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Methylphenidate enhances spontaneous fluctuations in reward and cognitive control networks in children with attention-deficit/hyperactivity disorder

  • Yoshifumi Mizuno
    Correspondence
    Corresponding authors: Yoshifumi Mizuno, M.D., Ph.D. Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304, USA Tel: +1-650-736-3699
    Affiliations
    Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA

    Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan

    Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan

    Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan
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  • Weidong Cai
    Affiliations
    Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA

    Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA

    Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
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  • Kaustubh Supekar
    Affiliations
    Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA

    Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA

    Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
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  • Kai Makita
    Affiliations
    Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan

    Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan
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  • Shinichiro Takiguchi
    Affiliations
    Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan

    Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan
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  • Timothy J. Silk
    Affiliations
    Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Geelong, VIC, 3125, Australia

    Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia
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  • Akemi Tomoda
    Affiliations
    Research Center for Child Mental Development, University of Fukui, Fukui, 910-1193, Japan

    Division of Developmental Higher Brain Functions, United Graduate School of Child Development, University of Fukui, Fukui, 910-1193, Japan

    Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui, 910-1193, Japan
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  • Vinod Menon
    Correspondence
    Corresponding authors: Vinod Menon, Ph.D. Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304, USA Tel: +1-650-736-3699
    Affiliations
    Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA

    Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94304, USA

    Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94304, USA

    Maternal & Child Health Research Institute, Stanford University, Stanford, CA 94304, USA
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Open AccessPublished:October 22, 2022DOI:https://doi.org/10.1016/j.bpsc.2022.10.001

      Abstract

      Background

      Methylphenidate, a first-line treatment for attention-deficit/hyperactivity disorder (ADHD), is thought to influence dopaminergic neurotransmission in the nucleus accumbens (NAc), and its associated brain circuitry, but this hypothesis has yet to be systematically tested.

      Methods

      We conducted a randomized, placebo-controlled double-blind crossover trial with 27 children with ADHD. Children with ADHD were scanned twice with resting-state functional MRI under methylphenidate and placebo conditions, along with assessment of sustained attention. We examined spontaneous neural activity in the NAc and the salience, frontoparietal, and default mode networks, and their links to behavioral changes. Replicability of methylphenidate effects on spontaneous neural activity was examined in a second independent cohort.

      Results

      Methylphenidate increased spontaneous neural activity in the NAc, and the salience and default mode networks. Methylphenidate-induced changes in spontaneous activity patterns in the default mode network were associated with improvements in intra-individual response variability during a sustained attention task. Critically, despite differences in clinical trial protocols and data acquisition parameters, the NAc, and the salience and default mode networks showed replicable patterns of methylphenidate-induced changes in spontaneous activity across two independent cohorts.

      Conclusions

      We provide reproducible evidence demonstrating that methylphenidate enhances spontaneous neural activity in NAc and cognitive control networks in children with ADHD, resulting in more stable sustained attention. Findings identify a novel neural mechanism underlying methylphenidate treatment in ADHD and inform the development of clinically useful biomarkers for evaluating treatment outcomes.

      Key words

      Introduction

      Methylphenidate is a widely used first-line medication for alleviating clinical symptoms of inattention, hyperactivity, and impulsivity in children with attention deficit hyperactivity disorder (ADHD) (
      • McLennan J.D.
      Understanding attention deficit hyperactivity disorder as a continuum.
      ,
      • Posner J.
      • Polanczyk G.V.
      • Sonuga-Barke E.
      Attention-deficit hyperactivity disorder.
      ,
      • Engert V.
      • Pruessner J.C.
      Dopaminergic and noradrenergic contributions to functionality in ADHD: the role of methylphenidate.
      ). Altered dopamine signaling has been hypothesized to be a key mechanism underlying the therapeutic effects of methylphenidate in ADHD (
      • Arnsten A.F.T.
      Stimulants: Therapeutic actions in ADHD.
      ). Individuals with ADHD display low dopamine receptor availability in the corticolimbic pathway (
      • Volkow N.D.
      • Wang G.-J.
      • Kollins S.H.
      • Wigal T.L.
      • Newcorn J.H.
      • Telang F.
      • et al.
      Evaluating dopamine reward pathway in ADHD: clinical implications.
      ,
      • Volkow N.D.
      • Wang G.-J.
      • Newcorn J.
      • Telang F.
      • Solanto M.V.
      • Fowler J.S.
      • et al.
      Depressed dopamine activity in caudate and preliminary evidence of limbic involvement in adults with attention-deficit/hyperactivity disorder.
      ) and methylphenidate has been hypothesized to ameliorate ADHD symptoms by increasing extracellular dopamine in the nucleus accumbens (NAc) (
      • Faraone S.V.
      The pharmacology of amphetamine and methylphenidate: Relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities.
      ). In neurotypical individuals, dopamine acts as a reinforcer to facilitate motivated behaviors and goal-driven adaptive control (
      • Bromberg-Martin E.S.
      • Matsumoto M.
      • Hikosaka O.
      Dopamine in motivational control: rewarding, aversive, and alerting.
      ) via its action on the NAc and cognitive control systems that it regulates (
      • Stoy M.
      • Schlagenhauf F.
      • Schlochtermeier L.
      • Wrase J.
      • Knutson B.
      • Lehmkuhl U.
      • et al.
      Reward processing in male adults with childhood ADHD-a comparison between drug-naïve and methylphenidate-treated subjects.
      ,
      • Coghill D.R.
      • Seth S.
      • Pedroso S.
      • Usala T.
      • Currie J.
      • Gagliano A.
      Effects of methylphenidate on cognitive functions in children and adolescents with attention-deficit/hyperactivity disorder: evidence from a systematic review and a meta-analysis.
      ,
      • Tamminga H.G.H.
      • Reneman L.
      • Huizenga H.M.
      • Geurts H.M.
      Effects of methylphenidate on executive functioning in attention-deficit/hyperactivity disorder across the lifespan: a meta-regression analysis.
      ,
      • Mueller A.
      • Hong D.S.
      • Shepard S.
      • Moore T.
      Linking ADHD to the Neural Circuitry of Attention.
      ). However, despite decades of its effective use in clinical practice, the precise brain mechanisms underlying the therapeutic effects of methylphenidate are poorly understood as no consistent findings have emerged to date (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ). Specifically, the parallel effects of methylphenidate-induced changes on NAc and its interconnected cognitive control networks, and their relation to attentional deficits in childhood ADHD remain unknown.
      Dopaminergic pharmacology has been most consistently mapped in the NAc where dopamine receptors and transporters are particularly dense (
      • Faraone S.V.
      The pharmacology of amphetamine and methylphenidate: Relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities.
      ,
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ). Low dopamine receptor density in the NAc has been linked to the severity of inattention symptoms in adults with ADHD (
      • Volkow N.D.
      • Wang G.-J.
      • Kollins S.H.
      • Wigal T.L.
      • Newcorn J.H.
      • Telang F.
      • et al.
      Evaluating dopamine reward pathway in ADHD: clinical implications.
      ). At the brain network level, integrative PET-MRI analyses in neurotypical adults have further revealed that mesolimbic dopamine function influences connectivity of the salience network (SN) and the default mode network (DMN) (
      • McCutcheon R.A.
      • Nour M.M.
      • Dahoun T.
      • Jauhar S.
      • Pepper F.
      • Expert P.
      • et al.
      Mesolimbic Dopamine Function Is Related to Salience Network Connectivity: An Integrative Positron Emission Tomography and Magnetic Resonance Study.
      ). The SN is important for identifying biologically and cognitively salient events, and guiding attention and goal-directed behaviors (
      • Menon V.
      • Uddin L.Q.
      Saliency, switching, attention and control: a network model of insula function.
      ,
      • Cai W.
      • Ryali S.
      • Chen T.
      • Li C.-S.R.
      • Menon V.
      Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.
      ,
      • Cai W.
      • Chen T.
      • Ide J.S.
      • Li C.-S.R.
      • Menon V.
      Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.
      ,
      • Seeley W.W.
      • Menon V.
      • Schatzberg A.F.
      • Keller J.
      • Glover G.H.
      • Kenna H.
      • et al.
      Dissociable intrinsic connectivity networks for salience processing and executive control.
      ). The SN, together with the frontoparietal network (FPN), and the default mode network (DMN) constitute a triple-network system (
      • Menon V.
      • Uddin L.Q.
      Saliency, switching, attention and control: a network model of insula function.
      ) which plays a crucial role in a wide range of cognitive tasks that require moment-by-moment changes in adaptive cognitive control (
      • Menon V.
      • Uddin L.Q.
      Saliency, switching, attention and control: a network model of insula function.
      ,

      Menon V (2015): Salience Network. Brain Mapping: An Encyclopedic Reference, vol. 2. Elsevier Inc. https://doi.org/10.1016/B978-0-12-397025-1.00052-X

