The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Atypical Default Network Connectivity in Youth with Attention-Deficit/Hyperactivity Disorder
Open accessAbstract
Background Attention-deficit/hyperactivity disorder (ADHD) is a major public health concern. It has been suggested that the brain's default network may provide a crucial avenue for understanding the neurobiology of attention deficit/hyperactivity disorder. Evaluations of the default network have increased over recent years with the applied technique of resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). These investigations have established that spontaneous activity in this network is highly correlated at rest in young adult populations. This coherence seems to be reduced in adults with ADHD. This is an intriguing finding, as coherence in spontaneous activity within the default network strengthens with age. Thus, the pathophysiology of ADHD might include delayed or disrupted maturation of the default network. If so, it is important to determine whether an altered developmental picture can be detected using rs-fcMRI in children with ADHD.Methods This study used the typical developmental context provided previously by Fair et al. (2008) to examine coherence of brain activity within the default network using rs-fcMRI in children with (n = 23) and without attention deficit/hyperactivity disorder (n = 23).Results We found that functional connections previously shown as developmentally dynamic in the default network were atypical in children with attention deficit/hyperactivity disorder-consistent with perturbation or failure of the maturational processes.Conclusions These findings are consistent with the hypothesis that atypical consolidation of this network over development plays a role in attention deficit/hyperactivity disorder.
Overview
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
Verification
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?
In the citing paper
“Connections to the default network were atypical in ADHD in all the three subgroups, corroborating previous findings of atypical connectivity between the nucleus accumbens and regions of the default network in a group of children with ADHD combined type (which shared some participants with the current study) (Costa Dias et al., 2012), and of atypical integration of this network in ADHD (Castellano”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2010
In the citing paper
“The default mode network is implicated in ADHD (Fair et al., 2010) and is associated with poorer attentional regulation in ADHD (Castellanos et al., 2008).”
From Mindfulness Meditation Training for Attention-Deficit/Hyperactivity Disorder in Adulthood: Current Empirical Support, Treatment Overview, and Future Directions (2015) · cites this paper as Fair et al., 2010
In the citing paper
“Another example includes assessment of the default mode network, which is another promising target for mindfulness (Sood & Jones, 2013) and is implicated in ADHD (Castellanos et al., 2008; Fair et al., 2010)”
From Mindfulness Meditation Training for Attention-Deficit/Hyperactivity Disorder in Adulthood: Current Empirical Support, Treatment Overview, and Future Directions (2015) · cites this paper as Fair et al., 2010
In the citing paper
“in the first section we found that NAcc is atypically connected to several cortical regions in children with ADHD, including regions previously shown to present atypical correlated spontaneous activity in adults and children with the disorder (Castellanos et al., 2008; Fair et al., 2010; Mills et al., 2012).”
From Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder (2013) · cites this paper as Fair et al., 2010
In the citing paper
“Rs-fcMRI has been used to study brain functional connectivity in ADHD (Castellanos et al., 2008; Fair et al., 2010), but studies focusing on cortical-subcortical connections remain infrequent.”
From Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder (2013) · cites this paper as Fair et al., 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
KAUFMAN, J., BIRMAHER, B., BRENT, D., RAO, U., FLYNN, C., MORECI, P., WILLIAMSON, D., & RYAN, N. (1997) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-199707000-00021 · Cited by 10,148
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Co-planar stereotaxic atlas of the human brain
Laitinen, L. (1989) · Clinical Neurology and Neurosurgery · doi:10.1016/0303-8467(89)90128-5 · Cited by 7,565
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Research works printed but not linked: 2
- Gilbert, 2007, Comment on “Wandering minds: The default network and stimulus-Independent thought.”, Science, 317, 43, 10.1126/science.1140801 · DOI
- Castellanos, 2008, Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder, Biol Psychiatry, 63, 332, 10.1016/j.biopsych.2007.06.025 · DOI · Paper page
Cited by
Sorted by citations
Items 201–300 of 353
Yamamuro, K., Ota, T., Iida, J., Nakanishi, Y., Suehiro, Y., Matsuura, H., Uratani, M., Okazaki, K., Kishimoto, N., Tanaka, S., et al. (2016) · Neuropsychobiology · doi:10.1159/000444490 · Cited by 23
Effortful control and resting state networks: A longitudinal EEG study
Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Slobodskaya, H. R., Bairova, N. B., Tamozhnikov, S. S., & Stepanova, V. V. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.01.031 · Cited by 25
Matthews, M., & Fair, D. A. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12335 · Cited by 21
Self-citationLifespan associations of resting-state brain functional networks with ADHD symptoms
Wang, R., Fan, Y., Wu, Y., Zang, Y., & Zhou, C. (2022) · iScience · doi:10.1016/j.isci.2022.104673 · Cited by 21
Battel, L., Kieling, R. R., Kieling, C., Anés, M., Aurich, N. K., da Costa, J. C., Rohde, L. A., & Franco, A. R. (2016) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/cap.2015.0221 · Cited by 20
Ding, C., Xiang, J., Cui, X., Wang, X., Li, D., Chen, C., & Wang, B. (2020) · Journal of Attention Disorders · doi:10.1177/1087054720959712 · Cited by 19
Cai, W., Chen, T., Szegletes, L., Supekar, K., & Menon, V. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.10.017 · Cited by 20
RetractedAlterations in Structural and Functional Connectivity in ADHD: Implications for Theories of ADHD
González-Madruga, K., Staginnus, M., & Fairchild, G. F. (2022) · Current topics in behavioral neurosciences · doi:10.1007/7854_2022_345 · Cited by 19
Cognitive characterization of children with Dravet syndrome: A neurodevelopmental perspective
Acha, J., Pérez, A., Davidson, D. J., & Carreiras, M. (2014) · Child Neuropsychology · doi:10.1080/09297049.2014.959480 · Cited by 21
Hasler, R., Preti, M. G., Meskaldji, D. E., Prados, J., Adouan, W., Rodriguez, C. K., Toma, S., Hiller, N., Ismaili, T., Hofmeister, J., et al. (2017) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2017.09.004 · Cited by 19
Lee, D., Knight, E. Q., Song, H., Lee, S., Pae, C., Yoo, S., & Park, H. (2021) · PLoS ONE · doi:10.1371/journal.pone.0260295 · Cited by 20
Trait-Based Profiles of ADHD in Adolescents and Young Adults
Smith, T. E., & Martel, M. M. (2018) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2018.1491004 · Cited by 20
Duffy, F. H., Shankardass, A., McAnulty, G. B., & Als, H. (2017) · BMC Medicine · doi:10.1186/s12916-017-0805-9 · Cited by 19
Pedersini, C. A., Guàrdia‐Olmos, J., Montalà-Flaquer, M., Cardobi, N., Sánchez-López, J., Parisi, G., Savazzi, S., & Marzi, C. A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0226816 · Cited by 19
Zhu, D. C., & Majumdar, S. (2012) · Journal of Neuroimaging · doi:10.1111/j.1552-6569.2012.00768.x · Cited by 18
A neural window on the emergence of cognition
Cusack, R., Ball, G., Smyser, C. D., & Dehaene‐Lambertz, G. (2016) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13036 · Cited by 23
Wang, Y., Tao, F., Zuo, C., Kanji, M., Hu, M., & Wang, D. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00300 · Cited by 18
Towards personalized precision functional mapping in infancy
Moore, L. A., Hermosillo, R. J. M., Feczko, E., Moser, J., Koirala, S., Allen, M. C., Buß, C., Conan, G., Juliano, A., Marr, M. C., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00165 · Cited by 18
Self-citationDavis, B., Jovicich, J., Iacovella, V., & Hasson, U. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs416 · Cited by 17
A Neuropsychological Perspective on Attention Problems in Neurofibromatosis Type 1
Templer, A. K., Titus, J. B., & Gutmann, D. H. (2012) · Journal of Attention Disorders · doi:10.1177/1087054711433422 · Cited by 20
Yao, D.-R., Guo, X., Zhao, Q.-H., Liu, L., Cao, Q.-J., Wang, Y.-F., Calhoun, V., Sun, L., & Sui, J. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/embc.2018.8513155 · Cited by 12
Soman, S. M., Vijayakumar, N., Ball, G., Hyde, C. E., & Silk, T. J. (2022) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2022.01.001 · Cited by 14
Mizuno, Y., Cai, W., Supekar, K., Makita, K., Takiguchi, S., Silk, T. J., Tomoda, A., & Menon, V. (2022) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2022.10.001 · Cited by 18
Imaging the “At-Risk” Brain: Future Directions
Koyama, M. S., Martino, A. D., Castellanos, F. X., Ho, E. J., Marcelle, E. T., LEVENTHAL, B. L., & Milham, M. P. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715001356 · Cited by 16
Miranda, P., Cox, C. D., Alexander, M., Danev, S., & Lakey, J. R. T. (2020) · Medical Devices Evidence and Research · doi:10.2147/mder.s241205 · Cited by 18
Scofield, J. E., Johnson, J. D., Wood, P. K., & Geary, D. C. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218891 · Cited by 16
Empirical Bayes estimation of pairwise maximum entropy model for nonlinear brain state dynamics
Jeong, S., Kang, J., Pae, C., Eo, J., Park, S., Son, J., & Park, H. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118618 · Cited by 14
Millevert, C., Vidas-Guscic, N., Vanherp, L., Jonckers, E., Verhoye, M., Staelens, S. G., Bertoglio, D., & Weckhuysen, S. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1043-23.2023 · Cited by 17
Unfolding neurodevelopmental disorders: The mystery of developing connections
Neul, J. L. (2011) · Nature Medicine · doi:10.1038/nm.2552 · Cited by 15
Jung, M., Mizuno, Y., Fujisawa, T. X., Takiguchi, S., Kong, J., Kosaka, H., & Tomoda, A. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy269 · Cited by 16
What do ADHD Neuroimaging Studies Reveal for Teachers, Teacher Educators and Inclusive Education?
