Treatment effect of methylphenidate on intrinsic functional brain network in medication-naïve ADHD children: A multivariate analysis
- 577 Downloads
Methylphenidate is a first-line therapeutic option for treating attention-deficit/hyperactivity disorder (ADHD); however, elicited changes on resting-state functional networks (RSFNs) are not well understood. This study investigated the treatment effect of methylphenidate using a variety of RSFN analyses and explored the collaborative influences of treatment-relevant RSFN changes in children with ADHD. Resting-state functional magnetic resonance imaging was acquired from 20 medication-naïve ADHD children before methylphenidate treatment and twelve weeks later. Changes in large-scale functional connectivity were defined using independent component analysis with dual regression and graph theoretical analysis. The amplitude of low frequency fluctuation (ALFF) was measured to investigate local spontaneous activity alteration. Finally, significant findings were recruited to random forest regression to identify the feature subset that best explains symptom improvement. After twelve weeks of methylphenidate administration, large-scale connectivity was increased between the left fronto-parietal RSFN and the left insula cortex and the right fronto-parietal and the brainstem, while the clustering coefficient (CC) of the global network and nodes, the left fronto-parietal, cerebellum, and occipital pole-visual network, were decreased. ALFF was increased in the bilateral superior parietal cortex and decreased in the right inferior fronto-temporal area. The subset of the local and large-scale RSFN changes, including widespread ALFF changes, the CC of the global network and the cerebellum, could explain the 27.1% variance of the ADHD Rating Scale and 13.72% of the Conner’s Parent Rating Scale. Our multivariate approach suggests that the neural mechanism of methylphenidate treatment could be associated with alteration of spontaneous activity in the superior parietal cortex or widespread brain regions as well as functional segregation of the large-scale intrinsic functional network.
KeywordsAttention deficit-hyperactivity disorder Methylphenidate Functional magnetic resonance imaging Resting state networks Machine learning
Compliance with ethical standards
This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2016M3C7A1914448 to B.J.), and by KAIST Future Systems Healthcare Project from the Ministry of Education, Science and Technology (N11160068 to B.J.)
Conflict of interest
All authors declares that they have no conflict of interest.
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 was obtained from all individual participants and their parents included in the study.
- An, L., Cao, X. H., Cao, Q. J., Sun, L., Yang, L., Zou, Q. H., et al. (2013b). Methylphenidate normalizes resting-state brain dysfunction in boys with attention deficit hyperactivity disorder. Neuropsychopharmacology, 38(7), 1287–1295. doi: 10.1038/npp.2013.27.CrossRefPubMedPubMedCentralGoogle Scholar
- An, L., Cao, Q. J., Sui, M. Q., Sun, L., Zou, Q. H., Zang, Y. F., et al. (2013a). Local synchronization and amplitude of the fluctuation of spontaneous brain activity in attention-deficit/hyperactivity disorder: a resting-state fMRI study. Neuroscience Bulletin, 29(5), 603–613. doi: 10.1007/s12264-013-1353-8.CrossRefPubMedPubMedCentralGoogle Scholar
- Arnsten, A. F., & Pliszka, S. R. (2011). Catecholamine influences on prefrontal cortical function: relevance to treatment of attention deficit/hyperactivity disorder and related disorders. Pharmacology, Biochemistry, and Behavior, 99(2), 211–216. doi: 10.1016/j.pbb.2011.01.020.CrossRefPubMedPubMedCentralGoogle Scholar
- Berridge, C. W., Devilbiss, D. M., Andrzejewski, M. E., Arnsten, A. F., Kelley, A. E., Schmeichel, B., et al. (2006). Methylphenidate preferentially increases catecholamine neurotransmission within the prefrontal cortex at low doses that enhance cognitive function. Biological Psychiatry, 60(10), 1111–1120. doi: 10.1016/j.biopsych.2006.04.022.CrossRefPubMedGoogle Scholar
- Broyd, S. J., Johnstone, S. J., Barry, R. J., Clarke, A. R., McCarthy, R., Selikowitz, M., et al. (2005). The effect of methylphenidate on response inhibition and the event-related potential of children with attention deficit/hyperactivity disorder. International Journal of Psychophysiology, 58(1), 47–58. doi: 10.1016/j.ijphyscho.2005.03.008.CrossRefPubMedGoogle Scholar
- Cho, S. C., Hwang, J. W., Kim, B. N., Lee, H. Y., Kim, H. W., Lee, J. S., et al. (2007). The relationship between regional cerebral blood flow and response to methylphenidate in children with attention-deficit hyperactivity disorder: comparison between non-responders to methylphenidate and responders. Journal of Psychiatric Research, 41(6), 459–465. doi: 10.1016/j.jpsychires.2006.05.011.CrossRefPubMedGoogle Scholar
- Cubillo, A., Smith, A. B., Barrett, N., Giampietro, V., Brammer, M. J., Simmons, A., et al. (2014). Shared and drug-specific effects of atomoxetine and methylphenidate on inhibitory brain dysfunction in medication-naive ADHD boys. Cerebral Cortex, 24(1), 174–185. doi: 10.1093/cercor/bhs296.CrossRefPubMedGoogle Scholar
- Czerniak, S. M., Sikoglu, E. M., King, J. A., Kennedy, D. N., Mick, E., Frazier, J., et al. (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.PubMedPubMedCentralGoogle Scholar
- Di, X., Kim, E. H., Huang, C. C., Tsai, S. J., Lin, C. P., & Biswal, B. B. (2013). The influence of the amplitude of low-frequency fluctuations on resting-state functional connectivity. Frontiers in Human Neuroscience, 7, 118. doi: 10.3389/fnhum.2013.00118.