      ,
      • Taghia J.
      • Cai W.
      • Ryali S.
      • Kochalka J.
      • Nicholas J.
      • Chen T.
      • Menon V.
      Uncovering hidden brain state dynamics that regulate performance and decision-making during cognition.
      ,
      • Cai W.
      • Ryali S.
      • Pasumarthy R.
      • Talasila V.
      • Menon V.
      Dynamic causal brain circuits during working memory and their functional controllability.
      ). Task-based fMRI studies of inhibitory control in children with ADHD have suggested that psychostimulants increase activation in the right insula/inferior frontal cortex (
      • Rubia K.
      • Alegria A.A.
      • Cubillo A.I.
      • Smith A.B.
      • Brammer M.J.
      • Radua J.
      Effects of stimulants on brain function in attention-deficit/hyperactivity disorder: A systematic review and meta-analysis.
      ), a key SN node implicated in inhibitory control (
      • Cai W.
      • Ryali S.
      • Chen T.
      • Li C.-S.R.
      • Menon V.
      Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.
      ,
      • Cai W.
      • Chen T.
      • Ide J.S.
      • Li C.-S.R.
      • Menon V.
      Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.
      ). The SN as a locus of deficits in childhood ADHD has been further bolstered by network connectivity analysis of a Go/NoGo task which identified SN-FPN connectivity as a common locus of deficits in cognitive control and clinical measures of inattention symptoms (
      • Cai W.
      • Griffiths K.
      • Korgaonkar M.S.
      • Williams L.M.
      • Menon V.
      Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.
      ). DMN impairments have also emerged as a prominent feature of ADHD, consistent with theoretical models which have proposed that aberrant engagement of the SN leads to a lack of active suppression and disengagement of the DMN and inattention (
      • Menon V.
      Large-scale brain networks and psychopathology: a unifying triple network model.
      ,
      • Cai W.
      • Chen T.
      • Szegletes L.
      • Supekar K.
      • Menon V.
      Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits.
      ,
      • Jilka S.R.
      • Scott G.
      • Ham T.
      • Pickering A.
      • Bonnelle V.
      • Braga R.M.
      • et al.
      Damage to the Salience Network and interactions with the Default Mode Network.
      ). Together, these observations suggest that aberrancies in the NAc together with the SN, FPN and DMN cognitive control networks may underlie the clinical symptoms of ADHD and constitute specific brain targets for remediation using methylphenidate.
      Here we use a randomized placebo-controlled double-blind crossover design (Figure S1) to investigate the effect of methylphenidate on spontaneous neural activity in the NAc, as well as the SN, FPN and DMN, and their links to the behavioral effects of medication in children with ADHD. We used amplitude of low-frequency fluctuation (ALFF) to capture the regional intensity of spontaneous fluctuations in fMRI signals (
      • Zang Y.-F.
      • He Y.
      • Zhu C.-Z.
      • Cao Q.-J.
      • Sui M.-Q.
      • Liang M.
      • et al.
      Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI.
      ). Multimodal PET-MRI studies have suggested that spontaneous fluctuations in fMRI signals arise from metabolic demands associated with ongoing fluctuations in synaptic currents and action potential propagation (
      • Tomasi D.
      • Wang G.-J.
      • Volkow N.D.
      Energetic cost of brain functional connectivity.
      ,
      • Attwell D.
      • Laughlin S.B.
      An energy budget for signaling in the grey matter of the brain.
      ). ALFF has been widely used to probe the integrity of brain region-level functioning in psychiatric and neurological disorders (
      • Tomasi D.
      • Wang G.-J.
      • Volkow N.D.
      Energetic cost of brain functional connectivity.
      ,
      • Yang L.
      • Yan Y.
      • Wang Y.
      • Hu X.
      • Lu J.
      • Chan P.
      • et al.
      Gradual Disturbances of the Amplitude of Low-Frequency Fluctuations (ALFF) and Fractional ALFF in Alzheimer Spectrum.
      ,
      • Fox M.D.
      • Raichle M.E.
      Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.
      ,
      • Kofler M.J.
      • Rapport M.D.
      • Sarver D.E.
      • Raiker J.S.
      • Orban S.A.
      • Friedman L.M.
      • Kolomeyer E.G.
      Reaction time variability in ADHD: a meta-analytic review of 319 studies.
      ). We used ALFF to test the hypothesis that methylphenidate increases spontaneous neural activity in the NAc, a key node in the dopaminergic reward system, and associated cognitive control circuitry.
      A critical unaddressed question is whether methylphenidate-induced changes in spontaneous neural activity are related to remediation of attention and cognitive control deficits. Intra-individual response variability (IIRV), a quantitative measure of trial-wise performance for behavioral instability, is the most consistent robust behavioral phenotype associated with ADHD (
      • Kofler M.J.
      • Rapport M.D.
      • Sarver D.E.
      • Raiker J.S.
      • Orban S.A.
      • Friedman L.M.
      • Kolomeyer E.G.
      Reaction time variability in ADHD: a meta-analytic review of 319 studies.
      ,
      • Lijffijt M.
      • Kenemans J.L.
      • Verbaten M.N.
      • van Engeland H.
      A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: deficient inhibitory motor control?.
      ), and that psychostimulant treatment reduces this increased variability (
      • Kofler M.J.
      • Rapport M.D.
      • Sarver D.E.
      • Raiker J.S.
      • Orban S.A.
      • Friedman L.M.
      • Kolomeyer E.G.
      Reaction time variability in ADHD: a meta-analytic review of 319 studies.
      ). We recently reported that IIRV in ADHD is associated with poor sustained attention and problems in cognitive control (
      • Cai W.
      • Warren S.L.
      • Duberg K.
      • Pennington B.
      • Hinshaw S.P.
      • Menon V.
      Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
      ). Here, we used a novel similarity metric to measure the extent to which ALFF in the cognitive control network system are similar between children with ADHD and typically developing (TD) children (
      • Lijffijt M.
      • Kenemans J.L.
      • Verbaten M.N.
      • van Engeland H.
      A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: deficient inhibitory motor control?.
      ). We specifically focused on the triple-network system encompassing the SN, FPN and DMN in relation to behavioral instability (
      • Cai W.
      • Warren S.L.
      • Duberg K.
      • Pennington B.
      • Hinshaw S.P.
      • Menon V.
      Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
      ) based on extensive evidence for their role in attention and cognitive control (
      • Cai W.
      • Chen T.
      • Ide J.S.
      • Li C.-S.R.
      • Menon V.
      Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.
      ,
      • Cai W.
      • Ryali S.
      • Pasumarthy R.
      • Talasila V.
      • Menon V.
      Dynamic causal brain circuits during working memory and their functional controllability.
      ,
      • Cai W.
      • Griffiths K.
      • Korgaonkar M.S.
      • Williams L.M.
      • Menon V.
      Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.
      ,
      • Jilka S.R.
      • Scott G.
      • Ham T.
      • Pickering A.
      • Bonnelle V.
      • Braga R.M.
      • et al.
      Damage to the Salience Network and interactions with the Default Mode Network.
      ,
      • Wen X.
      • Liu Y.
      • Yao L.
      • Ding M.
      Top-down regulation of default mode activity in spatial visual attention.
      ). We hypothesized that children with ADHD, whose post-medication spontaneous activity patterns are more similar to TD controls, would exhibit greater improvements in IIRV with medication.
      Finally, to address the replication crisis in ADHD (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ), we leveraged resting-state fMRI data from a second independent cohort of children with ADHD who participated in a similar randomized controlled trial involving single-dose methylphenidate treatment (
      • Silk T.J.
      • Malpas C.
      • Vance A.
      • Bellgrove M.A.
      The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD.
      ). We test the hypothesis that multivariate pattern analyses (

      Spisak T, Bingel U, Wager T (2022): Replicable multivariate BWAS with moderate sample sizes. bioRxiv 2022.06.22.497072.

      ) would provide convergent evidence for reproducible findings of methylphenidate-induced changes in spontaneous activity in the NAc and associated cognitive control circuitry, in the primary and secondary cohorts.

