Aberrant development of functional connectivity among resting state-related functional networks in medication-naive ADHD children
Open accessAbstract
OBJECTIVE: The aim of this study was to investigate the compromised developmental trajectory of the functional connectivity among resting-state-related functional networks (RSFNs) in medication-naïve children with attention-deficit/hyperactivity disorder (ADHD). SUBJECTS AND METHODS: Using both independent component analysis and dual regression, subject-specific time courses of 12 RSFNs were extracted from both 20 medication-naïve children with ADHD, and 20 age and gender-matched control children showing typical development (TDC). Both partial correlation coefficients among the 12 RSFNs and a resting-state resource allocation index (rsRAI) of the salience network (SN) were entered into multiple linear regression analysis to investigate the compromised, age-related change in medication-naïve ADHD children. Finally, correlation analyses were performed between the compromised RSFN connections showing significant group-by-age interaction and rsRAI of SN or clinical variables. RESULTS: Medication-naïve ADHD subjects failed to show age-related increment of functional connectivity in both rsRAI of SN and two RSFN connections, SN-Sensory/motor and posterior default mode/precuneus network (pDMN/prec)--anterior DMN. Lower SN-Sensory/motor connectivity was related with higher scores on the ADHD Rating Scale, and with poor scores on the continuous performance test. The pDMN/prec-aDMN connectivity was positively related with rsRAI of SN. CONCLUSIONS: Our results suggest that medication-naïve ADHD subjects may have delayed maturation of the two functional connections, SN-Sensory/Motor and aDMN-pDMN/prec. Interventions that enhance the functional connectivity of these two connections may merit attention as potential therapeutic or preventive options in both ADHD and TDC.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
It is commonplace to forgo group matching on IQ in the ADHD literature.
“where it is commonplace to forgo group matching on IQ (Choi et al., 2013).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Choi et al., 2013
Research into the impact of IQ levels on neuroimaging results are only beginning to emerge for the ASD literature and are virtually absent in the ADHD literature.
“Research into the impact of IQ levels on neuroimaging results are only beginning to emerge for the ASD literature (Reiter et al., 2019) and are virtually absent in the ADHD literature, where it is commonplace to forgo group matching on IQ (Choi et al., 2013).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Choi et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426 · see citing works
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256 · see citing works
Dynamic mapping of human cortical development during childhood through early adulthood
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., Nugent, T. F., Herman, D. H., Clasen, L. S., Toga, A. W., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402680101 · Cited by 5,604 · cited 1× · see citing works
“As brain development is very active from age 7 to 16, the functional connectivity should also be actively changing during childhood and adolescence [33,34].”
BackgroundBrain development during childhood and adolescence: a longitudinal MRI study
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., Paus, T., Evans, A. C., & Rapoport, J. L. (1999) · Nature Neuroscience · doi:10.1038/13158 · Cited by 5,552 · see citing works
The reorienting system of the human brain: from environment to theory of mind
Corbetta, M., Patel, G., & Shulman, G. L. (2008) · Neuron · doi:10.1016/j.neuron.2008.04.017 · Cited by 3,889 · see citing works
Better Bootstrap Confidence Intervals
Efron, B. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478410 · Cited by 3,462 · see citing works
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398 · see citing works
Sridharan, D., Levitin, D. J., & Menon, V. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800005105 · Cited by 2,892 · see citing works
Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging
Beckmann, C. F., & Smith, S. M. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.822821 · Cited by 2,707 · see citing works
Network modelling methods for FMRI
Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., Ramsey, J. D., & Woolrich, M. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.063 · Cited by 1,878 · see citing works
Default-mode brain dysfunction in mental disorders: A systematic review
Broyd, S. J., Demanuele, C., Debener, S., Helps, S. K., James, C. J., & Sonuga-Barke, E. J. S. (2009) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2008.09.002 · Cited by 1,675 · see citing works
Distinct patterns of brain activity in young carriers of the <i>APOE</i> -ε4 allele
Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811879106 · Cited by 1,613 · see citing works
Prevalence and correlates of adult attention-deficit hyperactivity disorder: meta-analysis
Simon, V., Czobor, P., Bálint, S., Mészáros, Á., & Bitter, I. (2009) · British Journal of Psychiatry · doi:10.1192/bjp.bp.107.048827 · Cited by 1,601 · see citing works
Microglial interactions with synapses are modulated by visual experience
Tremblay, M.-È., Lowery, R. L., & Majewska, A. K. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000527 · Cited by 1,542 · see citing works
Microstructural maturation of the human brain from childhood to adulthood
Lebel, C., Walker, L., Leemans, A., Phillips, L., & Beaulieu, C. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.12.053 · Cited by 1,398 · see citing works
The maturing architecture of the brain's default network
Fair, D. A., Cohen, A. L., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800376105 · Cited by 1,314 · see citing works
Competition between functional brain networks mediates behavioral variability
Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.008 · Cited by 1,287 · see citing works
Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood
Lebel, C., & Beaulieu, C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5302-10.2011 · Cited by 1,193 · see citing works
Jafri, M. J., Pearlson, G. D., Stevens, M. C. G., & Calhoun, V. D. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.11.001 · Cited by 976 · see citing works
Sonuga-Barke, E. J. S., & Castellanos, F. X. (2007) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2007.02.005 · Cited by 890 · see citing works
Castellanos, F. X., Margulies, D. S., Kelly, C., Uddin, L. Q., Ghaffari, M., Kirsch, A., Shaw, D., Shehzad, Z., Di Martino, A., Biswal, B., et al. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.06.025 · Cited by 854 · see citing works
Large-scale brain systems in ADHD: beyond the prefrontal–striatal model
Castellanos, F. X., & Proal, E. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.11.007 · Cited by 831 · see citing works
The neural correlates of attention deficit hyperactivity disorder: an ALE meta‐analysis
Dickstein, S. G., Bannon, K., Xavier Castellanos, F., & Milham, M. P. (2006) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2006.01671.x · Cited by 745 · see citing works
Fox, M. D., Snyder, A. Z., Zacks, J. M., & Raichle, M. E. (2006) · Nature Neuroscience · doi:10.1038/nn1616 · Cited by 660 · see citing works
Nakao, T., Radua, J., Rubia, K., & Mataix-Cols, D. (2011) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11020281 · Cited by 588 · see citing works
Uddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4465-11.2011 · Cited by 520 · see citing works
Network homogeneity reveals decreased integrity of default-mode network in ADHD
Uddin, L. Q., Kelly, A. M. C., Biswal, B. B., Margulies, D. S., Shehzad, Z., Shaw, D., Ghaffari, M., Rotrosen, J., Adler, L. A., Castellanos, F. X., et al. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.11.031 · Cited by 452 · see citing works
Developmental Normative Data on The Test of Variables of Attention (T.O.V.A.™)
Greenberg, L. M., & Waldmant, I. D. (1993) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.1993.tb01105.x · Cited by 449 · see citing works
A role for synaptic plasticity in the adolescent development of executive function
Selemon, L. D. (2013) · Translational Psychiatry · doi:10.1038/tp.2013.7 · Cited by 439 · cited 1× · see citing works
“Although the cellular basis of the altered developmental trajectory of the functional connection between specific RSFNs has yet to be established, the delayed or failed development of the between-RSFN connections in medication-naı̈ve ADHD children may be attributed to the slower maturation of the brain network system…”
BackgroundAbnormal Functional Connectivity in Children with Attention-Deficit/Hyperactivity Disorder
