Skip to main content

Advertisement

Log in

The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

We examined the effect of a single dose of methylphenidate (MPH) on whole brain functional connectivity, assessed using resting state functional MRI (rsfMRI), in young people with ADHD. 16 young people with ADHD participated in two rsfMRI scans in a randomized, placebo-controlled study with an acute dose of MPH (20 mg). 15 typically developing controls also performed the task under placebo conditions. The network-based statistic (NBS) was used to identify differential connectivity patterns between the MPH and placebo conditions in the ADHD group. Mean connectivity of the resulting sub-network was examined in the ADHD and control groups. Resting state functional connectivity (RSFC) analysis revealed significantly reduced connectivity under MPH compared to placebo in young people with ADHD. Findings were robust across a range of thresholds. No sub-networks of increased connectivity were found at any threshold. Mean connectivity of the identified sub-network was significantly higher in ADHD individuals in the placebo condition compared to controls, however there was no difference between MPH condition and controls. We demonstrated a significant MPH-related reduction in RSFC in a large, robust network primarily involving occipital, temporal and cerebellar regions, and visual, executive and default mode networks. These findings suggest that MPH is ‘normalising’ a higher RSFC in young people with ADHD. This study is a novel addition to the understanding of treatment effects on the brain in ADHD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • An, L., Cao, X.-H., Cao, Q.-J., Sun, L., Yang, L., Zou, Q.-H., et al. (2013). Methylphenidate normalizes resting-state brain dysfunction in boys with attention deficit hyperactivity disorder. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology, 38(7), 1287–1295. doi:10.1038/npp.2013.27.

    Article  CAS  Google Scholar 

  • Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37(1), 90–101. doi:10.1016/j.neuroimage.2007.04.042.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bond, A., & Lader, M. (1974). The use of analogue scales in rating subjective feelings. British Journal of Medical Psychology, 47(3), 211–218. doi:10.1111/j.2044-8341.1974.tb02285.x.

    Article  Google Scholar 

  • Buckner, R. L., Andrews Hanna, J. R., & Schacter, D. L. (2008). The Brain’s default network. Annals of the New York Academy of Sciences, 1124(1), 1–38. doi:10.1196/annals.1440.011.

    Article  PubMed  Google Scholar 

  • Cao, M., Shu, N., Cao, Q., Wang, Y., & He, Y. (2014). Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder. Molecular Neurobiology, 50(3), 1111–1123. doi:10.1007/s12035-014-8685-x.

    Article  CAS  PubMed  Google Scholar 

  • Castellanos, F. X., & Proal, E. (2012). Large-scale brain systems in ADHD: beyond the prefrontal-striatal model. Trends in Cognitive Sciences, 16(1), 17–26. doi:10.1016/j.tics.2011.11.007.

    Article  PubMed  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York, NY: Routledge Academic

  • Czerniak, S. M., Sikoglu, E. M., King, J. A., Kennedy, D. N., Mick, E., Frazier, J., & Moore, C. M. (2013). Areas of the brain modulated by single-dose methylphenidate treatment in youth with ADHD during task-based fMRI: a systematic review. Harvard Review of Psychiatry, 21(3), 151–162. doi:10.1097/HRP.0b013e318293749e.

    PubMed  PubMed Central  Google Scholar 

  • Dwyer, D. B., Harrison, B. J., Yuecel, M., Whittle, S., Zalesky, A., Pantelis, C., et al. (2014). Large-scale brain network dynamics supporting adolescent cognitive control. Journal of Neuroscience, 34(42), 14096–14107. doi:10.1523/JNEUROSCI.1634-14.2014.

    Article  CAS  PubMed  Google Scholar 

  • Eichele, T., Debener, S., Calhoun, V. D., Specht, K., Engel, A. K., Hugdahl, K., et al. (2008). Prediction of human errors by maladaptive changes in event-related brain networks. Proceedings of the National Academy of Sciences of the United States of America, 105(16), 6173–6178. doi:10.1073/pnas.0708965105.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Farr, O. M., Zhang, S., Hu, S., Matuskey, D., Abdelghany, O., Malison, R. T., & Li, C.-S. R. (2014). The effects of methylphenidate on resting-state striatal, thalamic and global functional connectivity in healthy adults. International Journal of Neuropsychopharmacology, 17(8), 1177–1191. doi:10.1017/S1461145714000674.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012). Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection. Proceedings of the National Academy of Sciences of the United States of America, 109(31), 12788–12793. doi:10.1073/pnas.1204185109.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Friston, K. J., Jezzard, P., & Turner, R. (1994). Analysis of functional MRI time-series. Human Brain Mapping, 1(2), 153–171. doi:10.1002/hbm.460010207.