Boon, H. J. (2020) · Child & Youth Care Forum · doi:10.1007/s10566-019-09542-4 · Cited by 16
Ahmadi, M., Kazemi, K., Kuć, K., Cybulska-Kłosowicz, A., Helfroush, M. S., & Aarabi, A. (2021) · Brain Sciences · doi:10.3390/brainsci11070938 · Cited by 14
Cao, J., Yang, L., Yu, H., Zhao, X., Li, Y., & Wang, S. (2017) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2017.10.005 · Cited by 14
Luo, Y., Schulz, K. P., Alvarez, T. L., Halperin, J. M., & Li, X. (2018) · Cortex · doi:10.1016/j.cortex.2018.09.013 · Cited by 14
Assessment of ADHD Through Electroencephalographic Measures of Functional Connectivity
González, J. J., Alba, G., Mañas, S., González, A., & Pereda, E. (2015) · InTech eBooks · doi:10.5772/60559 · Cited by 14
Hsu, C.-F., Broyd, S. J., Helps, S. K., Benikos, N., & Sonuga-Barke, E. J. S. (2013) · Brain Research · doi:10.1016/j.brainres.2013.05.043 · Cited by 14
Siniatchkin, M., Moehring, J., Kroeher, B., Galka, A., von Ondarza, G., Moeller, F., Wolff, S., Tagliazucchi, E., Steinmann, E., Boor, R., et al. (2018) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2018.07.001 · Cited by 14
Attention‐Deficit/Hyperactivity Disorder
Nigg, J. T. (2017) · Wiley eBooks · doi:10.1002/9781394258932.ch13 · Cited by 14
Self-citationIntranasal oxytocin in rhesus monkeys alters brain networks that detect social salience and reward
Parr, L. A., Mitchell, T., & Hecht, E. E. (2018) · American Journal of Primatology · doi:10.1002/ajp.22915 · Cited by 13
Differences in brain networks of children with ADHD: Whole‐brain analysis of resting‐state fMRI
İçer, S., Benli, Ş. G., & Özmen, S. (2019) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22348 · Cited by 13
Guo, P., Lang, S., Jiang, M., Wang, Y., Zeng, Z., Wen, Z., Liu, Y., & Chen, B. T. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.678910 · Cited by 14
Contextual and Developmental Differences in the Neural Architecture of Cognitive Control
Petrican, R., & Grady, C. L. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0667-17.2017 · Cited by 14
Álvarez, D. M. H., Pacheco, L., Velasco-Segura, R., de la Mora, M. P., Romero, C. T., & García, N. G. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00209 · Cited by 13
Dysfunctional brain network organization in neurodevelopmental disorders
Henry, T. R., & Cohen, J. R. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-813838-0.00005-4 · Cited by 15
Diao, Y., Huang, Y., Zhu, B., Guo, M., Wang, W., Li, Z., Li, W., Zhang, H., Zhou, J., Li, X., et al. (2026) · Research · doi:10.34133/research.1115 · Cited by 12
Hung, Y., Dallenbach, N. T., Green, A., Gaillard, S. L., Capella, J., Hoskova, B., Vater, C. H., Cooper, E., Rudberg, N., Takahashi, A., et al. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.115039 · Cited by 13
Kember, J., Stepien, L., Panda, E., & Tekok-Kılıç, A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0277382 · Cited by 12
Liu, L., Chen, D., Huang, F., Jia, T., Cheng, W., Pan, M., Zhao, M., Bu, X., Liao, X., Wang, Y., et al. (2024) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14900 · Cited by 12
Jeong, B., Choi, J., & Kim, J.-W. (2012) · Korean Journal of Radiology · doi:10.3348/kjr.2012.13.3.265 · Cited by 13
Pediatric ADHD symptom burden relates to distinct neural activity across executive function domains
Nugiel, T., Roe, M. A., Engelhardt, L. E., Mitchell, M. E., Zheng, A., & Church, J. A. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102394 · Cited by 13