Tomasi, D., & Volkow, N. D. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.11.003 · Cited by 363 · see citing works
Mennes, M., Kelly, C. A. M., Zuo, X., Martino, A. D., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.002 · Cited by 355 · see citing works
Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder
Fair, D. A., Posner, J., Nagel, B. J., Bathula, D., Dias, T. G. C., Mills, K. L., Blythe, M. S., Giwa, A., Schmitt, C. F., & Nigg, J. T. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.07.003 · Cited by 354 · see citing works
Cingulate, Frontal, and Parietal Cortical Dysfunction in Attention-Deficit/Hyperactivity Disorder
Bush, G. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.01.022 · Cited by 304 · see citing works
Selective aberrant functional connectivity of resting state networks in social anxiety disorder
Liao, W., Chen, H., Feng, Y., Mantini, D., Gentili, C., Pan, Z., Ding, J., Duan, X., Qiu, C., Lui, S., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.010 · Cited by 304 · see citing works
Shaw, P., Malek, M., Watson, B., Greenstein, D., de Rossi, P., & Sharp, W. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.007 · Cited by 303 · see citing works
ADHD Rating Scale-IV: School Checklist
DuPaul, G. J., Power, T. J., Anastopoulos, A. D., & Reid, R. (2018) · PsycTESTS Dataset · doi:10.1037/t00680-000 · Cited by 297 · see citing works
The Reliability and Validity of Korean Parent and Teacher ADHD Rating Scale
So, Y. K., Noh, J. S., Kim, Y. S., Ko, S. G., & Koh, Y. J. (2002) · Cited by 273 · see citing works
Pavuluri, M. N., Yang, S., Kamineni, K., Passarotti, A. M., Srinivasan, G., Harral, E. M., Sweeney, J. A., & Zhou, X. J. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.10.015 · Cited by 246 · see citing works
Makris, N., Buka, S. L., Biederman, J., Papadimitriou, G. M., Hodge, S. M., Valera, E. M., Brown, A. B., Bush, G., Monuteaux, M. C., Caviness, V. S., et al. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhm156 · Cited by 239 · see citing works
Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics
Mennes, M., Zuo, X., Kelly, C. A. M., Martino, A. D., Zang, Y., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.046 · Cited by 215 · see citing works
Proal, E. (2011) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2011.117 · Cited by 207 · see citing works
Konrad, A., Dielentheis, T. F., El Masri, D., Bayerl, M., Fehr, C., Gesierich, T., Vucurevic, G., Stoeter, P., & Winterer, G. (2010) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07110.x · Cited by 191 · see citing works
Development of the corpus callosum in childhood, adolescence and early adulthood
Keshavan, M. S., Diwadkar, V. A., DeBellis, M. D., Dick, E. L., Kotwal, R., Rosenberg, D. R., Sweeney, J. A., Minshew, N. J., & Pettegrew, J. W. (2002) · Life Sciences · doi:10.1016/s0024-3205(02)01492-3 · Cited by 174 · see citing works
Sun, L., Cao, Q., Long, X., Sui, M., Cao, X., Zhu, C., Zuo, X., Li, A., Song, Y., Zang, Y., et al. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2011.07.001 · Cited by 168 · see citing works
Supekar, K., & Menon, V. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002374 · Cited by 137 · see citing works
Cortese, S., Imperati, D., Zhou, J., Proal, E., Klein, R. G., Mannuzza, S., Ramos-Olazagasti, M. A., Milham, M. P., Kelly, C., & Castellanos, F. X. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.02.025 · Cited by 127 · see citing works
A STUDY OF THE DEVELOPMENT AND STANDARDIZATION OF ADHD DIAGNOSTIC SYSTEM
Cho, S.-Z., SunYoung, C., Hong, K.-E. M., & Shin, M. (2000) · Journal of korean Academy of Child and Adolescent Psychiatry · Cited by 123 · see citing works
Altered regional homogeneity patterns in adults with attention-deficit hyperactivity disorder
Wang, X., Jiao, Y., Tang, T., Wang, H., & Lu, Z. (2013) · European Journal of Radiology · doi:10.1016/j.ejrad.2013.04.009 · Cited by 103 · see citing works
Abnormal Brain Connectivity Patterns in Adults with ADHD: A Coherence Study
Sato, J. R., Hoexter, M. Q., Castellanos, F. X., & Rohde, L. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0045671 · Cited by 92 · see citing works
Pisapia, N. D., Turatto, M., Lin, P., Jovicich, J., & Caramazza, A. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr146 · Cited by 52 · see citing works
Altered self-referential network in resting-state amnestic type mild cognitive impairment.