      Methods and Materials

      Participants and Study Design

      This study protocol was approved by the Ethics Committee of the University of Fukui, Japan (Assurance no. 20170005). All participants and their parent(s) provided written informed consent for participation in this study. This study is registered with the University Hospital Medical Information Network (UMIN000027533).
      Thirty-four children with ADHD and 65 TD children were recruited at the University of Fukui Hospital, Japan. Figure S1 shows the study design (see Supplemental Methods for details). Children with ADHD were scanned twice, in a randomized placebo-controlled double-blind crossover design. The administration order was counterbalanced across participants to address potential test-retest issues. During the first visit, they were administered osmotic release oral system methylphenidate (OROS-MPH) (1.0 ± 0.1mg/kg) or placebo (lactose) under double-blind conditions as previous studies (
      • Wilens T.
      • McBurnett K.
      • Stein M.
      • Lerner M.
      • Spencer T.
      • Wolraich M.
      ADHD treatment with once-daily OROS methylphenidate: final results from a long-term open-label study.
      ,
      • Chermá M.D.
      • Josefsson M.
      • Rydberg I.
      • Woxler P.
      • Trygg T.
      • Hollertz O.
      • Gustafsson P.A.
      Methylphenidate for Treating ADHD: A Naturalistic Clinical Study of Methylphenidate Blood Concentrations in Children and Adults With Optimized Dosage.
      ,
      • Akhondzadeh S.
      • Mohammadi M.R.
      • Khademi M.
      Zinc sulfate as an adjunct to methylphenidate for the treatment of attention deficit hyperactivity disorder in children: A double blind and randomized trial [ISRCTN64132371].
      ). Five to eight hours after administration, when the methylphenidate concentration in the blood is maximal (

      Concerta® Tablets (Methylphenidate Hydrochloride), Common Technical Document in Japan(October 26 2007、CTD2.7.6.8) (2007):

      ), they underwent a resting-state functional MRI (fMRI) scan and performed a standardized continuous performance task (CPT) (
      • Huang-Pollock C.L.
      • Karalunas S.L.
      • Tam H.
      • Moore A.N.
      Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance.
      ,
      • Shin M.S.
      • Cho S.
      • Chun S.Y.
      • Hong K.-E.M.
      A study of the development and standardization of ADHD Diagnostic system.
      ) outside the MRI scanner.
      During the second visit, within 1 to 6 weeks after the first visit, children with ADHD underwent a resting-state fMRI scan, and performed the CPT after they took the second medicine: children who took OROS-MPH at the first visit took the placebo at the second visit under double-blind conditions, and vice versa. The OROS-MPH and the placebo condition are referred to as ADHD-MPH and ADHD-Placebo, respectively, in this study.
      TD children completed the same resting-state fMRI scan once without either OROS-MPH or placebo. The following inclusion criteria were used for both groups: no contraindications for magnetic resonance imaging (MRI), full-scale intelligence quotient (FSIQ) > 70 (to exclude participants with intellectual disability), no history of severe head trauma or neurological abnormalities (e.g. epilepsy, arachnoid cysts). To minimize the potential impact of sex differences, we included only male participants, consistent with previous ADHD imaging studies (
      • Silk T.J.
      • Malpas C.
      • Vance A.
      • Bellgrove M.A.
      The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD.
      ,
      • Mizuno Y.
      • Jung M.
      • Fujisawa T.X.
      • Takiguchi S.
      • Shimada K.
      • Saito D.N.
      • et al.
      Catechol-O-methyltransferase polymorphism is associated with the cortico-cerebellar functional connectivity of executive function in children with attention-deficit/hyperactivity disorder.
      ,
      • Mizuno Y.
      • Kagitani-Shimono K.
      • Jung M.
      • Makita K.
      • Takiguchi S.
      • Fujisawa T.X.
      • et al.
      Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder.
      ,
      • Jung M.
      • Mizuno Y.
      • Fujisawa T.X.
      • Takiguchi S.
      • Kong J.
      • Kosaka H.
      • Tomoda A.
      The Effects of COMT Polymorphism on Cortical Thickness and Surface Area Abnormalities in Children with ADHD.
      ,
      • Mizuno Y.
      • Cai W.
      • Supekar K.
      • Makita K.
      • Takiguchi S.
      • Tomoda A.
      • Menon V.
      Methylphenidate remediates aberrant brain network dynamics in children with attention-deficit/hyperactivity disorder: A randomized controlled trial.
      ). Participants with excessive head motion (over 3.0 mm, 3.0 degrees, and mean framewise displacement (FD) 0.3 mm) during the scanning were excluded (
      • Mizuno Y.
      • Jung M.
      • Fujisawa T.X.
      • Takiguchi S.
      • Shimada K.
      • Saito D.N.
      • et al.
      Catechol-O-methyltransferase polymorphism is associated with the cortico-cerebellar functional connectivity of executive function in children with attention-deficit/hyperactivity disorder.
      ). Seven children with ADHD were excluded because of refusal to participate, arachnoid cysts, and motion during the MRI, while 16 TD controls were excluded because of psychiatric disorders, and neurological abnormalities, leading to a final sample of 27 children with ADHD (age: 10.6±1.8years, range 7.3-15.5 years) and 49 TD controls (age: 11.1±2.3years, range 6.1-15.6 years) (Table S1). Nine patients with ADHD had autism spectrum disorder, 6 ADHD patients had oppositional defiant disorder, 2 had specific learning disorder, and 1 had developmental coordination disorder as comorbid disorders. While one of the patients with ADHD was medication-naïve, 25 were medicated with OROS-MPH (medication period was 22.2±15.3 months, range 1-58 months), three with atomoxetine, and two with aripiprazole. Children with ADHD took their regularly prescribed medications between the two visits, but all participants were medication-free prior to MRI for at least 5 times half-life, including methylphenidate and atomoxetine, consistent with protocols from previous studies (
      • Mizuno Y.
      • Jung M.
      • Fujisawa T.X.
      • Takiguchi S.
      • Shimada K.
      • Saito D.N.
      • et al.
      Catechol-O-methyltransferase polymorphism is associated with the cortico-cerebellar functional connectivity of executive function in children with attention-deficit/hyperactivity disorder.
      ,
      • Fair D.A.
      • Posner J.
      • Nagel B.J.
      • Bathula D.
      • Dias T.G.C.
      • Mills K.L.
      • et al.
      Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder.
      ).

      Assessment of attention and cognitive control

      A standardized CPT (
      • Huang-Pollock C.L.
      • Karalunas S.L.
      • Tam H.
      • Moore A.N.
      Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance.
      ,
      • Shin M.S.
      • Cho S.
      • Chun S.Y.
      • Hong K.-E.M.
      A study of the development and standardization of ADHD Diagnostic system.
      ) was administered to children with ADHD outside the MRI scanner under both methylphenidate and placebo conditions. The task consisted of a Go/NoGo paradigm in which children were presented with either a target or non-target stimulus on the screen for 100 msec, once every 2 seconds for 15 minutes across three 5-minute blocks. The target stimulus was a triangle, while the non-target stimulus was either a circle or a square. Children were required to press a button when a target stimulus was presented, and withhold response to non-targets. The test has been normed to age-adjusted T-scores on four distinct performance measures: omission errors, commission errors, mean response time (RT), and IIRV, which were quantified using RT standard deviation (
      • Huang-Pollock C.L.
      • Karalunas S.L.
      • Tam H.
      • Moore A.N.
      Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance.
      ,
      • Shin M.S.
      • Cho S.
      • Chun S.Y.
      • Hong K.-E.M.
      A study of the development and standardization of ADHD Diagnostic system.
      ). We examined medication-induced performance differences using paired t-tests.

      fMRI data acquisition

      Functional images were acquired with a T2*-weighted gradient-echo echo-planar imaging (EPI) sequence via a 3-T scanner (Discovery MR 750; General Electric Medical Systems, Milwaukee, WI) and a 32-channnel head coil. In total, 201 volumes were acquired for a scanning time of 7 minutes 42 seconds. Each volume consisted of 40 slices, with a thickness of 3.5 mm and a 0.5-mm gap. The time interval between each successive acquisition of the same slice (repetition time, TR) was 2300 ms, with an echo time (TE) of 30 ms, and a flip angle (FA) of 81°. The field of view (FOV) was 192 × 192 mm, and the matrix size was 64 × 64, yielding volume dimensions of 3 × 3 mm. The participants were instructed to stay awake with their eyes closed.

      fMRI data pre-processing

      Resting state fMRI data were analyzed using SPM12 and DPARSF (
      • Chao-Gan Y.
      • Yu-Feng Z.
      DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI.
      ). First, the initial 10 volumes were discarded, and slice-timing correction was performed. The signal from each slice was realigned temporally to that obtained from the middle slice using sinc interpolation. The re-sliced volumes were normalized to the Montreal Neurological Institute space with a voxel size of 2 × 2 × 2 mm using the EPI template provided by SPM12. The normalized images were spatially smoothed with a 6-mm Gaussian kernel. Next, the non-neural noise in the time series was controlled, and several sources of spurious variance (e.g., the Friston 24-parameter model) were removed from the data through linear regression.