Akhrif, A., Romanos, M., Peters, K., Furtmann, A.-K., Caspers, J., Lesch, K., Meisenzahl‐Lechner, E., & Neufang, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282813 · Cited by 12
State-Dependent Effective Connectivity in Resting-State fMRI
Park, H., Eo, J., Pae, C., Son, J., Park, S., & Kang, J. (2021) · Frontiers in Neural Circuits · doi:10.3389/fncir.2021.719364 · Cited by 12
Cai, W., Mizuno, Y., Tomoda, A., & Menon, V. (2023) · Neuropsychopharmacology · doi:10.1038/s41386-023-01668-3 · Cited by 12
Variability of kinematic graphomotor fluency in adults with ADHD
Duda, T. A., Casey, J. E., & McNevin, N. H. (2014) · Human Movement Science · doi:10.1016/j.humov.2014.07.006 · Cited by 12
Developmental implications of children’s brain networks and learning
Chan, J. S. Y., Wang, Y., Yan, J. H., & Chen, H. (2016) · Reviews in the Neurosciences · doi:10.1515/revneuro-2016-0007 · Cited by 12
Farré‐Colomés, À., Gerhardt, S., Luderer, M., Sobanski, E., Kiefer, F., & Vollstädt‐Klein, S. (2021) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.14593 · Cited by 14
Manouilenko, I., Pagani, M., Stone‐Elander, S., Odh, R., Brolin, F., Hatherly, R., Jacobsson, H., Larsson, S., & Bejerot, S. (2013) · Research in Autism · doi:10.1016/j.rasd.2012.12.008 · Cited by 13
Variations in Structural MRI Quality Significantly Impact Commonly-Used Measures of Brain AnatomyPreprint
Gilmore, A. D., Buser, N. J., & Hanson, J. L. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/581876 · Cited by 12
Sastry, N. C., & Banerjee, A. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02929-5 · Cited by 10
Functional brain networks predicting sustained attention are not specific to perceptual modality
Corriveau, A., Ke, J., Terashima, H., Kondo, H. M., & Rosenberg, M. D. (2024) · Network Neuroscience · doi:10.1162/netn_a_00430 · Cited by 12
Horowitz‐Kraus, T., Woodburn, M., Rajagopal, A., Versace, A., Kowatch, R. A., Bertocci, M. A., Bebko, G. M., Almeida, J., Perlman, S. B., Travis, M. J., et al. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.02.034 · Cited by 12
Development of lateral pulvinar resting state functional connectivity and its role in attention
Huang, R. W., & Barber, A. D. (2020) · Cortex · doi:10.1016/j.cortex.2020.12.004 · Cited by 10
Scheel, N., Tarumi, T., Tomoto, T., Cullum, C. M., Zhang, R., & Zhu, D. C. (2021) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x211064846 · Cited by 11
Jurgiel, J., Miyakoshi, M., Dillon, A., Piacentini, J. C., & Loo, S. K. (2022) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2022.10.003 · Cited by 11
Deng, H., Huang, Z.-M., Li, Z., Cao, L., He, Y., Sun, N., Zeng, Y., & Wu, J. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1098526 · Cited by 10
RESTING STATE FUNCTIONAL MRI. GENERAL ISSUES AND CLINICAL APPLICATION
Bukkieva, T., Chegina, D. S., Efimtsev, A. Y., Levchuk, A. G., Iskhakov, D. N., Sokolov, A. V., Fokin, V. A., & Труфанов, Г. Е. (2019) · Russian Electronic Journal of Radiology · doi:10.21569/2222-7415-2019-9-2-150-170 · Cited by 11
Fan, Y., Wang, R., Lin, P., & Wu, Y. (2019) · PLoS ONE · doi:10.1371/journal.pone.0222414 · Cited by 9
Estimating Electroencephalograph Network Parameters Using Mutual Information
Thuraisingham, R. A. (2018) · Brain Connectivity · doi:10.1089/brain.2017.0529 · Cited by 8
