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A Comprehensive Study of Whole-Brain Functional Connectivity in Children and Young Adults
Open accessAbstract
Over the past decade, examination of functional connectivity using functional magnetic resonance imaging has become an important tool to investigate functional changes in patient populations, healthy aging, and recently also child development. Most prior developmental studies focused on functional connectivity between brain regions important for cognitive or emotional control and the so-called "default-mode network." In the present study, we investigated whole-brain functional connectivity in children (11-13 years; N = 19) and young adults (19-25 years; N = 29), without a priori restrictions to specific regions. We found similar patterns of functionally connected regions in children and young adults, but there were differences in the size of functionally connected regions (i.e., the number of voxels), as well as in the strength of functional connectivity (i.e., the correlation value) between brain regions. This indicates that functional connectivity continues to change during adolescence. Developmental differences were found across the whole brain, but the effects differed for functional connectivity patterns associated with higher cognitive or emotional functions and functional connectivity patterns associated with basic visual and sensorimotor functions. Finally, we showed that the majority of functional connectivity differences could not be explained on the basis of gray matter density alone.
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“Thus, functional connectivity continues to change during and after adolescence, and these developmental differences in functional connectivity patterns were associated with higher cognitive or emotional functions and basic visual and sensorimotor functions.”
From Emerging Adulthood, a Pre-adult Life-History Stage (2020) · cites this paper as [34]
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“Thus, functional connectivity continues to change during and after adolescence, and these developmental differences in functional connectivity patterns were associated with higher cognitive or emotional functions and basic visual and sensorimotor functions.”
From Emerging Adulthood, a Pre-adult Life-History Stage (2020) · cites this paper as [34]
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Cites
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
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
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 7,018
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
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
Research works printed but not linked: 3
- Chiron, 1992, Journal of Nuclear Medicine, 33, 696
- 2009, 5, e100381
- 2004, 1, S208
Cited by
Sorted by citations
Items 101–181 of 181
Qiao, C., Yang, L., Calhoun, V. D., Xu, Z.-B., & Wang, Y. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.12.007 · Cited by 14
Functional connectivity differences in brain networks from childhood to youth
İçer, S. (2019) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22366 · Cited by 13
“Barber et al have found increased MPFC connections for the (8-12) and (20-47) age groups using rsfMRI.”
MethodWang, Y., Qiao, C., Qu, G., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3423803 · Cited by 13
“Itindicatesthatthebrainnetworkchangesfrom undifferentiatedtomorespecializedstructuresasage[67].”
Thornburgh, C. L., Narayana, S., Rezaie, R., Bydlinski, B. N., Tylavsky, F. A., Papanicolaou, A. C., Choudhri, A. F., & Völgyi, E. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00199 · Cited by 13
“…and toddlers during various stages of sleep (Fransson et al., 2011; Manning et al., 2013), in children under sedation (Funakoshi et al., 2016), in awake children (5–10 years old; de Bie et al., 2012), and adolescents (9–15 years old; Littow et al., 2010; Jolles et al., 2011; Thomason et al., 2011).”
BackgroundAbrol, A., Fu, Z., Du, Y., Wilson, T. W., Wang, Y., Stephen, J. M., & Calhoun, V. D. (2023) · Human Brain Mapping · doi:10.1002/hbm.26200 · Cited by 12
Behavioral Heterogeneity in Relation with Brain Functional Networks in Young Children
Chong-yaw Wee, A., Poh, J. S., Wang, Q., Broekman, B. F. P., Chong, Y. S., Kwek, K. Y. C., Shek, L. P., Saw, S., Gluckman, P. D., Fortier, M. V., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx205 · Cited by 13
Functional properties of extended body representations in the context of kinesthesia
Barra, J., Giroux, M., Métral, M., Cian, C., Luyat, M., Kavounoudias, A., & Guerraz, M. (2020) · Neurophysiologie Clinique · doi:10.1016/j.neucli.2020.10.011 · Cited by 15
Chuang, K., Ramakrishnapillai, S., Madden, K., Amant, J. S., McKlveen, K., Gwizdala, K. L., Dhullipudi, R., Bazzano, L., & Carmichael, O. T. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1110434 · Cited by 12
“These graphs have led to new observations about how the brain changes over the course of child development (Bitan et al., 2007; Fair et al., 2010; Jolles et al., 2011; Morken et al., 2017), various brain diseases (Achard and Bullmore, 2007; Fox and Greicius, 2010; Lynall et al.”