- Dosenbach, N. U., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A., et al. (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences of the United States of America, 104(26), 11073–11078. doi: 10.1073/pnas.0704320104.CrossRefPubMedPubMedCentralGoogle Scholar
- DuPaul, G. J., McGoey, K. E., Eckert, T. L., & VanBrakle, J. (2001). Preschool children with attention-deficit/hyperactivity disorder: impairments in behavioral, social, and school functioning. Journal of the American Academy of Child and Adolescent Psychiatry, 40(5), 508–515. doi: 10.1097/00004583-200105000-00009.CrossRefPubMedGoogle Scholar
- Epstein, J. N., Casey, B. J., Tonev, S. T., Davidson, M. C., Reiss, A. L., Garrett, A., et al. (2007). ADHD- and medication-related brain activation effects in concordantly affected parent-child dyads with ADHD. Journal of Child Psychology and Psychiatry, 48(9), 899–913. doi: 10.1111/j.1469-7610.2007.01761.x.CrossRefPubMedGoogle Scholar
- Fair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U., et al. (2012). Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data. Frontiers in Systems Neuroscience, 6, 80. doi: 10.3389/fnsys.2012.00080.PubMedGoogle Scholar
- Fair, D. A., Posner, J., Nagel, B. J., Bathula, D., Dias, T. G., Mills, K. L., et al. (2010). Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder. Biological Psychiatry, 68(12), 1084–1091. doi: 10.1016/j.biopsych.2010.07.003.CrossRefPubMedPubMedCentralGoogle Scholar
- Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., et al. (2009). Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proceedings of the National Academy of Sciences of the United States of America, 106(17), 7209–7214. doi: 10.1073/pnas.0811879106.CrossRefPubMedPubMedCentralGoogle Scholar
- Kaufman, J., Birmaher, B., Brent, D., Rao, U., Flynn, C., Moreci, P., et al. (1997). Schedule for affective disorders and Schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry, 36(7), 980–988. doi: 10.1097/00004583-199707000-00021.CrossRefPubMedGoogle Scholar
- Kim, Y. S., Cheon, K. A., Kim, B. N., Chang, S. A., Yoo, H. J., Kim, J. W., et al. (2004). The reliability and validity of kiddie-schedule for affective disorders and Schizophrenia-present and lifetime version- Korean version (K-SADS-PL-K). Yonsei Medical Journal, 45(1), 81–89.CrossRefPubMedGoogle Scholar
- Kim, J., Whyte, J., Patel, S., Europa, E., Wang, J., Coslett, H. B., et al. (2012). Methylphenidate modulates sustained attention and cortical activation in survivors of traumatic brain injury: a perfusion fMRI study. Psychopharmacology, 222(1), 47–57. doi: 10.1007/s00213-011-2622-8.CrossRefPubMedGoogle Scholar
- Konrad, K., Neufang, S., Fink, G. R., & Herpertz-Dahlmann, B. (2007). Long-term effects of methylphenidate on neural networks associated with executive attention in children with ADHD: results from a longitudinal functional MRI study. Journal of the American Academy of Child and Adolescent Psychiatry, 46(12), 1633–1641. doi: 10.1097/chi.0b013e318157cb3b.CrossRefPubMedGoogle Scholar
- Littow, H., Elseoud, A. A., Haapea, M., Isohanni, M., Moilanen, I., Mankinen, K., et al. (2010). Age-related differences in functional nodes of the brain cortex - a high model order group ICA study. Frontiers in Systems Neuroscience, 4, doi: 10.3389/fnsys.2010.00032.
- Park K. S. Y. J., Park H. J., Kwon K. U. (1996). Development of KEDI-WSIC, individual intelligence test for Korean children Seoul: Korean educational development instituteGoogle Scholar
- Park, E., So, Y., Kim, Y., Choi, N., Kim, S., Noh, J., et al. (2003). The reliability and validity of Korean conners parent and teacher rating scale. Korean Journal of Child and Adolescent Psychiatry, 14(2), 183–196.Google Scholar
- R Core Team (2016). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org/.
