 2) functionally map these neural correlates to neurocognitive measures. Methods: We identified functional connectivity abnormalities related to ADHD across 14 networks within a large resting-state functional magnetic resonance imaging dataset (n = 409; age = 17.5 ± 3.3 years). We tested these abnormalities for their association with the categorical ADHD diagnosis and with dimensional inattention and hyperactivity/impulsivity scores using a novel modeling framework, creating orthogonalized models. Next, we evaluated the relationship of these findings with neurocognitive measures (working memory, response inhibition, reaction time variability, reward sensitivity). Results: Within the default mode network, we mainly observed categorical ADHD-related functional connectivity abnormalities, unrelated to neurocognitive measures. Clusters within the visual networks primarily related to dimensional scores of inattention and reaction time variability, while findings within the sensorimotor networks were mainly linked to hyperactivity/impulsivity and both reward sensitivity and working memory. Findings within the cerebellum network and salience network related to both categorical and dimensional ADHD measures and were linked to response inhibition and reaction time variability. Conclusions: This proof-of-concept study identified ADHD-related neural correlates across multiple functional networks, showing distinct categorical and dimensional mechanisms and their links to neurocognitive functioning.",

keywords = "Attention-deficit/hyperactivity disorder, Categorical-dimensional analysis, Connectivity, Neural networks, Neuropsychology, Resting-state functional magnetic resonance imaging, rfMRI",

author = "Pruim, {Raimon H.R.} and Beckmann, {Christian F.} and Marianne Oldehinkel and Jaap Oosterlaan and Dirk Heslenfeld and Hartman, {Catharina A.} and Hoekstra, {Pieter J.} and Faraone, {Stephen V.} and Barbara Franke and Buitelaar, {Jan K.} and Maarten Mennes",

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Pruim, RHR, Beckmann, CF, Oldehinkel, M, Oosterlaan, J, Heslenfeld, D, Hartman, CA, Hoekstra, PJ, Faraone, SV, Franke, B, Buitelaar, JK & Mennes, M 2019, 'An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder', Biological Psychiatry : Cognitive Neuroscience and Neuroimaging, vol. 4, no. 5, pp. 472-483. https://doi.org/10.1016/j.bpsc.2018.11.014

An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder. / Pruim, Raimon H.R.; Beckmann, Christian F.; Oldehinkel, Marianne et al.
In: Biological Psychiatry : Cognitive Neuroscience and Neuroimaging, Vol. 4, No. 5, 05.2019, p. 472-483.

Research output: Contribution to Journal › Article › Academic › peer-review

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T1 - An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder

AU - Pruim, Raimon H.R.

AU - Beckmann, Christian F.

AU - Oldehinkel, Marianne

AU - Oosterlaan, Jaap

AU - Heslenfeld, Dirk

AU - Hartman, Catharina A.

AU - Hoekstra, Pieter J.

AU - Faraone, Stephen V.

AU - Franke, Barbara

AU - Buitelaar, Jan K.

AU - Mennes, Maarten

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N2 - Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder, putatively induced by dissociable dysfunctional biobehavioral pathways. Here, we present a proof-of-concept study to parse ADHD-related heterogeneity in its underlying neurobiology by investigating functional connectivity across multiple brain networks to 1) disentangle categorical diagnosis-related effects from dimensional behavior-related effects and 2) functionally map these neural correlates to neurocognitive measures. Methods: We identified functional connectivity abnormalities related to ADHD across 14 networks within a large resting-state functional magnetic resonance imaging dataset (n = 409; age = 17.5 ± 3.3 years). We tested these abnormalities for their association with the categorical ADHD diagnosis and with dimensional inattention and hyperactivity/impulsivity scores using a novel modeling framework, creating orthogonalized models. Next, we evaluated the relationship of these findings with neurocognitive measures (working memory, response inhibition, reaction time variability, reward sensitivity). Results: Within the default mode network, we mainly observed categorical ADHD-related functional connectivity abnormalities, unrelated to neurocognitive measures. Clusters within the visual networks primarily related to dimensional scores of inattention and reaction time variability, while findings within the sensorimotor networks were mainly linked to hyperactivity/impulsivity and both reward sensitivity and working memory. Findings within the cerebellum network and salience network related to both categorical and dimensional ADHD measures and were linked to response inhibition and reaction time variability. Conclusions: This proof-of-concept study identified ADHD-related neural correlates across multiple functional networks, showing distinct categorical and dimensional mechanisms and their links to neurocognitive functioning.

AB - Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder, putatively induced by dissociable dysfunctional biobehavioral pathways. Here, we present a proof-of-concept study to parse ADHD-related heterogeneity in its underlying neurobiology by investigating functional connectivity across multiple brain networks to 1) disentangle categorical diagnosis-related effects from dimensional behavior-related effects and 2) functionally map these neural correlates to neurocognitive measures. Methods: We identified functional connectivity abnormalities related to ADHD across 14 networks within a large resting-state functional magnetic resonance imaging dataset (n = 409; age = 17.5 ± 3.3 years). We tested these abnormalities for their association with the categorical ADHD diagnosis and with dimensional inattention and hyperactivity/impulsivity scores using a novel modeling framework, creating orthogonalized models. Next, we evaluated the relationship of these findings with neurocognitive measures (working memory, response inhibition, reaction time variability, reward sensitivity). Results: Within the default mode network, we mainly observed categorical ADHD-related functional connectivity abnormalities, unrelated to neurocognitive measures. Clusters within the visual networks primarily related to dimensional scores of inattention and reaction time variability, while findings within the sensorimotor networks were mainly linked to hyperactivity/impulsivity and both reward sensitivity and working memory. Findings within the cerebellum network and salience network related to both categorical and dimensional ADHD measures and were linked to response inhibition and reaction time variability. Conclusions: This proof-of-concept study identified ADHD-related neural correlates across multiple functional networks, showing distinct categorical and dimensional mechanisms and their links to neurocognitive functioning.

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An Integrated Analysis of Neural Network Correlates of Categorical and Dimensional Models of Attention-Deficit/Hyperactivity Disorder

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