Bai, F., Shi, Y.-M., Yuan, Y.-G., Wang, Y., Yue, C., Teng, Y., Wu, D., Zhang, Z.-S., Jia, J., & Zhang, Z.-J. (2012) · Cortex; a journal devoted to the study of the nervous system and behavior · doi:10.1016/j.cortex.2011.02.011 · Cited by 41 · see citing works
Cho, S. C., Kim, B., Kim, J., Kim, H. W., Choi, H. J., Jung, S. W., Yang, Y. H., Chungh, D.-S., Bock-Ja, G., Kim, B. S., et al. (2007) · Journal of korean Academy of Child and Adolescent Psychiatry · Cited by 35 · see citing works
Self-citationJeong, B., Choi, J., & Kim, J.-W. (2012) · Korean Journal of Radiology · doi:10.3348/kjr.2012.13.3.265 · Cited by 12 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [20]Dupaul GJ PT, Anastopoulos AD, Reid R (1998) The ADHD rating scale-IV: Checklists, norm, and clinical interpretation. New York: Guilford Press.
Cited by
Sorted by citations
Wang, T., Zhang, X., Li, A., Zhu, M., Liu, S., Qin, W., Li, J., Yu, C., Jiang, T., & Liu, B. (2017) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.02.011 · Cited by 88 · see citing works
Quasi-periodic patterns contribute to functional connectivity in the brain
Abbas, A., Belloy, M., Kashyap, A., Billings, J., Nezafati, M., Schumacher, E. H., & Keilholz, S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.076 · Cited by 81 · see citing works
Karcher, N. R., Michelini, G., Kotov, R., & Barch, D. M. (2021) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.09.008 · Cited by 55 · see citing works
Dajani, D. R., Burrows, C. A., Odriozola, P., Baez, A., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101678 · Cited by 33 · see citing works
“, 2019) and are virtually absent in the ADHD literature, where it is commonplace to forgo group matching on IQ (Choi et al., 2013).”
Hilger, K., & Fiebach, C. J. (2019) · Network Neuroscience · doi:10.1162/netn_a_00083 · Cited by 31 · see citing works
Wang, X., Cao, Q., Wang, J., Wu, Z., Wang, P., Sun, L., Cai, T., & Wang, Y. (2016) · Behaviour Research and Therapy · doi:10.1016/j.brat.2015.11.003 · Cited by 21 · see citing works
- Authors
- Choi, J., Jeong, B., Lee, S. W., & Go, H.-J.
- Affiliations
- The Catholic University of Korea Daejeon St. Mary's Hospital (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Corresponding author
- Jeong, Bumseok
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-12-26
- Volume
- 8
- Issue
- 12
- Pages
- e83516
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3873390
- OpenAlex
- W1994662974
- Cited by
- 58
- References
- 53
- Citations by year
- 2025: 4 · 2024: 2 · 2023: 2 · 2022: 7 · 2021: 3 · 2020: 5 · 2019: 8 · 2018: 8 · 2017: 4 · 2016: 8 · 2015: 7
- FWCI
- 3.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- National Research Foundation (NRF-2012R1A1A2001 and NRF-2006-2005372, NRF‐2006‐2005372, NRF-2012R1A1A2001)
- Ministry of Education, Science and Technology (N01130010, G04110085, N01130009)
- Korea Advanced Institute of Science and Technology
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Keywords
- attention deficit hyperactivity disorder, resting-state functional connectivity, functional networks, salience network, default mode network, precuneus, sensorimotor network, network maturation, developmental trajectories, continuous performance test, ADHD Rating Scale
- MeSH terms
- Adolescent, Algorithms, Attention Deficit Disorder with Hyperactivity, Brain, Brain Mapping, Child, Cognition, Female, Humans, Magnetic Resonance Imaging, Male, Neural Pathways, Risk Factors, Models, Statistical
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review