    Article  Google Scholar 

  • Goetz, M., Vesela, M., & Ptacek, R. (2014). Notes on the role of the cerebellum in ADHD.

  • Hedges, L. V. (1981). Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational and Behavioral Statistics, 6(2), 107–128. doi:10.3102/10769986006002107.

    Article  Google Scholar 

  • Hotelling, H. (1953). New light on the correlation coefficient and its transforms. Journal of the Royal Statistical Society, Series B. doi:10.2307/2983768.

    Google Scholar 

  • Kimko, H. C., Cross, J. T., & Abernethy, D. R. (1999). Pharmacokinetics and clinical effectiveness of methylphenidate. Clinical Pharmacokinetics, 37(6), 457–470. doi:10.2165/00003088-199937060-00002.

    Article  CAS  PubMed  Google Scholar 

  • Koziol, L. F., Budding, D., Andreasen, N., D’Arrigo, S., Bulgheroni, S., Imamizu, H., et al. (2014). Consensus paper: the cerebellum’s role in movement and cognition. In Presented at the Cerebellum (Vol. 13, pp. 151–177). London: Springer. doi:10.1007/s12311-013-0511-x.

    Google Scholar 

  • Lee, J. S., Kim, B. N., Kang, E., Lee, D. S., Kim, Y. K., Chung, J. K., et al. (2005). Regional cerebral blood flow in children with attention deficit hyperactivity disorder: comparison before and after methylphenidate treatment. Human Brain Mapping, 24(3), 157–164. doi:10.1002/hbm.20067.

    Article  PubMed  Google Scholar 

  • Li, S. J., Biswal, B., Li, Z., Risinger, R., Rainey, C., Cho, J. K., et al. (2000). Cocaine administration decreases functional connectivity in human primary visual and motor cortex as detected by functional MRI. Magnetic Resonance in Medicine, 43(1), 45–51.

    Article  CAS  PubMed  Google Scholar 

  • Liddle, E. B., Hollis, C., Batty, M. J., Groom, M. J., Totman, J. J., Liotti, M., et al. (2011). Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 52(7), 761–771. doi:10.1111/j.1469-7610.2010.02333.x.

    Article  PubMed  Google Scholar 

  • Makris, N., Goldstein, J. M., Kennedy, D., Hodge, S. M., Caviness, V. S., Faraone, S. V., et al. (2006). Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophrenia Research, 83(2–3), 155–171. doi:10.1016/j.schres.2005.11.020.

    Article  PubMed  Google Scholar 

  • Mueller, S., Costa, A., Keeser, D., Pogarell, O., Berman, A., Coates, U., et al. (2014). The effects of methylphenidate on whole brain intrinsic functional connectivity. Human Brain Mapping, 35(11), 5379–5388. doi:10.1002/hbm.22557.

    Article  PubMed  Google Scholar 

  • O’Gorman, R. L., Mehta, M. A., Asherson, P., Zelaya, F. O., Brookes, K. J., Toone, B. K., et al. (2008). Increased cerebral perfusion in adult attention deficit hyperactivity disorder is normalised by stimulant treatment: a non-invasive MRI pilot study. NeuroImage, 42(1), 36–41. doi:10.1016/j.neuroimage.2008.04.169.

    Article  PubMed  Google Scholar 

  • Peterson, B. S., Marc, N., Potenza, M. D. P. D., Zhishun Wang, P. D., Hongtu Zhu, P. D., Andrés Martin, M. D., Rachel Marsh, P. D., et al. (2009). An fMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD. American Journal of Psychiatry, 166(11), 1286–1294. doi:10.1176/appi.ajp.2009.08050724.

    Article  PubMed  PubMed Central  Google Scholar 

  • Posner, J., Park, C., & Wang, Z. (2014). Connecting the dots: a review of resting connectivity MRI studies in attention-deficit/hyperactivity disorder. Neuropsychology Review, 24(1), 3–15. doi:10.1007/s11065-014-9251-z.

    Article  PubMed  PubMed Central  Google Scholar 

  • Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154. doi:10.1016/j.neuroimage.2011.10.018.

    Article  PubMed  Google Scholar 

  • Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: a brief history of an evolving idea. NeuroImage, 37(4), 1083–1090 discussion 1097–9. doi:10.1016/j.neuroimage.2007.02.041.

    Article  PubMed  Google Scholar 

  • Ricciardi, E., Handjaras, G., Bernardi, G., Pietrini, P., & Furey, M. L. (2013). Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention. Neuropharmacology, 64, 305–313. doi:10.1016/j.neuropharm.2012.07.003.