BackgroundFunctional connectivity of the pediatric brain
Argyropoulou, M. I., Xydis, V. G., & Astrakas, L. G. (2024) · Neuroradiology · doi:10.1007/s00234-024-03453-5 · Cited by 13
“Research indicates that the FC of a child’s brain becomes more similar to that of an adult as they age, with significant changes occurring during adolescence [ 5, 119].”
Emergence of Higher Cognitive Functions
Paz‐Alonso, P. M., Bunge, S. A., & Ghetti, S. (2014) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199935291.013.003 · Cited by 13
Association Between Age and Familial Risk for Alcoholism on Functional Connectivity in Adolescence
Vaidya, J. G., Elmore, A. L., Wallace, A. L., Langbehn, D. R., Kramer, J., Kuperman, S., & OʼLeary, D. S. (2019) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2018.12.008 · Cited by 13
Xu, F., Qiao, C., Zhou, H., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.12.007 · Cited by 11
Chen, L., Qiao, C., Ren, K., Qu, G., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120771 · Cited by 13
Wager, J., Lorenzo Fabrizi, D., & Tham, S. W. (2023) · Pain · doi:10.1097/j.pain.0000000000002923 · Cited by 13
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
“Infant and adult networks mainly differ from each other in the number of connected voxels and the connectivity strength (Jolles et al., 2011).”
BackgroundJiang, P., Tokariev, M., Aronen, E. T., Salonen, O. L. M., Ma, Y., Vuontela, V., & Carlson, S. (2014) · Brain and Cognition · doi:10.1016/j.bandc.2014.10.005 · Cited by 11
Development of Neural Networks Supporting Goal‐Directed Behavior
Johnson, E. L., Munro, S. E., & Bunge, S. A. (2013) · Wiley eBooks · doi:10.1002/9781118732373.ch2 · Cited by 13
“Regions associated with higher cognitive and emotional functions became more tightly coupled with age, while connectivity between regions linked to basic visual and sensorimotor functions showed the opposite effect (Jolles et al., 2011).”
BackgroundDuff, I. T., Krolick, K. N., Mahmoud, H., & Chidambaran, V. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12165176 · Cited by 11
“In addition, pain connectomes are more localized (Figure 1) at younger ages [71], defined more by anatomical proximity, which transition into more specialized neural networks with a more distributed architecture by young adulthood.”
BackgroundBrain Network Connectivity and Executive Function in Children with Infantile Hydrocephalus
Adam, R., Ghahari, D., Morton, J. B., Eagleson, R. A., & de Ribaupierre, S. (2022) · Brain Connectivity · doi:10.1089/brain.2021.0149 · Cited by 10
“These inconsistent connectivity findings may reflect the evolving interactions between large-scale networks that continue to develop throughout childhood (Betzel et al., 2014; Fair et al., 2007; Jolles et al., 2011; Marek et al., 2015; Zhong et al., 2014).”
Meijer, A., Königs, M., Pouwels, P. J. W., Smith, J., Visscher, C., Bosker, R., Hartman, E., & Oosterlaan, J. (2022) · Child Development · doi:10.1111/cdev.13759 · Cited by 8
The development of visuospatial processing
Stiles, J., Akshoomoff, N. A., & Haist, F. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-814411-4.00017-2 · Cited by 13
Mersov, A., Crane, D., Chappell, M. A., Black, S. E., & MacIntosh, B. J. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.02.017 · Cited by 10
Examining Brain Maturation during Adolescence Using Graph Laplacian Learning Based Fourier Transform
Wang, J.-Q., Xiao, L., Wilson, T., Stephen, J., Calhoun, V., & Wang, Y.-P. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108649 · Cited by 9
“A large number of studies have been conducted to uncover the changes in brain functional activity that occur throughout childhood and adolescence [4], [5], and to detect the functional difference between children and adult brain [6].”