      fMRI data analysis

      Our overall analysis is illustrated in Figure 1A and summarized below (see Supplemental Methods for details).
      Figure thumbnail gr1
      Figure 1(A) Data analysis pipeline. We first computed ALFF within the bilateral NAc and three brain networks implicated in ADHD: SN, DMN, and left and right FPN. Paired t-tests were used to examine the medication effects (ADHD in methylphenidate versus placebo conditions) and two-sample t-tests were used to examine the difference between ADHD and TD controls. Second, we conducted ALFF pattern similarity analysis (illustrated in detail in Panel B) to quantify the extent to which ALFF values are similar between children with ADHD and TD children, and examined whether children with ADHD whose post-medication spontaneous activity patterns are more similar to TD children would exhibit greater improvement in IIRV with medication. Third, we used classification analysis to test whether the multivariate pattern of ALFF in the NAc and the three brain networks could distinguish children with ADHD in medication or placebo conditions (primary cohort) and crucially whether this can be replicated in another independent dataset (replication cohort). (B) Overview of ALFF pattern similarity analysis between children with ADHD and TD controls. We first computed the correlation between ALFF values within SN or DMN from each child with ADHD and those from the mean ALFF map in the TD group. The correlation coefficient was standardized using Fisher’s r-to-z transformation. Next, we calculated methylphenidate-induced changes in the similarity measures of ALFF in the SN or DMN between ADHD-Placebo and ADHD-MPH conditions. Higher values indicate that medication leads to more TD-like spontaneous neural activity patterns. ADHD-MPH: children with attention-deficit/hyperactivity disorder under methylphenidate administration; ADHD-Placebo: children with attention-deficit/hyperactivity disorder under placebo; ALFF: amplitude of low-frequency fluctuations; DMN: default mode network; IIRV: intra-individual response variability; LFPN: left frontoparietal network; NAc: nucleus accumbens; RFPN: right frontoparietal network; ROI: region of interest; SN: salience network; TD: typically developing.
      Brain regions and networks of interest. We focused on the NAc, a key node in the reward pathway, and the SN, DMN, and FPN, three core brain systems involved in cognitive control. Probabilistic masks of the bilateral NAc were obtained from an independent high-resolution structural study, and the masks were thresholded at 0.9 (
      • Pauli W.M.
      • Nili A.N.
      • Tyszka J.M.
      A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei.
      ). The SN, DMN, left FPN, and right FPN maps were obtained from a previous study (
      • Menon V.
      Large-scale brain networks and psychopathology: a unifying triple network model.
      ). To test the robustness of our findings, we applied independent component analysis to generate another set of network masks for SN, DMN, left FPN, and right FPN, using the analytic approach used in our previous study (
      • Cai W.
      • Chen T.
      • Szegletes L.
      • Supekar K.
      • Menon V.
      Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits.
      ).
      ALFF analysis. We assessed spontaneous neural activity by computing ALFF in bilateral NAc, SN, DMN, left FPN, and right FPN. Paired t-tests were used to examine the medication effects (ADHD-MPH versus ADHD-Placebo) and two-sample t-tests were used to examine the difference between ADHD and TD controls.
      ALFF pattern similarity analysis. We evaluated the extent to which ALFF values are similar between children with ADHD and TD children in the SN, DMN, and FPN. We then determined how ALFF similarity is modulated by medication, and determined its relation with medication-induced changes in behavior. We computed an ALFF similarity metric (
      • Cai W.
      • Duberg K.
      • Padmanabhan A.
      • Rehert R.
      • Bradley T.
      • Carrion V.
      • Menon V.
      Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children.
      ) (Figure 1B) using z-transformed Pearson’s correlation between ALFF values within each brain network (SN, DMN, or FPN) from each child with ADHD and those from the averaged ALFF map in the TD group. This metric captures the similarity of ALFF patterns in each child with ADHD with respect to the expected patterns in the TD group, in each brain region or network of interest. A higher ALFF similarity value indicates that the child with ADHD has a more TD-like ALFF spatial pattern of ALFF. Medication effect was calculated by subtracting z-transformed correlation coefficients in ADHD-Placebo from ADHD-MPH conditions. A positive value indicates that medication leads to a more TD-like ALFF spatial pattern. We tested whether medication effects on the ALFF patterns are associated with a behavioral measure of attention and cognitive control, the IIRV, using Pearson’s correlation.

      Replication of methylphenidate effects on spontaneous neural activity patterns using multivariate analysis

      Finally, we evaluated the replicability of methylphenidate effects on spontaneous neural activity patterns using a second independent cohort of children with ADHD who participated in a similar randomized controlled study involving single-dose methylphenidate treatment. Details of participants and study design are reported elsewhere (
      • Silk T.J.
      • Malpas C.
      • Vance A.
      • Bellgrove M.A.
      The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD.
      ) and summarized in the Supplemental Methods and Table S3. To overcome the limitations of small sample size in the secondary cohort (N=15), we used a multivariate pattern analysis strategy which facilitates greater reproducibility in comparison to univariate voxel-wise measures (

      Spisak T, Bingel U, Wager T (2022): Replicable multivariate BWAS with moderate sample sizes. bioRxiv 2022.06.22.497072.

      ). Specifically, we sought to determine whether methylphenidate would modulate multivariate patterns of ALFF activity in the NAc, SN, DMN, and FPN.

      Results

      Methylphenidate improves attention and cognitive control function

      Methylphenidate significantly reduced omission errors, mean RT, and IIRV in the CPT in children with ADHD (all ps < 0.001) (see Supplemental Results and Figure S2 for details).

      Methylphenidate effects on spontaneous neural activity in NAc

      ALFF in the right NAc in ADHD-MPH was significantly higher than ADHD-Placebo condition (p < 0.05, Bonferroni corrected Cohen's d = 0.55) (Figure 2A) (see Supplemental Results and Figure S3A for comparisons with TD controls). These results suggest that methylphenidate enhances spontaneous neural activity in the right NAc.
      Figure thumbnail gr2
      Figure 2Methylphenidate modulates spontaneous neural activity in the nucleus accumbens (NAc) and cognitive control networks. (A) Methylphenidate increases ALFF in the right NAc (p < 0.05, Bonferroni corrected, Cohen's d =0.43), but not in the left NAc. (B) Methylphenidate increases ALFF in the default mode network (DMN) (p < 0.01, Bonferroni corrected, Cohen's d =0.66) and salience network (SN) (p < 0.05, Cohen's d = 0.57), but not in the left and right frontoparietal network (FPN). ADHD-MPH: children with attention-deficit/hyperactivity disorder under methylphenidate administration; ADHD-Placebo: children with attention-deficit/hyperactivity disorder under placebo; ALFF: amplitude of low-frequency fluctuation. **p < 0.01; *p < 0.05; n.s, not significant.

      Methylphenidate effects on spontaneous neural activity in SN, FPN, and DMN

      ALFF in the SN and DMN in ADHD-MPH were significantly higher than ADHD-Placebo condition (SN, p < 0.05, Bonferroni corrected, Cohen's d =0.57; DMN, p < 0.01, Bonferroni corrected, Cohen's d = 0.66). There was no significant difference in the left and right FPN (p > 0.05) (Figure 2B) (see Supplemental Results and Figure S3B for comparisons with TD controls). Results were replicated using alternate SN, DMN, left FPN, and right FPN masks (see Supplemental Results and Figure S4 for details). These results suggest that methylphenidate enhances spontaneous neural activity in the SN and DMN.

      Relationship between methylphenidate-induced changes in spontaneous neural activity and changes in response variability

      We focused on the SN and DMN as these two networks showed significant effects of medication on the mean ALFF. We found that medication-induced changes in IIRV were significantly correlated with medication-induced changes in spontaneous activity patterns in the DMN (r = -0.46, p < 0.05, Bonferroni corrected, Figure 3), but not in the SN (r = -0.34, p = 0.080). Additional analysis confirmed that the relationship between changes in IIRV and changes in DMN ALFF was robust against several potential confounds (Table 1). Results were replicated using an alternate DMN mask (see Supplemental Results, Figure S5, and Table S2 for details). These results suggest that greater similarity with TD-like ALFF patterns in the DMN post-medication is associated with more stable behavioral performance in children with ADHD.
      Figure thumbnail gr3
      Figure 3Methylphenidate modulation of spontaneous neural activity in the default mode network (DMN) predicts the medication effect on intra-individual response variability (IIRV) (r = -0.46, p = 0.016). MPH: methylphenidate.
      Table 1Multiple linear regression analysis revealed that only methylphenidate modulation of ALFF similarity pattern within DMN is significantly associated with medication effects on IIRV.
      Methylphenidate induced difference in IIRV
      βtp
      Methylphenidate effects on ALFF similarity pattern within DMN-50.587-2.3330.029*
      Age1.7621.6150.121
      Handedness-5.553-0.7530.460
      FSIQ-0.220-0.9700.342
      ALFF: amplitude of low-frequency fluctuation; DMN: default mode network; FSIQ: full scale intelligence quotient; IIRV: intra-individual response variability. *p < 0.05.

      Replication of methylphenidate effects on spontaneous neural activity patterns

      Multivariate classification analysis revealed that ALFF differentiated ADHD-MPH and ADHD-Placebo conditions in the primary cohort in right NAc (accuracy = 70%, p = 0.02), SN (accuracy = 74%, p = 0.002), and DMN (accuracy = 82%, p = 0.002). A similar differentiation was observed in the replication cohort: right NAc (accuracy = 87%, p = 0.002), SN (accuracy = 73%, p = 0.002), and DMN (accuracy = 73%, p = 0.002) (Figure 4, Supplemental Tables S4). These analyses demonstrate the robustness of our key findings related to methylphenidate-induced changes in spontaneous neural activity patterns in the NAc, SN, and DMN across two independent cohorts.
      Figure thumbnail gr4
      Figure 4Methylphenidate modulates spontaneous neural activity in the nucleus accumbens (NAc), salience network (SN), default mode network (DMN), and frontoparietal network (FPN) in children with ADHD: Replicable evidence from multivariate classification analyses of primary and replication cohorts. In both the primary and replication cohorts, multivariate patterns of ALFF in the right NAc, SN, DMN, and right FPN (RFPN) distinguish ADHD-MPH from ADHD-Placebo conditions. Statistical significance of classification accuracy was estimated using permutation tests. ADHD-MPH: children with attention-deficit/hyperactivity disorder under methylphenidate treatment; ADHD-Placebo: children with attention-deficit/hyperactivity disorder under placebo; LFPN: left frontoparietal network; **p < 0.01; *p < 0.05.

