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Cited by 322

The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Development of the Default Mode and Central Executive Networks across early adolescence: A longitudinal study

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Sherman, Lauren E., Rudie, Jeffrey D., Pfeifer, Jennifer H., Masten, Carrie L., McNealy, Kristin, Dapretto, Mirella·2014·Developmental Cognitive Neuroscience
DOI 10.1016/j.dcn.2014.08.002
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Abstract

The mature brain is organized into distinct neural networks defined by regions demonstrating correlated activity during task performance as well as rest. While research has begun to examine differences in these networks between children and adults, little is known about developmental changes during early adolescence. Using functional magnetic resonance imaging (fMRI), we examined the Default Mode Network (DMN) and the Central Executive Network (CEN) at ages 10 and 13 in a longitudinal sample of 45 participants. In the DMN, participants showed increasing integration (i.e., stronger within-network correlations) between the posterior cingulate cortex (PCC) and the medial prefrontal cortex. During this time frame participants also showed increased segregation (i.e., weaker between-network correlations) between the PCC and the CEN. Similarly, from age 10 to 13, participants showed increased connectivity between the dorsolateral prefrontal cortex and other CEN nodes, as well as increasing DMN segregation. IQ was significantly positively related to CEN integration at age 10, and between-network segregation at both ages. These findings highlight early adolescence as a period of significant maturation for the brain's functional architecture and demonstrate the utility of longitudinal designs to investigate neural network development.

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Research works printed but not linked: 37

  1. Anderson, 2011, Network anticorrelations, global regression, and phase-shifted soft tissue correction, Hum. Brain Mapp., 32, 919, 10.1002/hbm.21079 · DOI · Paper page
  2. Canivez, 1998, Long-term stability of the Wechsler intelligence scale for children—third edition, Psychol. Assess., 10, 285, 10.1037/1040-3590.10.3.285 · DOI
  3. Chang, 2009, Effects of model-based physiological noise correction on default mode network anti-correlations and correlations, Neuroimage, 47, 1448, 10.1016/j.neuroimage.2009.05.012 · DOI · Paper page
  4. Chen, 2013, Causal interactions between fronto-parietal central executive and default-mode networks in humans, Proc. Natl. Acad. Sci. U. S. A., 201311772
  5. Dennis, 2013, Mapping connectivity in the developing brain, Int. J. Dev. Neurosci., 31, 525, 10.1016/j.ijdevneu.2013.05.007 · DOI · Paper page
  6. Dosenbach, 2010, Prediction of individual brain maturity using fMRI, Science, 329, 1358, 10.1126/science.1194144 · DOI · Paper page
  7. Fair, 2007, Development of distinct control networks through segregation and integration, Proc. Natl. Acad. Sci. U. S. A., 104, 13507, 10.1073/pnas.0705843104 · DOI · Paper page
  8. Fair, 2007, A method for using blocked and event-related fMRI data to study “resting state” functional connectivity, Neuroimage, 35, 396, 10.1016/j.neuroimage.2006.11.051 · DOI · Paper page
  9. Gordon, 2011, Strength of default mode resting-state connectivity relates to white matter integrity in children, Dev. Sci., 14, 738, 10.1111/j.1467-7687.2010.01020.x · DOI
  10. Gusnard, 2001, Medial prefrontal cortex and self-referential mental activity: relation to a default mode of brain function, Proc. Natl. Acad. Sci. U. S. A., 98, 4259, 10.1073/pnas.071043098 · DOI · Paper page
  11. Hallquist, 2013, The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity, Neuroimage, 82, 208, 10.1016/j.neuroimage.2013.05.116 · DOI · Paper page
  12. Harris, 2014, Altered functional connectivity of the default mode network in diffuse gliomas measured with pseudo-resting state fMRI, J. Neurooncol., 116, 373, 10.1007/s11060-013-1304-2 · DOI
  13. Hwang, 2013, The development of hub architecture in the human functional brain network, Cereb. Cortex, 23, 2380, 10.1093/cercor/bhs227 · DOI · Paper page
  14. Jung, 2007, The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence, Behav. Brain Sci., 30, 135, 10.1017/S0140525X07001185 · DOI · Paper page
  15. Langeslag, 2013, Functional connectivity between parietal and frontal brain regions and intelligence in young children: the Generation R study, Hum. Brain Mapp., 34, 3299, 10.1002/hbm.22143 · DOI
  16. Li, 2014, Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence, AJNR, 10.3174/ajnr.A3850 · DOI
  17. Maddock, 1999, The retrosplenial cortex and emotion: new insights from functional neuroimaging of the human brain, Trends Neurosci., 22, 310, 10.1016/S0166-2236(98)01374-5 · DOI · Paper page
  18. McNealy, 2006, Cracking the language code: neural mechanisms underlying speech parsing, J. Neurosci., 26, 7629, 10.1523/JNEUROSCI.5501-05.2006 · DOI · Paper page
  19. McNealy, 2010, The neural basis of speech parsing in children and adults, Dev. Sci., 13, 385, 10.1111/j.1467-7687.2009.00895.x · DOI
  20. McNealy, 2011, Age and experience shape developmental changes in the neural basis of language-related learning, Dev. Sci., 14, 1261, 10.1111/j.1467-7687.2011.01075.x · DOI
  21. Miranda-Dominguez, 2014, Bridging the gap between the human and macaque connectome: a quantitative comparison of global interspecies structure–function relationships and network topology, J. Neurosci., 34, 5552, 10.1523/JNEUROSCI.4229-13.2014 · DOI · Paper page
  22. Power, 2012, Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion, Neuroimage, 59, 2142, 10.1016/j.neuroimage.2011.10.018 · DOI · Paper page
  23. Santarnecchi, 2014, Efficiency of weak brain connections support general cognitive functioning, Hum. Brain Mapp., 10.1002/hbm.22495 · DOI · Paper page
  24. Satterthwaite, 2013, An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data, Neuroimage, 64, 240, 10.1016/j.neuroimage.2012.08.052 · DOI · Paper page
  25. Satterthwaite, 2012, Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth, Neuroimage, 60, 623, 10.1016/j.neuroimage.2011.12.063 · DOI · Paper page
  26. Sato, 2008, Adolescents and androgens, receptors and rewards, Horm. Behav., 53, 647, 10.1016/j.yhbeh.2008.01.010 · DOI
  27. Schlegel, 1995, A cross-cultural approach to adolescence, Ethos, 23, 15, 10.1525/eth.1995.23.1.02a00020 · DOI
  28. Smyzer, 2010, Longitudinal analysis of neural network development in preterm infants, Cereb. Cortex, 20, 2852, 10.1093/cercor/bhq035 · DOI · Paper page
  29. Song, 2008, Brain spontaneous functional connectivity and intelligence, Neuroimage, 41, 1168, 10.1016/j.neuroimage.2008.02.036 · DOI · Paper page
  30. Supekar, 2010, Development of functional and structural connectivity within the default mode network in young children, Neuroimage, 52, 290, 10.1016/j.neuroimage.2010.04.009 · DOI · Paper page
  31. Thomason, 2008, Default-mode function and task-induced deactivation have overlapping brain substrates in children, Neuroimage, 41, 1493, 10.1016/j.neuroimage.2008.03.029 · DOI
  32. Uddin, 2010, Typical and atypical development of functional human brain networks: insights from resting-state FMRI, Front. Syst. Neurosci., 4, 21, 10.3389/fnsys.2010.00021 · DOI · Paper page
  33. Uddin, 2011, Dynamic reconfiguration of structural and functional connectivity across core neurocognitive brain networks with development, J. Neurosci., 31, 18578, 10.1523/JNEUROSCI.4465-11.2011 · DOI · Paper page
  34. Van Dijk, 2012, The influence of head motion on intrinsic functional connectivity MRI, Neuroimage, 59, 431, 10.1016/j.neuroimage.2011.07.044 · DOI · Paper page
  35. von dem Hagen, 2013, Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions, Soc. Cogn. Affect. Neurosci., 8, 694, 10.1093/scan/nss053 · DOI · Paper page
  36. Wang, 2011, Regional homogeneity of the resting-state brain activity correlates with individual intelligence, Neurosci. Lett., 488, 275, 10.1016/j.neulet.2010.11.046 · DOI
  37. Watkins, 2013, Long-term stability of the Wechsler intelligence scale for children—fourth edition, Psychol. Assess., 25, 477, 10.1037/a0031653 · DOI · Paper page