BackgroundFunctional network estimation using multigraph learning with application to brain maturation study
Wang, J.-Q., Xiao, L., Hu, W.-X., Qu, G., Wilson, T., Stephen, J., Calhoun, V., & Wang, Y.-P. (2021) · Human Brain Mapping · doi:10.1002/hbm.25410 · Cited by 14
“Considerable research has been conducted to reveal the development of the brain from their functional activation differences throughout childhood and adolescence (Fair et al., 2009; Jolles, van Buchem, Crone, & Rombouts, 2010).”
BackgroundResultCastellanos, F. X., Cortese, S., & Proal, E. (2013) · Current topics in behavioral neurosciences · doi:10.1007/7854_2013_244 · Cited by 13
Lan, Y., Qiao, C., Zhou, H., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2023) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2023.3244921 · Cited by 9
“Both resting and task fMRIs suggest that the functions of the brain in processing information, working memory, and cognition are not mature in children compared with young adults [3].”
BackgroundGao, B., Yu, A., Qiao, C., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3467384 · Cited by 8
Zhu, W., He, J., Xiang, L., Wang, L., Lü, Z., Li, C., & Gong, J. (2017) · Child s Nervous System · doi:10.1007/s00381-017-3604-x · Cited by 8
Age-related changes in functional connectivity between young adulthood and late adulthood
Xu, X., Kuang, Q., Zhang, Y., Wang, H., Wen, Z., & Li, M. (2015) · Analytical Methods · doi:10.1039/c5ay00699f · Cited by 9
“They reported that both children and young adults showed similar spatial patterns of functionally connected regions and that the strength of the functional connectivity between brain regions was significantly different in these two groups [8].”
BackgroundMüller, C. P. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2020.112521 · Cited by 8
A hominoid-specific signaling axis regulating the tempo of synaptic maturation
Dong, J., Zhu, X.-N., Zeng, P.-M., Cao, D.-D., Yang, Y., Hu, J., & Luo, Z. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114548 · Cited by 7
Zhao, X. W., Wu, Q., Chen, Y., Song, X., Ni, H., & Ming, D. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00856 · Cited by 7
“Specifically, five metastates correspond to specific networks with FC, such as the FPN (Emerson and Cantlon, 2012; Di and Biswal, 2015; Lee and Telzer, 2016), OCC (Yan et al., 2011; Damoiseaux et al., 2016; Chen et al., 2017; Zhang et al., 2017), SMN (Jolles et al., 2011; Pujol et al., 2014; He et al., 2016; Syed et al.,…”
InfluentialVom Hirnbild zum guten Unterricht
Stubenrauch, C., Krinzinger, H., & Konrad, K. (2014) · Zeitschrift für Kinder- und Jugendpsychiatrie und Psychotherapie · doi:10.1024/1422-4917/a000298 · Cited by 11
Tapia‐Medina, M. G., Cosío‐Guirado, R., Peró, M., Cañete‐Massé, C., Villuendas‐González, E. R., & Guàrdia‐Olmos, J. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1576932 · Cited by 6
Intervenir auprès des enseignants en formation pour favoriser un développement global
Buysse, A. (2019) · Phronesis · doi:10.7202/1056317ar · Cited by 6
Xu, W., Ying, F., Luo, Y., Zhang, X., & Li, Z. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00379-3 · Cited by 6
“…al. 2015), or medial prefrontal cortex (Kelly et al. 2009); or examined multiple networks together (Sole-Padulles et al. 2016; Supekar et al. 2010; Jolles et al. 2011); however, these studies, though focused more on specific networks, have considered the “brake” (e.g. prefrontal network) and…”
BackgroundQiao, C., Gao, B., Liu, Y., Hu, X., Hu, W., Calhoun, V. D., & Wang, Y. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102941 · Cited by 7
Timar, L., Deplazes, S., Bothmann, J., Renzel, R., Ledergerber, D., Dubček, T., & Imbach, L. (2025) · Epilepsia · doi:10.1111/epi.18531 · Cited by 5
“29 Because our patient sample included children as well as adults, we compared functional connectivity between pediatric and adult patients within all four patient groups.”
The neural networks of touch observation
Schaefer, M., Kuehn, E., Schweitzer, F. M., & Muehlhan, M. (2023) · Imaging Neuroscience · doi:10.1162/imag_a_00065 · Cited by 6
“The dorsal attention network has been linked to top-down attention processes, which have been shown to improve and develop from early childhood to adolescence ( Jolles et al., 2011).”