      Discussion

      We examined whether methylphenidate alters spontaneous neural activity in the mesolimbic dopaminergic system and cognitive control networks, and how these alterations impact cognitive flexibility in children with ADHD. Using a randomized placebo-controlled double-blind crossover design, with sample sizes larger than extant randomized controlled studies (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ), we show that methylphenidate alters spontaneous activity in the NAc as well as the SN and DMN, two large-scale cognitive control networks implicated in attention and cognitive control deficits in ADHD. Importantly, methylphenidate-induced changes in spontaneous activity patterns in the DMN were associated with improvements in intra-individual response variability during a sustained attention task. Finally, in advance over previous studies, we discovered that methylphenidate alters spontaneous neural activity patterns in the NAc, SN and DMN and demonstrated replication across two independent cohorts of children with ADHD. Together, these findings identify a novel neural mechanism underlying methylphenidate treatment in ADHD.

      Methylphenidate modulates spontaneous activity in the nucleus accumbens

      Prominent theories of ADHD have emphasized deficits in the reward and motivation system (
      • Haenlein M.
      • Caul W.F.
      Attention deficit disorder with hyperactivity: a specific hypothesis of reward dysfunction.
      ,
      • Sonuga-Barke E.J.S.
      Causal models of attention-deficit/hyperactivity disorder: from common simple deficits to multiple developmental pathways.
      ,
      • Tripp G.
      • Wickens J.R.
      Research review: dopamine transfer deficit: a neurobiological theory of altered reinforcement mechanisms in ADHD.
      ,
      • Luman M.
      • Tripp G.
      • Scheres A.
      Identifying the neurobiology of altered reinforcement sensitivity in ADHD: A review and research agenda.
      ). This hypothesis is supported by behavioral findings of aberrant delay discounting, i.e. preference of a small immediate reward over a large delayed reward in children with ADHD, and abnormal activation in regions of dopamine reward circuitry during anticipation or processing of rewards in children with ADHD (
      • Mizuno K.
      • Yoneda T.
      • Komi M.
      • Hirai T.
      • Watanabe Y.
      • Tomoda A.
      Osmotic release oral system-methylphenidate improves neural activity during low reward processing in children and adolescents with attention-deficit/hyperactivity disorder.
      ,
      • Plichta M.M.
      • Scheres A.
      Ventral-striatal responsiveness during reward anticipation in ADHD and its relation to trait impulsivity in the healthy population: a meta-analytic review of the fMRI literature.
      ). As a key node of the dopaminergic reward pathway, the NAc plays an important role in these processes (
      • Knutson B.
      • Adams C.M.
      • Fong G.W.
      • Hommer D.
      Anticipation of increasing monetary reward selectively recruits nucleus accumbens.
      ,
      • Liu X.
      • Hairston J.
      • Schrier M.
      • Fan J.
      Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies.
      ).
      In the present study, we first examined whether methylphenidate alters the spontaneous neural activity of the NAc. We found that, compared to placebo, methylphenidate increased spontaneous activity in the NAc in children with ADHD. Our results converge with findings from PET studies which have reported methylphenidate-induced dopamine increases in the ventral striatum in adults with ADHD (
      • Volkow N.D.
      • Wang G.-J.
      • Tomasi D.
      • Kollins S.H.
      • Wigal T.L.
      • Newcorn J.H.
      • et al.
      Methylphenidate-elicited dopamine increases in ventral striatum are associated with long-term symptom improvement in adults with attention deficit hyperactivity disorder.
      ). Due to the use of radioactive ligands, PET imaging studies cannot be conducted in children. This is an impediment to investigations of methylphenidate-induced dopamine changes in children with ADHD at ages closer to clinical diagnosis, but ALFF measures may offer a useful alternative. In contrast to PET, results with fMRI provide greater anatomical precision and localize methylphenidate-induced effects specifically to the NAc within the ventral striatum. In line with our results, methylphenidate has been reported to increase spontaneous activity in rodent NAc (
      • Easton N.
      • Marshall F.H.
      • Marsden C.A.
      • Fone K.C.F.
      Mapping the central effects of methylphenidate in the rat using pharmacological MRI BOLD contrast.
      ) and a recent study in non-human primates found that the therapeutic effect of methylphenidate on impulsive decision is associated with the pharmacological action on the dopamine transporter in the NAc (

      Martinez E, Pasquereau B, Drui G, Saga Y, Météreau É, Tremblay L (2020): Ventral striatum supports Methylphenidate therapeutic effects on impulsive choices expressed in temporal discounting task. Sci Reports 2020 101 10: 1–11.

      ). Similarly, in both children and adults with ADHD, methylphenidate has been reported to modify abnormal striatal activity during reward processing (
      • Mizuno K.
      • Yoneda T.
      • Komi M.
      • Hirai T.
      • Watanabe Y.
      • Tomoda A.
      Osmotic release oral system-methylphenidate improves neural activity during low reward processing in children and adolescents with attention-deficit/hyperactivity disorder.
      ,
      • Rubia K.
      • Halari R.
      • Cubillo A.
      • Mohammad A.-M.
      • Brammer M.
      • Taylor E.
      Methylphenidate normalises activation and functional connectivity deficits in attention and motivation networks in medication-naïve children with ADHD during a rewarded continuous performance task.
      ,
      • Aarts E.
      • van Holstein M.
      • Hoogman M.
      • Onnink M.
      • Kan C.
      • Franke B.
      • et al.
      Reward modulation of cognitive function in adult attention-deficit/hyperactivity disorder: a pilot study on the role of striatal dopamine.
      ,
      • Furukawa E.
      • da Costa R.Q.M.
      • Bado P.
      • Hoefle S.
      • Vigne P.
      • Monteiro M.
      • et al.
      Methylphenidate modifies reward cue responses in adults with ADHD: An fMRI study.
      ). Together, these findings demonstrate that methylphenidate has a strong effect on spontaneous neural activity in the NAc, a key node in the mesolimbic reward pathway and that the ALFF might be a useful proxy measure to probe methylphenidate effects in children with ADHD.

      Methylphenidate modulates spontaneous activity in the salience and default mode networks

      Next, we examined the parallel effects of methylphenidate-induced changes on the SN, FPN, and DMN, three large-scale cognitive control networks implicated in ADHD and in attention and cognitive control more broadly (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ,
      • Cai W.
      • Ryali S.
      • Chen T.
      • Li C.-S.R.
      • Menon V.
      Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.
      ,
      • Jilka S.R.
      • Scott G.
      • Ham T.
      • Pickering A.
      • Bonnelle V.
      • Braga R.M.
      • et al.
      Damage to the Salience Network and interactions with the Default Mode Network.
      ,
      • Cai W.
      • Warren S.L.
      • Duberg K.
      • Pennington B.
      • Hinshaw S.P.
      • Menon V.
      Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
      ,
      • Cai W.
      • Duberg K.
      • Padmanabhan A.
      • Rehert R.
      • Bradley T.
      • Carrion V.
      • Menon V.
      Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children.
      ). We found that methylphenidate also increases spontaneous activity in the SN and DMN. Key nodes of the SN, including the anterior insula and anterior cingulate cortex, are among the most highly activated regions in a variety of attention and cognitive control tasks (
      • Cai W.
      • Ryali S.
      • Chen T.
      • Li C.-S.R.
      • Menon V.
      Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.
      ,
      • Wager T.D.
      • Sylvester C.-Y.C.
      • Lacey S.C.
      • Nee D.E.
      • Franklin M.
      • Jonides J.
      Common and unique components of response inhibition revealed by fMRI.
      ). Weak activation in the anterior insula and anterior cingulate cortex during cognitive control, especially on error trials, has been reported in children with ADHD (
      • Cai W.
      • Griffiths K.
      • Korgaonkar M.S.
      • Williams L.M.
      • Menon V.
      Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.
      ). Increased attention and cognitive control demand is also accompanied with deactivation in the DMN (
      • Cai W.
      • Ryali S.
      • Pasumarthy R.
      • Talasila V.
      • Menon V.
      Dynamic causal brain circuits during working memory and their functional controllability.
      ,
      • Mayer J.S.
      • Roebroeck A.
      • Maurer K.
      • Linden D.E.J.
      Specialization in the default mode: Task-induced brain deactivations dissociate between visual working memory and attention.
      ,
      • Harrison B.J.
      • Pujol J.
      • López-Solà M.
      • Hernández-Ribas R.
      • Deus J.
      • Ortiz H.
      • et al.
      Consistency and functional specialization in the default mode brain network.
      ), and abnormal DMN activity during cognitively demanding tasks is a reproducible feature of ADHD (
      • Hart H.
      • Radua J.
      • Nakao T.
      • Mataix-Cols D.
      • Rubia K.
      Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects.
      ). In adults with ADHD, methylphenidate has been shown to increase intrinsic functional connectivity within DMN regions (
      • Picon F.A.
      • Sato J.R.
      • Anés M.
      • Vedolin L.M.
      • Mazzola A.A.
      • Valentini B.B.
      • et al.
      Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD.
      ), and enhance deactivation of the DMN regions during attentional tasks (
      • Tomasi D.
      • Volkow N.D.
      • Wang G.J.
      • Wang R.
      • Telang F.
      • Caparelli E.C.
      • et al.
      Methylphenidate enhances brain activation and deactivation responses to visual attention and working memory tasks in healthy controls.
      ). Our results extend these findings and suggest that one mechanism by which methylphenidate alters cognitive control function is by enhancing spontaneous activity in both the SN and DMN in children with ADHD.