Zhu, Z., Lei, D., Qin, K., Li, X., Li, W., Tallman, M. J., Patino, L. R., Fleck, D. E., Aghera, V., Gong, Q., et al. (2023) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.220209 · Cited by 8
Rafi, H., Delavari, F., Perroud, N. A., Derome, M., & Debbané, M. (2023) · PLoS ONE · doi:10.1371/journal.pone.0279260 · Cited by 8
Proal, E., Gonzalez-Olvera, J. J., Blancas‐Velazquez, A. S., Chalita, P. J., & Castellanos, F. X. (2013) · PubMed · Cited by 8
Duffy, K. A., & Helwig, N. E. (2024) · NeuroSci · doi:10.3390/neurosci5040033 · Cited by 8
Toffoli, L., Zdorovtsova, N., Epihova, G., Duma, G. M., Cristaldi, F. D. P., Pastore, M., Astle, D. E., & Mento, G. (2024) · Human Brain Mapping · doi:10.1002/hbm.70011 · Cited by 7
Hong, Y. N., Hwang, H., Hong, J. S., & Han, D. H. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.03.021 · Cited by 9
Hakimdavoodi, H., & Amirmazlaghani, M. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab965b · Cited by 7
Attention Deficit Hyperactivity Disorder (Adhd)
Pearson, G. S., & Crowley, A. A. (2012) · Wiley eBooks · doi:10.1002/9781118704660.ch7 · Cited by 7
Proal, E., Olvera, J. G., Blancas‐Velazquez, A. S., Chalita, P. J., & Castellanos, F. X. (2013) · Revista de Neurología · doi:10.33588/rn.57s01.2013293 · Cited by 7
Atypical functional connectivity in adolescents and adults with persistent and remitted ADHDPreprint
Michelini, G., Jurgiel, J., Bakolis, I., Cheung, C. H. M., Asherson, P., Loo, S., Kuntsi, J., & Mohammad-Rezazadeh, I. (2017) · bioRxiv · doi:10.1101/201772 · Cited by 2
Controllability in attention deficit hyperactivity disorder brains
Chen, B., Sun, W., & Yan, C. (2024) · Cognitive Neurodynamics · doi:10.1007/s11571-023-10063-z · Cited by 6
Acute inflammatory ankle arthritis in Northern India.
Gogia, A., & Kakar, A. (2011) · PubMed · Cited by 6
Wu, X., Guo, Y., Xue, J., Dong, Y., Sun, Y., Wang, B., Xiang, J., & Liu, Y. (2023) · Brain Sciences · doi:10.3390/brainsci13091331 · Cited by 6
Ren, Y., Hu, X., Lv, J., Quo, L., Han, J., & Liu, T. (2016) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2016.7493500 · Cited by 6
Mindfulness Intervention for Attention-Deficit/Hyperactivity Disorder: Theory and Action Mechanisms
Schoenberg, P. L. A. (2016) · Springer eBooks · doi:10.1007/978-3-319-29866-5_17 · Cited by 6
Borlase, N., Melzer, T. R., Eggleston, M. J. F., Darling, K. A., & Rucklidge, J. J. (2019) · Nutritional Neuroscience · doi:10.1080/1028415x.2019.1574329 · Cited by 6
Araiza, J. F. R. (2014) · Salud Mental · doi:10.17711/sm.0185-3325.2014.009 · Cited by 15
Personality and resting state networks in children: A longitudinal EEG study
Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Slobodskaya, H. R., & Bairova, N. B. (2017) · Personality and Individual Differences · doi:10.1016/j.paid.2017.03.012 · Cited by 5
Rubinson, M., Horowitz, I., Naim‐Feil, J., Gothelf, D., Moses, E., & Levit‐Binnun, N. (2019) · Brain Connectivity · doi:10.1089/brain.2018.0630 · Cited by 5
Attention Deficit/Hyperactivity Disorder
Cortese, S., & Castellanos, F. X. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-398270-4.00004-5 · Cited by 5
Pearson, G. S. (2012) · The Nurse Practitioner · doi:10.1097/01.npr.0000418391.21853.07 · Cited by 4
Attention Deficit Hyperactivity Disorder
Marco, P., Maddalena, M., Bertella, S., Gatti, E., & Nobile, M. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820472-6.00164-x · Cited by 5
The Role of Glutamate Dysregulation in the Etiology of ADHD