BackgroundQiao, C., Gao, B., Lu, L.-J., Calhoun, V. D., & Wang, Y. (2019) · Applied Sciences · doi:10.3390/app9204298 · Cited by 5
“showed that the hyper-connectivity of young adults’ VN with other RSNs is enhanced, that is, young adults’ visual information processing ability is higher than that of children [33].”
BackgroundNature Contact Linked to Higher Levels of Positive Well-Being in Young Adults During the Pandemic
Cahn, P. R., & Duvall, J. (2022) · Ecopsychology · doi:10.1089/eco.2022.0059 · Cited by 8
“Furthermore, young people may feel stress more acutely than adults since the general neural systems that regulate emotion and executive functioning are still developing in early adulthood (Jolles, van Buchem, Crone, & Rombouts, 2011; Riediger & Klipker, 2014).”
Modelling developmental disorders
Thomas, M., Baughman, F. D., Karaminis, T., & Addyman, C. (2013) · Psychology Press eBooks · doi:10.4324/9780203100288-12 · Cited by 5
Iyer, A., Stanford, W., Dayan, E., & Xavier, R. M. (2025) · Schizophrenia · doi:10.1038/s41537-025-00687-x · Cited by 5
Developmental differences of large-scale functional brain networks for spoken word processing
Liu, X., Yin, H., Gao, Y., Booth, J. R., Zhang, L., Zhang, S., Lu, C., & Liu, L. (2022) · Brain and Language · doi:10.1016/j.bandl.2022.105149 · Cited by 4
Huang, C., Zhou, X., Ren, M., Zhang, W., Wan, K., Yin, J., Li, M., Li, Z., Zhu, X., & Sun, Z. (2023) · Journal of Neuroscience Research · doi:10.1002/jnr.25230 · Cited by 4
Kim, J., Ruesch, A., Kang, N. R., Huppert, T. J., Kainerstorfer, J. M., Thiessen, E. D., & Fisher, A. V. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.13.904029 · Cited by 4
Exploring the late maturation of an intrinsic episodic memory network: A resting-state fMRI study
Andrade, M. Â., Raposo, A., & Andrade, A. (2024) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2024.101453 · Cited by 3
“…s, a resting-state scan duration that has proven to produce reliable correlation estimates of network connectivity (Van Dijk et al., 2010) and that was already previously implemented with young developmental samples (that tend to show excessive motion in longer scan sessions; Jolles et al., 2011).”
Orlichenko, A., Su, K., Tian, Q., Shen, H., Deng, H.-W., & Wang, Y. (2024) · Journal of medical imaging · doi:10.1117/1.jmi.11.2.024010 · Cited by 3
Structural and Functional Imaging
Aga, V. M. (2018) · Springer eBooks · doi:10.1007/978-3-319-73078-3_15 · Cited by 3
Horien, C. L., Fontenelle, S., Joseph, K., Powell, N., Nutor, C., Fortes, D., Butler, M., Powell, K. K., Macris, D. M., Lee, K., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.04.975417 · Cited by 3
“Such analyses have been used extensively to characterize the brains of younger children [2-6] including those with autism spectrum disorder [6-10], and the hope is that one day such functional connectivity approaches can be used to help individual patients in clinical settings [11-13].”
BackgroundDeshpande, H. U., & Kohut, S. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.19.549741 · Cited by 3
Hidden Rhythms of a Developing Brain: Multimetric rs‐fMRI Insights Into Typical Youth Maturation
Tapia‐Medina, M. G., Cosío‐Guirado, R., Peró, M., Cañete‐Massé, C., Villuendas‐González, E. R., & Guàrdia‐Olmos, J. (2025) · Human Brain Mapping · doi:10.1002/hbm.70320 · Cited by 2
Abrol, A., & Calhoun, V. D. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9870916 · Cited by 2
“Notably, a previous study [16] confirmed reduced static FC in the sensorimotor and visual systems in children as well as young adults, whereas none of the trFNC states estimated in another recent study [17] revealed elevated connectivity between these domains in adolescence.”