      Methylphenidate improves behavioral performance by modulating spontaneous activity in the DMN

      Cognitive control dysfunction is a prominent feature of ADHD and we recently showed that inattention is correlated with IIRV (
      • Cai W.
      • Warren S.L.
      • Duberg K.
      • Pennington B.
      • Hinshaw S.P.
      • Menon V.
      Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
      ), a key intermediate phenotype of childhood ADHD (
      • Castellanos F.X.
      • Tannock R.
      Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes.
      ). Several studies have shown that, compared to controls, children with ADHD display increased IIRV during cognitive task performance (
      • Kofler M.J.
      • Rapport M.D.
      • Sarver D.E.
      • Raiker J.S.
      • Orban S.A.
      • Friedman L.M.
      • Kolomeyer E.G.
      Reaction time variability in ADHD: a meta-analytic review of 319 studies.
      ,
      • Lijffijt M.
      • Kenemans J.L.
      • Verbaten M.N.
      • van Engeland H.
      A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: deficient inhibitory motor control?.
      ). We used a novel multivariate pattern similarity measure (
      • Cai W.
      • Duberg K.
      • Padmanabhan A.
      • Rehert R.
      • Bradley T.
      • Carrion V.
      • Menon V.
      Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children.
      ) to determine whether children with ADHD whose spontaneous activity patterns are more similar to TD controls after methylphenidate treatment would exhibit greater improvements in IIRV with medication. Our analysis revealed that higher similarity of ALFF patterns in DMN between children with ADHD and TD controls was associated with a greater reduction in IIRV in children with ADHD. Previous task-based fMRI studies have reported that activity in DMN during cognitive performance was related to IIRV and psychostimulants alter the DMN activity in youth with ADHD (
      • Fassbender C.
      • Zhang H.
      • Buzy W.M.
      • Cortes C.R.
      • Mizuiri D.
      • Beckett L.
      • Schweitzer J.B.
      A lack of default network suppression is linked to increased distractibility in ADHD.
      ,
      • Peterson B.S.
      • Potenza M.N.
      • Wang Z.
      • Zhu H.
      • Martin A.
      • Marsh R.
      • et al.
      An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD.
      ). Our results suggest that the alteration in spontaneous activity in the DMN is a plausible mechanism by which methylphenidate alleviates cognitive inflexibility in children with ADHD. Our results also highlight the specificity of the DMN in terms of its unique association with the effects of medication on IIRV, and provide novel evidence that methylphenidate actions on the DMN contribute to remediation of core attention and cognitive control deficits in ADHD (
      • Peterson B.S.
      • Potenza M.N.
      • Wang Z.
      • Zhu H.
      • Martin A.
      • Marsh R.
      • et al.
      An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD.
      ,
      • Sonuga-Barke E.J.S.
      • Castellanos F.X.
      Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis.
      ).

      Methylphenidate modulates multivariate spontaneous neural activity patterns

      Replication across two independent cohorts

      Lack of converging evidence across independent studies is a challenge in clinical neuroscience research, especially in the domain of pharmacological interventions (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ). To address this challenge, we sought to replicate key findings in a second cohort of participants from a previously published study (
      • Silk T.J.
      • Malpas C.
      • Vance A.
      • Bellgrove M.A.
      The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD.
      ). Because of the small sample size in the replication cohort (N=15), we used a multivariate pattern analysis approach which has been shown to yield more replicable results than univariate methods (

      Spisak T, Bingel U, Wager T (2022): Replicable multivariate BWAS with moderate sample sizes. bioRxiv 2022.06.22.497072.

      ). Using such an approach, here we report the unprecedented replication of findings in two neuroimaging clinical trial cohorts acquired independently. Our analyses revealed that multivariate patterns of spontaneous activity in the NAc as well as in the SN, DMN are modulated by methylphenidate in children with ADHD in both the primary and secondary cohorts. To the best of our knowledge (
      • Pereira-Sanchez V.
      • Franco A.R.
      • Vieira D.
      • de Castro-Manglano P.
      • Soutullo C.
      • Milham M.P.
      • Castellanos F.X.
      Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
      ), our replication is the first of its kind and provides confirmatory evidence that methylphenidate alters spontaneous neural activity in key reward and cognitive control systems implicated in childhood ADHD.

      Limitations and future work

      One limitation of the present study is that fMRI measures cannot establish direct links to changes in dopamine. Future work with hybrid PET-MRI techniques that enable multimodal imaging of different neurotransmitter systems (
      • Zimmer L.
      Contribution of Clinical Neuroimaging to the Understanding of the Pharmacology of Methylphenidate.
      ) is needed to investigate the impact of methylphenidate on dopamine as well as other neurotransmitters such as norepinephrine and their relation to spontaneous fluctuations in fMRI signals. Because PET-fMRI studies can only be conducted in adults due to the use of radioactive ligands, the characterization of methylphenidate effects on different neurotransmitter systems in children remains a challenge. As with extant ADHD brain imaging studies, children with ADHD in our study were not drug naïve, were male, and spanned a wide range from 5 to 16. Larger multi-cohort studies that include drug naïve males and females with ADHD are needed to determine how medication history, sex, and development stage modulate methylphenidate effects and to further assess the robustness of the effects reported here.

      Conclusion

      Our randomized, placebo-controlled double-blind crossover study revealed that methylphenidate increases spontaneous brain activity in the reward system at the regional level, and in the salience and default mode networks at the network level. Using a novel ALFF similarity metric, we show that the methylphenidate effect on spontaneous activity patterns in the default mode network is associated with the effect of medication on intra-individual response variability. Strikingly, multivariate analysis demonstrated replicable patterns of methylphenidate-induced changes in spontaneous activity patterns in two independent cohorts of children with ADHD. Our findings advance the current understanding of the neurobiological mechanisms underlying methylphenidate treatment in children with ADHD and may lead to clinically useful biomarkers for evaluating treatment response. Finally, our study provides a template for investigations of the effects of methylphenidate on task-related neural activity in striatal reward and related cognitive control circuitry in children with ADHD.

      Uncited reference

      • Han Y.
      • Wang J.
      • Zhao Z.
      • Min B.
      • Lu J.
      • Li K.
      • et al.
      Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: a resting-state fMRI study.
      .

      Acknowledgements

      This work was supported by Japan Society for the Promotion of Science (JSPS) Overseas Research Fellowships (#201960003), a Grant-in-Aid for Scientific Research (A)(B), Challenging Exploratory Research, and Young Scientists from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan (#17K19898 and #19H00617 to A.T., and #16K16621, #18K13106, and # 21K02380 to Y.M.), a research grant from the Life Cycle Medicine from Faculty of Medical Sciences, University of Fukui to A.T., research grants from Japan-United States Brain Research Cooperation Program to A.T., and Japan Agency for Medical Research and Development (AMED) under Grant Number JP20gk0110052 to A.T. This work was also supported by Stanford Maternal & Child Health Research Institute Clinician Educator Grant to W.C., Stanford Innovator award to K.S., and grants from the NIH to W.C. (MH124816), K.S. (AG072114) and V.M. (NS086085, EB022907, MH084164).