- Rubia, K., Halari, R., Cubillo, A., Mohammad, A. M., Brammer, M., & Taylor, E. (2009). Methylphenidate normalises activation and functional connectivity deficits in attention and motivation networks in medication-naive children with ADHD during a rewarded continuous performance task. Neuropharmacology, 57(7–8), 640–652. doi: 10.1016/j.neuropharm.2009.08.013.CrossRefPubMedGoogle Scholar
- Rubia, K., Halari, R., Mohammad, A. M., Taylor, E., & Brammer, M. (2011). Methylphenidate normalizes frontocingulate underactivation during error processing in attention-deficit/hyperactivity disorder. Biological Psychiatry, 70(3), 255–262. doi: 10.1016/j.biopsych.2011.04.018.CrossRefPubMedPubMedCentralGoogle Scholar
- Sidlauskaite, J., Sonuga-Barke, E., Roeyers, H., & Wiersema, J. R. (2016). Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity. European Archives of Psychiatry and Clinical Neuroscience, 266(4), 349–357. doi: 10.1007/s00406-015-0630-0.CrossRefPubMedGoogle 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.CrossRefPubMedPubMedCentralGoogle Scholar
- So, Y., Noh, J., Kim, Y., Ko, S., & Koh, Y. (2002). The reliability and validity of Korean parent and teacher ADHD rating scale. Journal of Korean Neuropsychiatric Association, 41(2), 283–289.Google Scholar
- Spinelli, S., Vasa, R. A., Joel, S., Nelson, T. E., Pekar, J. J., & Mostofsky, S. H. (2011). Variability in post-error behavioral adjustment is associated with functional abnormalities in the temporal cortex in children with ADHD. Journal of Child Psychology and Psychiatry, 52(7), 808–816. doi: 10.1111/j.1469-7610.2010.02356.x.CrossRefPubMedGoogle Scholar
- Sripada, C. S., Kessler, D., & Angstadt, M. (2014). Lag in maturation of the brain's intrinsic functional architecture in attention-deficit/hyperactivity disorder. Proceedings of the National Academy of Sciences of the United States of America, 111(39), 14259–14264. doi: 10.1073/pnas.1407787111.CrossRefPubMedPubMedCentralGoogle Scholar
- Sripada, C. S., Kessler, D., Welsh, R., Angstadt, M., Liberzon, I., Phan, K. L., et al. (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.CrossRefPubMedPubMedCentralGoogle Scholar
- Strobl, C., Malley, J., & Tutz, G. (2009). An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods, 14(4), 323–348. doi: 10.1037/a0016973.CrossRefPubMedPubMedCentralGoogle Scholar
- Subcommittee on Attention-Deficit/Hyperactivity, D, Steering Committee on Quality, I., Management, Wolraich, M., Brown, L., Brown, R. T., et al. (2011). ADHD: clinical practice guideline for the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Pediatrics, 128(5), 1007–1022. doi: 10.1542/peds.2011-2654.CrossRefGoogle Scholar
- Van der Oord, S., Prins, P. J., Oosterlaan, J., & Emmelkamp, P. M. (2008). Efficacy of methylphenidate, psychosocial treatments and their combination in school-aged children with ADHD: a meta-analysis. Clinical Psychology Review, 28(5), 783–800. doi: 10.1016/j.cpr.2007.10.007.CrossRefPubMedGoogle Scholar
- Veer, I. M., Beckmann, C. F., van Tol, M. J., Ferrarini, L., Milles, J., Veltman, D. J., et al. (2010). Whole brain resting-state analysis reveals decreased functional connectivity in major depression. Frontiers in Systems Neuroscience, 4, doi: 10.3389/fnsys.2010.00041.
- Volkow, N. D., Wang, G. J., Fowler, J. S., Logan, J., Angrist, B., Hitzemann, R., et al. (1997). Effects of methylphenidate on regional brain glucose metabolism in humans: relationship to dopamine D2 receptors. The American Journal of Psychiatry, 154(1), 50–55. doi: 10.1176/ajp.154.1.50.CrossRefPubMedGoogle Scholar
- Yang, Z., Kelly, C., Castellanos, F. X., Leon, T., Milham, M. P., & Adler, L. A. (2016). Neural correlates of symptom improvement following stimulant treatment in adults with attention-deficit/hyperactivity disorder. Journal of Child and Adolescent Psychopharmacology, 26(6), 527–536. doi: 10.1089/cap.2015.0243.CrossRefPubMedPubMedCentralGoogle Scholar
- Zou, Q. H., Zhu, C. Z., Yang, Y., Zuo, X. N., Long, X. Y., Cao, Q. J., et al. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. Journal of Neuroscience Methods, 172(1), 137–141. doi: 10.1016/j.jneumeth.2008.04.012.CrossRefPubMedPubMedCentralGoogle Scholar
- Zuo, X. N., Xu, T., Jiang, L., Yang, Z., Cao, X. Y., He, Y., et al. (2013). Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space. NeuroImage, 65, 374–386. doi: 10.1016/j.neuroimage.2012.10.017.CrossRefPubMedGoogle Scholar