Glaser, P. E. A., Batten, S. R., & Gerhardt, G. A. (2022) · Springer eBooks · doi:10.1007/978-3-030-87480-3_16 · Cited by 4
Zolghadr, Z., Batouli, S. A. H., Tehrani‐Doost, M., Shafaghi, L., Hadjighassem, M., Majd, H. A., & Mehrabi, Y. (2023) · Archives of Neuroscience · doi:10.5812/ans-134329 · Cited by 4
Frequency-specific alterations in low-frequency functional connectivity in children with ADHD
Fateh, A. A., Muhammed, H., Mohammed, A. A. Q., Smahi, A., Alarefi, A., Zhang, L., Yue, F., & Zeng, H. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-07586-6 · Cited by 3
Kashyap, R., Holla, B., Bhattacharjee, S., Sharma, E., Mehta, U. M., Vaidya, N., Bharath, R. D., Murthy, P., Basu, D., Nanjayya, S. B., et al. (2024) · Psychological Medicine · doi:10.1017/s0033291724000710 · Cited by 3
Wall, J., Miller, G. N., Taylor, J. J., Stubbs, J. L., Warfield, S. K., & Cohen, A. L. (2025) · Annals of the Child Neurology Society · doi:10.1002/cns3.20108 · Cited by 3
Vidal, L. M., Martínez‐Garcia, M., Blas, D. M.-D., Navas-Sánchez, F. J., Pretus, C., Ramos‐Quiroga, J. A., Vanesa Richarte, B., Vilarroya, Ó., Sepulcre, J., Desco, M., et al. (2022) · Journal of Attention Disorders · doi:10.1177/10870547211031998 · Cited by 3
Brain Functional Networks in the Developing Brain Using Resting BOLD
Gao, W., Zhou, H., Giovanello, K. S., Smith, J., Shen, D. G., Gilmore, J. H., & Lin, W. (2014) · InTech eBooks · doi:10.5772/58265 · Cited by 3
Sripada, C., Angstadt, M., Rutherford, S., Taxali, A., Greathouse, T., Clark, D. A., Hyde, L., Weigard, A., Brislin, S., Hicks, B. M., et al. (2020) · bioRxiv · doi:10.1101/2020.08.21.260927 · Cited by 4
Shu, Y., Zhang, Q., Liu, J., He, Q., & Hou, Y.-Z. (2025) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-025-02906-3 · Cited by 2
Proteomic Findings in ADHD: A Systematic Review
Karabulut, O. B., & Ünal, D. (2025) · International Journal of Developmental Neuroscience · doi:10.1002/jdn.70057 · Cited by 2
Metadata
- Authors
- 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.
- Affiliations
- Oregon Health & Science University (US)
- New York State Psychiatric Institute (US)
- Corresponding author
- Fair, Damien A.
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 68
- Issue
- 12
- Pages
- 1084-1091
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC2997893
- OpenAlex
- W2082502102
- Cited by
- 354
- References
- 77
- Citations by year
- 2026: 11 · 2025: 5 · 2024: 13 · 2023: 12 · 2022: 16 · 2021: 18 · 2020: 22 · 2019: 29 · 2018: 21 · 2017: 27 · 2016: 26 · 2015: 31 · 2014: 48 · 2013: 35 · 2012: 28
- FWCI
- 16.11
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Oregon Clinical and Translational Research Institute
- Medical Research Foundation
- UNCF Merck postdoctoral fellowship
- Ford Foundation
- Portland Alcohol Research Center pilot funds (P60 AA010760)
- Oregon Health and Science University Neuropsychiatric Institute
- 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 › Mind wandering and attention
- Keywords
- attention deficit hyperactivity disorder, default mode network, resting-state functional connectivity, children, brain maturation, developmental trajectories, spontaneous brain activity, neurodevelopmental hypothesis
- MeSH terms
- Adolescent, Age Factors, Attention Deficit Disorder with Hyperactivity, Brain, Brain Mapping, Child, Female, Humans, Magnetic Resonance Imaging, Male, Neural Pathways
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