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Metadata

Authors
Sherman, L. E., Rudie, J. D., Pfeifer, J. H., Masten, C. L., McNealy, K., & Dapretto, M.
Venue
Developmental Cognitive Neuroscience
Publisher
Elsevier BV
Published
2014-10
Volume
10
Pages
148-159
ISSN
1878-9293 (ISSN-L)
DOI
10.1016/j.dcn.2014.08.002
OpenAlex
W2051925828
Cited by
322
References
38
FWCI
10.21
Type
journal article
Language
en
Open access
gold
Licence
Funders
  • Brain Mapping Medical Research Organization
  • Brain Mapping Support Foundation
  • Pierson–Lovelace Foundation
  • Ahmanson Foundation
  • Tamkin Foundation
  • Jennifer Jones–Simon Foundation
  • Capital Group Companies Charitable Foundation
  • Northern Piedmont Community Foundation
  • Northstar Fund
  • National Center for Research Resources (RR12169, RR13642, RR00865)

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CoChat. (2026). Citation check: Development of the Default Mode and Central Executive Networks across early adolescence: A longitudinal study. https://app.cochat.ai/papers/10.1016/j.dcn.2014.08.002
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Sherman, L. E., Rudie, J. D., Pfeifer, J. H., Masten, C. L., McNealy, K., & Dapretto, M. (2014). Development of the Default Mode and Central Executive Networks across early adolescence: A longitudinal study. Developmental Cognitive Neuroscience. https://doi.org/10.1016/j.dcn.2014.08.002

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