      References

        • McLennan J.D.
        Understanding attention deficit hyperactivity disorder as a continuum.
        Can Fam Physician. 2016; 62: 979-982
        • Posner J.
        • Polanczyk G.V.
        • Sonuga-Barke E.
        Attention-deficit hyperactivity disorder.
        Lancet. 2020; 395: 450-462
        • Engert V.
        • Pruessner J.C.
        Dopaminergic and noradrenergic contributions to functionality in ADHD: the role of methylphenidate.
        Curr Neuropharmacol. 2008; 6: 322-328
        • Arnsten A.F.T.
        Stimulants: Therapeutic actions in ADHD.
        Neuropsychopharmacology. 2006; 31: 2376-2383
        • Volkow N.D.
        • Wang G.-J.
        • Kollins S.H.
        • Wigal T.L.
        • Newcorn J.H.
        • Telang F.
        • et al.
        Evaluating dopamine reward pathway in ADHD: clinical implications.
        JAMA. 2009; 302: 1084-1091
        • Volkow N.D.
        • Wang G.-J.
        • Newcorn J.
        • Telang F.
        • Solanto M.V.
        • Fowler J.S.
        • et al.
        Depressed dopamine activity in caudate and preliminary evidence of limbic involvement in adults with attention-deficit/hyperactivity disorder.
        Arch Gen Psychiatry. 2007; 64: 932-940
        • Faraone S.V.
        The pharmacology of amphetamine and methylphenidate: Relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities.
        Neurosci Biobehav Rev. 2018; 87: 255-270
        • Bromberg-Martin E.S.
        • Matsumoto M.
        • Hikosaka O.
        Dopamine in motivational control: rewarding, aversive, and alerting.
        Neuron. 2010; 68: 815-834
        • Stoy M.
        • Schlagenhauf F.
        • Schlochtermeier L.
        • Wrase J.
        • Knutson B.
        • Lehmkuhl U.
        • et al.
        Reward processing in male adults with childhood ADHD-a comparison between drug-naïve and methylphenidate-treated subjects.
        Psychopharmacology (Berl). 2011; 215: 467-481
        • Coghill D.R.
        • Seth S.
        • Pedroso S.
        • Usala T.
        • Currie J.
        • Gagliano A.
        Effects of methylphenidate on cognitive functions in children and adolescents with attention-deficit/hyperactivity disorder: evidence from a systematic review and a meta-analysis.
        Biol Psychiatry. 2014; 76: 603-615
        • Tamminga H.G.H.
        • Reneman L.
        • Huizenga H.M.
        • Geurts H.M.
        Effects of methylphenidate on executive functioning in attention-deficit/hyperactivity disorder across the lifespan: a meta-regression analysis.
        Psychol Med. 2016; 46: 1791-1807
        • Mueller A.
        • Hong D.S.
        • Shepard S.
        • Moore T.
        Linking ADHD to the Neural Circuitry of Attention.
        Trends Cogn Sci. 2017; 21: 474-488
        • Pereira-Sanchez V.
        • Franco A.R.
        • Vieira D.
        • de Castro-Manglano P.
        • Soutullo C.
        • Milham M.P.
        • Castellanos F.X.
        Systematic Review: Medication Effects on Brain Intrinsic Functional Connectivity in Patients With Attention-Deficit/Hyperactivity Disorder.
        J Am Acad Child Adolesc Psychiatry. 2021; 60: 222-235
        • McCutcheon R.A.
        • Nour M.M.
        • Dahoun T.
        • Jauhar S.
        • Pepper F.
        • Expert P.
        • et al.
        Mesolimbic Dopamine Function Is Related to Salience Network Connectivity: An Integrative Positron Emission Tomography and Magnetic Resonance Study.
        Biol Psychiatry. 2019; 85: 368-378
        • Menon V.
        • Uddin L.Q.
        Saliency, switching, attention and control: a network model of insula function.
        Brain Struct Funct. 2010; 214: 655-667
        • Cai W.
        • Ryali S.
        • Chen T.
        • Li C.-S.R.
        • Menon V.
        Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets.
        J Neurosci. 2014; 34: 14652-14667
        • Cai W.
        • Chen T.
        • Ide J.S.
        • Li C.-S.R.
        • Menon V.
        Dissociable Fronto-Operculum-Insula Control Signals for Anticipation and Detection of Inhibitory Sensory Cue.
        Cereb Cortex. 2017; 27: 4073-4082
        • Seeley W.W.
        • Menon V.
        • Schatzberg A.F.
        • Keller J.
        • Glover G.H.
        • Kenna H.
        • et al.
        Dissociable intrinsic connectivity networks for salience processing and executive control.
        J Neurosci. 2007; 27: 2349-2356
      1. Menon V (2015): Salience Network. Brain Mapping: An Encyclopedic Reference, vol. 2. Elsevier Inc. https://doi.org/10.1016/B978-0-12-397025-1.00052-X

        • Taghia J.
        • Cai W.
        • Ryali S.
        • Kochalka J.
        • Nicholas J.
        • Chen T.
        • Menon V.
        Uncovering hidden brain state dynamics that regulate performance and decision-making during cognition.
        Nat Commun. 2018; 9https://doi.org/10.1038/s41467-018-04723-6
        • Cai W.
        • Ryali S.
        • Pasumarthy R.
        • Talasila V.
        • Menon V.
        Dynamic causal brain circuits during working memory and their functional controllability.
        Nat Commun. 2021; 12: 3314
        • Rubia K.
        • Alegria A.A.
        • Cubillo A.I.
        • Smith A.B.
        • Brammer M.J.
        • Radua J.
        Effects of stimulants on brain function in attention-deficit/hyperactivity disorder: A systematic review and meta-analysis.
        Biol Psychiatry. 2014; 76: 616-628
        • Cai W.
        • Griffiths K.
        • Korgaonkar M.S.
        • Williams L.M.
        • Menon V.
        Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.
        Mol Psychiatry. 2019; https://doi.org/10.1038/s41380-019-0564-4
        • Menon V.
        Large-scale brain networks and psychopathology: a unifying triple network model.
        Trends Cogn Sci. 2011; 15: 483-506
        • Cai W.
        • Chen T.
        • Szegletes L.
        • Supekar K.
        • Menon V.
        Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits.
        Biol psychiatry Cogn Neurosci neuroimaging. 2018; 3: 263-273
        • Jilka S.R.
        • Scott G.
        • Ham T.
        • Pickering A.
        • Bonnelle V.
        • Braga R.M.
        • et al.
        Damage to the Salience Network and interactions with the Default Mode Network.
        J Neurosci. 2014; 34: 10798-10807
        • Zang Y.-F.
        • He Y.
        • Zhu C.-Z.
        • Cao Q.-J.
        • Sui M.-Q.
        • Liang M.
        • et al.
        Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI.
        Brain Dev. 2007; 29: 83-91
        • Tomasi D.
        • Wang G.-J.
        • Volkow N.D.
        Energetic cost of brain functional connectivity.
        Proc Natl Acad Sci U S A. 2013; 110: 13642-13647
        • Attwell D.
        • Laughlin S.B.
        An energy budget for signaling in the grey matter of the brain.
        J Cereb Blood Flow Metab. 2001; 21: 1133-1145
        • Han Y.
        • Wang J.
        • Zhao Z.
        • Min B.
        • Lu J.
        • Li K.
        • et al.
        Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: a resting-state fMRI study.
        Neuroimage. 2011; 55: 287-295
        • Yang L.
        • Yan Y.
        • Wang Y.
        • Hu X.
        • Lu J.
        • Chan P.
        • et al.
        Gradual Disturbances of the Amplitude of Low-Frequency Fluctuations (ALFF) and Fractional ALFF in Alzheimer Spectrum.
        Front Neurosci. 2018; 12: 975
        • Fox M.D.
        • Raichle M.E.
        Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.
        Nat Rev Neurosci. 2007; 8: 700-711
        • Kofler M.J.
        • Rapport M.D.
        • Sarver D.E.
        • Raiker J.S.
        • Orban S.A.
        • Friedman L.M.
        • Kolomeyer E.G.
        Reaction time variability in ADHD: a meta-analytic review of 319 studies.
        Clin Psychol Rev. 2013; 33: 795-811
        • Lijffijt M.
        • Kenemans J.L.
        • Verbaten M.N.
        • van Engeland H.
        A meta-analytic review of stopping performance in attention-deficit/hyperactivity disorder: deficient inhibitory motor control?.
        J Abnorm Psychol. 2005; 114: 216-222
        • Cai W.
        • Warren S.L.
        • Duberg K.
        • Pennington B.
        • Hinshaw S.P.
        • Menon V.
        Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention.
        Mol Psychiatry. 2021; 2021: 1-14
        • Wen X.
        • Liu Y.
        • Yao L.
        • Ding M.
        Top-down regulation of default mode activity in spatial visual attention.
        J Neurosci. 2013; 33: 6444-6453
        • Silk T.J.
        • Malpas C.
        • Vance A.
        • Bellgrove M.A.
        The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD.
        Brain Imaging Behav. 2017; 11: 1422-1431
      2. Spisak T, Bingel U, Wager T (2022): Replicable multivariate BWAS with moderate sample sizes. bioRxiv 2022.06.22.497072.