    Article  CAS  PubMed  Google Scholar 

  • Rubia, K., Alegría, A. A., Cubillo, A. I., Smith, A. B., Brammer, M. J., & Radua, J. (2014). Effects of stimulants on brain function in attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. Biological Psychiatry, 76(8), 616–628. doi:10.1016/j.biopsych.2013.10.016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schmahmann, J. D., Weilburg, J. B., & Sherman, J. C. (2007). The neuropsychiatry of the cerebellum - insights from the clinic. Cerebellum (London, England), 6(3), 254–267. doi:10.1080/14734220701490995.

    Article  Google Scholar 

  • Schweitzer, J. B., Lee, D. O., Hanford, R. B., Tagamets, M. A., Hoffman, J. M., Grafton, S. T., & Kilts, C. D. (2003). A positron emission tomography study of methylphenidate in adults with ADHD: alterations in resting blood flow and predicting treatment response. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology, 28(5), 967–973. doi:10.1038/sj.npp.1300110.

    CAS  Google Scholar 

  • Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., et al. (2009). Correspondence of the brain’s functional architecture during activation and rest. Proceedings of the National Academy of Sciences of the United States of America, 106(31), 13040–13045. doi:10.1073/pnas.0905267106.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sonuga-Barke, E. J. S., & Castellanos, F. X. (2007). Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neuroscience and Biobehavioral Reviews, 31(7), 977–986. doi:10.1016/j.neubiorev.2007.02.005.

    Article  PubMed  Google Scholar 

  • Spencer, T. J., Brown, A., Seidman, L. J., Valera, E. M., Makris, N., Lomedico, A., et al. (2013). Effect of psychostimulants on brain structure and function in ADHD: a qualitative literature review of magnetic resonance imaging-based neuroimaging studies. The Journal of Clinical Psychiatry, 74(9), 902–917. doi:10.4088/JCP.12r08287.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sripada, C. S., Kessler, D., Welsh, R., Angstadt, M., Liberzon, I., Phan, K. L., & Scott, C. (2013). Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis. NeuroImage, 81, 213–221. doi:10.1016/j.neuroimage.2013.05.016.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tomasi, D., Volkow, N. D., Wang, G. J., Wang, R., Telang, F., Caparelli, E. C., et al. (2011). Methylphenidate enhances brain activation and deactivation responses to visual attention and working memory tasks in healthy controls. NeuroImage, 54(4), 3101–3110. doi:10.1016/j.neuroimage.2010.10.060.

    Article  CAS  PubMed  Google Scholar 

  • Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., et al. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 15(1), 273–289. doi:10.1006/nimg.2001.0978.

    Article  CAS  PubMed  Google Scholar 

  • Valera, E. M., Faraone, S. V., Murray, K. E., & Seidman, L. J. (2007). Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biological Psychiatry, 61(12), 1361–1369. doi:10.1016/j.biopsych.2006.06.011.

    Article  PubMed  Google Scholar 

  • Van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. NeuroImage, 59(1), 431–438. doi:10.1016/j.neuroimage.2011.07.044.

    Article  PubMed  Google Scholar 

  • Weissman, D. H., Roberts, K. C., & Visscher, K. M. (2006). The neural bases of momentary lapses in attention. Nature Neuroscience, 9, 971–978.

    Article  CAS  PubMed  Google Scholar 

  • Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012). Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity, 2(3), 125–141. doi:10.1089/brain.2012.0073.

    Article  PubMed  Google Scholar 

  • Xia, M., Wang, J., & He, Y. (2013). BrainNet viewer: a network visualization tool for human brain connectomics. PloS One, 8(7), e68910. doi:10.1371/journal.pone.0068910.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: identifying differences in brain networks. NeuroImage, 53(4), 1197–1207. doi:10.1016/j.neuroimage.2010.06.041.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by a Project Grant to MAB and AV (No. 569533) from the National Health and Medical Research Council of Australia. TS was supported by a NHMRC Career Development Award. The research was conducted within the Academic Child Psychiatry Unit, University of Melbourne, Royal Children’s Hospital and the Developmental Imaging research group, Murdoch Childrens Research Institute (MCRI) and the Children’s MRI Centre, Royal Children’s Hospital, Melbourne, Victoria. It was also supported by The Royal Children’s Hospital Foundation and the Victorian Government’s Operational Infrastructure Support Program. This trial was registered at Australian New Zealand Clinical Trials Registry (www.anzctr.org.au) as ACTRN12610000652077. We thank Alex Fornito for his feedback on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Timothy J Silk.

Ethics declarations

Funding

This work was supported by a Project Grant to MAB and AV (No. 569,533) from the National Health and Medical Research Council of Australia.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Electronic supplementary material

ESM 1

(DOCX 179 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Silk, T.J., Malpas, C., Vance, A. et al. The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD. Brain Imaging and Behavior 11, 1422–1431 (2017). https://doi.org/10.1007/s11682-016-9620-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-016-9620-8

Keywords

Navigation