BackgroundZhao, N., Chen, J., Wei, Y., Zhang, J., Ding, G., Georgiou, G. K., Meng, X., & Yang, X. (2025) · Journal of Neurolinguistics · doi:10.1016/j.jneuroling.2025.101266 · Cited by 2
Imprints of extreme prematurity on functional brain networks in school-aged children and adolescents
Tokariev, M., Vuontela, V., Tokariev, A., Lönnberg, P., ANDERSSON, S. M., Mäenpää, H., Metsäranta, M., Lano, A., & Carlson, S. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121447 · Cited by 2
Aging-Dependent Loss of Connectivity in Alzheimer’s Model Mice with Rescue by mGluR5 ModulatorPreprint
Mandino, F., Shen, X., Desrosiers-Grégoire, G., O’Connor, D. A., Mukherjee, B., Owens, A., Qu, A., Onofrey, J. A., Papademetris, X., Chakravarty, M. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571715 · Cited by 2
Horowitz‐Kraus, T., Kenett, Y. N., Link, D., Ashqar, E., & Farah, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.07.687207 · Cited by 2
“These findings are in line with developmental theories previously suggested 112 .”
Wang, Y., Li, S., He, J., Peng, L., Wang, Q., Zou, X., Tudorascu, D., Schaeffer, D. J., Schaeffer, L. K. H., Szczupak, D., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00503 · Cited by 1
“Research ( Jockwitz & Caspers, 2021; Jolles et al., 2011; Pruitt et al., 2024; Tomasi & Volkow, 2012) has shown that the human brain network undergoes substantial changes in both functional connectivity (FC) ( Friston, 2011) and cognitive functions throughout a person’s lifespan.”
Computational Approaches to Attention
Cohen, R. A. (2013) · Springer eBooks · doi:10.1007/978-0-387-72639-7_27 · Cited by 1
Ayyash, S., Sunderji, A., Gallant, H. D., Hall, A., Davis, A. D., Pokhvisneva, I., Meaney, M. J., Silveira, P. P., Sassi, R. B., & Hall, G. B. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1066373 · Cited by 1
Functional brain hubs are related to age: A primer study with rs-fMRI
Figueroa-Jiménez, M. D., Cañete‐Massé, C., Gudayol‐Ferré, E., Gallardo‐Moreno, G. B., Peró, M., & Guàrdia‐Olmos, J. (2024) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2024.100517 · Cited by 1
“…in the size of functional networks; thus, the functional connectivity of these networks in children is greater than in adolescents and adults, and these decreases in connectivity with age will be related to the refinement in the network ’ s development (Jolles et al., 2011; DeSerisy et al., 2021).”
BackgroundInfluentialCheuquemán, C., Cerda, C., Fernàndez‐Carriba, S., & León, M. (2025) · Revista Colombiana de Educación · doi:10.17227/rce.num96-19371 · Cited by 1
“Precisamente, los cambios durante el neurodesarrollo dependen de la rápida 22 acumulación de experiencias, y van acompañados de un entorno social cambiante en el que otras personas (compañeros, familia y profesores) desempeñan un papel fundamental (Jolles et al. , 2011).”
A self-attention model for robust rigid slice-to-volume registration of functional MRI
Khawaled, S., Afacan, O., Warfield, S. K., & Freiman, M. (2025) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2025.102643 · Cited by 1
Age-related changes in spatial and temporal features of resting state fMRIPreprint
Vij, S. G., Nomi, J. S., Dajani, D. R., & Uddin, L. Q. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/109181 · Cited by 1
Brain Maturation Study during Adolescence Using Graph Laplacian Learning Based Fourier Transform.Preprint
Wang, J.-Q., Xiao, L., Wilson, T., Stephen, J., Calhoun, V., & Wang, Y.-P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07211 · Cited by 2
“A significant amount of studies have been conducted to uncover the mechanisms about changes in brain functional activity that occur throughout childhood and adolescence [4], [5].”
BackgroundIndividual differences in intrinsic connectivity Networks I: retest and validation in resting state.