        • Wilens T.
        • McBurnett K.
        • Stein M.
        • Lerner M.
        • Spencer T.
        • Wolraich M.
        ADHD treatment with once-daily OROS methylphenidate: final results from a long-term open-label study.
        J Am Acad Child Adolesc Psychiatry. 2005; 44: 1015-1023
        • Chermá M.D.
        • Josefsson M.
        • Rydberg I.
        • Woxler P.
        • Trygg T.
        • Hollertz O.
        • Gustafsson P.A.
        Methylphenidate for Treating ADHD: A Naturalistic Clinical Study of Methylphenidate Blood Concentrations in Children and Adults With Optimized Dosage.
        Eur J Drug Metab Pharmacokinet. 2017; 42: 295-307
        • Akhondzadeh S.
        • Mohammadi M.R.
        • Khademi M.
        Zinc sulfate as an adjunct to methylphenidate for the treatment of attention deficit hyperactivity disorder in children: A double blind and randomized trial [ISRCTN64132371].
        BMC Psychiatry. 2004; 4: 1-6
      3. Concerta® Tablets (Methylphenidate Hydrochloride), Common Technical Document in Japan(October 26 2007、CTD2.7.6.8) (2007):

        • Huang-Pollock C.L.
        • Karalunas S.L.
        • Tam H.
        • Moore A.N.
        Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance.
        J Abnorm Psychol. 2012; 121: 360-371
        • Shin M.S.
        • Cho S.
        • Chun S.Y.
        • Hong K.-E.M.
        A study of the development and standardization of ADHD Diagnostic system.
        Korean J Child Adol Psychiatr. 2000; 11: 91-99
        • Mizuno Y.
        • Jung M.
        • Fujisawa T.X.
        • Takiguchi S.
        • Shimada K.
        • Saito D.N.
        • et al.
        Catechol-O-methyltransferase polymorphism is associated with the cortico-cerebellar functional connectivity of executive function in children with attention-deficit/hyperactivity disorder.
        Sci Rep. 2017; 7: 4850
        • Mizuno Y.
        • Kagitani-Shimono K.
        • Jung M.
        • Makita K.
        • Takiguchi S.
        • Fujisawa T.X.
        • et al.
        Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder.
        Transl Psychiatry. 2019; 9: 332
        • Jung M.
        • Mizuno Y.
        • Fujisawa T.X.
        • Takiguchi S.
        • Kong J.
        • Kosaka H.
        • Tomoda A.
        The Effects of COMT Polymorphism on Cortical Thickness and Surface Area Abnormalities in Children with ADHD.
        Cereb Cortex. 2018; : 1-10
        • Mizuno Y.
        • Cai W.
        • Supekar K.
        • Makita K.
        • Takiguchi S.
        • Tomoda A.
        • Menon V.
        Methylphenidate remediates aberrant brain network dynamics in children with attention-deficit/hyperactivity disorder: A randomized controlled trial.
        Neuroimage. 2022; 257119332
        • Fair D.A.
        • Posner J.
        • Nagel B.J.
        • Bathula D.
        • Dias T.G.C.
        • Mills K.L.
        • et al.
        Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder.
        Biol Psychiatry. 2010; 68: 1084-1091
        • Chao-Gan Y.
        • Yu-Feng Z.
        DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI.
        Front Syst Neurosci. 2010; 4: 13
        • Pauli W.M.
        • Nili A.N.
        • Tyszka J.M.
        A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei.
        Sci data. 2018; 5180063
        • Cai W.
        • Duberg K.
        • Padmanabhan A.
        • Rehert R.
        • Bradley T.
        • Carrion V.
        • Menon V.
        Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children.
        Nat Commun. 2019; 10: 1-13
        • Haenlein M.
        • Caul W.F.
        Attention deficit disorder with hyperactivity: a specific hypothesis of reward dysfunction.
        J Am Acad Child Adolesc Psychiatry. 1987; 26: 356-362
        • Sonuga-Barke E.J.S.
        Causal models of attention-deficit/hyperactivity disorder: from common simple deficits to multiple developmental pathways.
        Biol Psychiatry. 2005; 57: 1231-1238
        • Tripp G.
        • Wickens J.R.
        Research review: dopamine transfer deficit: a neurobiological theory of altered reinforcement mechanisms in ADHD.
        J Child Psychol Psychiatry. 2008; 49: 691-704
        • Luman M.
        • Tripp G.
        • Scheres A.
        Identifying the neurobiology of altered reinforcement sensitivity in ADHD: A review and research agenda.
        Neurosci Biobehav Rev. 2010; 34: 744-754
        • Mizuno K.
        • Yoneda T.
        • Komi M.
        • Hirai T.
        • Watanabe Y.
        • Tomoda A.
        Osmotic release oral system-methylphenidate improves neural activity during low reward processing in children and adolescents with attention-deficit/hyperactivity disorder.
        NeuroImage Clin. 2013; 2: 366-376
        • Plichta M.M.
        • Scheres A.
        Ventral-striatal responsiveness during reward anticipation in ADHD and its relation to trait impulsivity in the healthy population: a meta-analytic review of the fMRI literature.
        Neurosci Biobehav Rev. 2014; 38: 125-134
        • Knutson B.
        • Adams C.M.
        • Fong G.W.
        • Hommer D.
        Anticipation of increasing monetary reward selectively recruits nucleus accumbens.
        J Neurosci. 2001; 21: RC159
        • Liu X.
        • Hairston J.
        • Schrier M.
        • Fan J.
        Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies.
        Neurosci Biobehav Rev. 2011; 35: 1219-1236
        • Volkow N.D.
        • Wang G.-J.
        • Tomasi D.
        • Kollins S.H.
        • Wigal T.L.
        • Newcorn J.H.
        • et al.
        Methylphenidate-elicited dopamine increases in ventral striatum are associated with long-term symptom improvement in adults with attention deficit hyperactivity disorder.
        J Neurosci. 2012; 32: 841-849
        • Easton N.
        • Marshall F.H.
        • Marsden C.A.
        • Fone K.C.F.
        Mapping the central effects of methylphenidate in the rat using pharmacological MRI BOLD contrast.
        Neuropharmacology. 2009; 57: 653-664
      4. Martinez E, Pasquereau B, Drui G, Saga Y, Météreau É, Tremblay L (2020): Ventral striatum supports Methylphenidate therapeutic effects on impulsive choices expressed in temporal discounting task. Sci Reports 2020 101 10: 1–11.

        • Rubia K.
        • Halari R.
        • Cubillo A.
        • Mohammad A.-M.
        • Brammer M.
        • Taylor E.
        Methylphenidate normalises activation and functional connectivity deficits in attention and motivation networks in medication-naïve children with ADHD during a rewarded continuous performance task.
        Neuropharmacology. 2009; 57: 640-652
        • Aarts E.
        • van Holstein M.
        • Hoogman M.
        • Onnink M.
        • Kan C.
        • Franke B.
        • et al.
        Reward modulation of cognitive function in adult attention-deficit/hyperactivity disorder: a pilot study on the role of striatal dopamine.
        Behav Pharmacol. 2015; 26: 227-240
        • Furukawa E.
        • da Costa R.Q.M.
        • Bado P.
        • Hoefle S.
        • Vigne P.
        • Monteiro M.
        • et al.
        Methylphenidate modifies reward cue responses in adults with ADHD: An fMRI study.
        Neuropharmacology. 2020; 162107833
        • Wager T.D.
        • Sylvester C.-Y.C.
        • Lacey S.C.
        • Nee D.E.
        • Franklin M.
        • Jonides J.
        Common and unique components of response inhibition revealed by fMRI.
        Neuroimage. 2005; 27: 323-340
        • Mayer J.S.
        • Roebroeck A.
        • Maurer K.
        • Linden D.E.J.
        Specialization in the default mode: Task-induced brain deactivations dissociate between visual working memory and attention.
        Hum Brain Mapp. 2010; 31: 126-139
        • Harrison B.J.
        • Pujol J.
        • López-Solà M.
        • Hernández-Ribas R.
        • Deus J.
        • Ortiz H.
        • et al.
        Consistency and functional specialization in the default mode brain network.
        Proc Natl Acad Sci U S A. 2008; 105: 9781-9786
        • Hart H.
        • Radua J.
        • Nakao T.
        • Mataix-Cols D.
        • Rubia K.
        Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects.
        JAMA psychiatry. 2013; 70: 185-198
        • Picon F.A.
        • Sato J.R.
        • Anés M.
        • Vedolin L.M.
        • Mazzola A.A.
        • Valentini B.B.
        • et al.
        Methylphenidate Alters Functional Connectivity of Default Mode Network in Drug-Naive Male Adults With ADHD.
        J Atten Disord. 2020; 24: 447-455
        • Tomasi D.
        • Volkow N.D.
        • Wang G.J.
        • Wang R.
        • Telang F.
        • Caparelli E.C.
        • et al.
        Methylphenidate enhances brain activation and deactivation responses to visual attention and working memory tasks in healthy controls.
        Neuroimage. 2011; 54: 3101-3110
        • Castellanos F.X.
        • Tannock R.
        Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes.
        Nat Rev Neurosci. 2002; 3: 617-628
        • Fassbender C.
        • Zhang H.
        • Buzy W.M.
        • Cortes C.R.
        • Mizuiri D.
        • Beckett L.
        • Schweitzer J.B.
        A lack of default network suppression is linked to increased distractibility in ADHD.
        Brain Res. 2009; 1273: 114-128
        • Peterson B.S.
        • Potenza M.N.
        • Wang Z.
        • Zhu H.
        • Martin A.
        • Marsh R.
        • et al.
        An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD.
        Am J Psychiatry. 2009; 166: 1286-1294
        • Sonuga-Barke E.J.S.
        • Castellanos F.X.
        Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis.
        Neurosci Biobehav Rev. 2007; 31: 977-986
        • Zimmer L.
        Contribution of Clinical Neuroimaging to the Understanding of the Pharmacology of Methylphenidate.
        Trends Pharmacol Sci. 2017; 38: 608-620