Wisner, K. (2012) · University of Minnesota Digital Conservancy (University of Minnesota)
Psychologische aspecten van diabetes per ontwikkelingsfase
Schaaijk, N. M.-V. (2015) · Tijdschrift voor kindergeneeskunde · doi:10.1007/s12456-015-0008-2
Auditory and Sensorimotor Resting State Networks in Children Preceding and Following Overt Speaking
Esch, J. (2014) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3x96m
“The authors’ interpretation of these findings was that the auditory and higher-order cognitive networks were not entirely refined and continued to develop into adulthood (Jolles et al., 2011).”
BackgroundInfluentialBenes, F. M., & Konopaske, G. T. (2012) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.716598020.792302857
Grohs, G., Hengerer, B., & Cruces-Solís, H. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.24.513480
“…these results are in line with longitudinal and cross-sectional studies in humans that show decreases in network functional connectivity from adolescence to adulthood, especially in within network connectivity (Fair et al., 2009; Jolles et al., 2011; Marek et al., 2015; Jiang et al., 2018).”
ResultOrlichenko, A., Su, K., Tian, Q., Shen, H., Deng, H., & Wang, Y. (2023) · doi:10.36227/techrxiv.23960856
Orlichenko, A., Su, K., Tian, Q., Shen, H., Deng, H., & Wang, Y. (2023) · PubMed · doi:10.48550/arxiv.2308.07992
Insights into brain network dynamics across ages using group-ICA functional parcellation
López-Medina, L. M., Paredes, O., Lora-Castro, S., Romo‐Vázquez, R., Morales, J. A., & Vélez-Pérez, H. A. (2024) · Franklin Open · doi:10.1016/j.fraope.2024.100178
Emerging Adulthood, Health, and Wellbeing
Waite‐Jones, J. M., & Rodriguez, A. (2025) · Springer eBooks · doi:10.1007/978-3-031-88177-0_3
La construction du schéma corporel dans un cerveau en développement
Fontan, A. (2017) · theses.fr (ABES) · doi:10.70675/cd3cc99fz444az42edza564za00a8aa3e9f5
Prochnow, A., Zhou, X., Ghorbani, F., Roessner, V., Hommel, B., & Beste, C. (2026) · Scientific Reports · doi:10.1038/s41598-026-46182-w
“Moreover, connectivity between brain regions—and thus the communication within the brain—also changes throughout adolescence 1,26–29 and should thus be taken into account when investigating the developmental changes in event segmentation.”
Functional reorganization of brain networks from childhood to adolescence: A multi-level approach
Tapia‐Medina, M. G., Cosío‐Guirado, R., Peró, M., Cañete‐Massé, C., Villuendas‐González, E. R., & Guàrdia‐Olmos, J. (2026) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2026.100700
“There is evidence suggesting that DMN reaches stability by late childhood, which may translate into focal reorganizations of key hubs rather than large-scale shifts in network-level connectivity (Jolles et al., 2011).”
Bellmont-Olson, L. M., Wright, M., Müller‐Oehring, E. M., Baker, F. C., Kiss, O., Pohl, K. M., Gotlib, I. H., & Schulte, T. (2026) · Journal of Affective Disorders Reports · doi:10.1016/j.jadr.2026.101129
Harvie, G., Monn, A., Olbrich, S., Korgaonkar, M. S., Kohn, M. R., & Griffiths, K. R. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106949
Lower engagement of cognitive control in children on ChatGPT
Horowitz‐Kraus, T., Kenett, Y. N., Link‐Sourani, D., Ashqar, E., & Farah, R. (2026) · Cerebral Cortex · doi:10.1093/cercor/bhag167 · Cited by 5
“Creativity, measured in this study as DAT ( Olson et al. 2021), is related to cognitive control, with evidence demonstrating increased creative abilities with increased frontal activation (specifically the Dorsolateral prefrontal cortex) from adolescence to young adulthood ( Jolles et al. 2011).”
Metadata
- Authors
- Jolles, D. D., van Buchem, M. A., Crone, E. A., & Rombouts, S. A. R. B.
- Affiliations
- Leiden University (NL)
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-06-11
- Volume
- 21
- Issue
- 2
- Pages
- 385-391
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2115718505
- Cited by
- 181
- References
- 81
- Citations by year
- 2026: 5 · 2025: 11 · 2024: 13 · 2023: 17 · 2022: 11 · 2021: 6 · 2020: 13 · 2019: 13 · 2018: 6 · 2017: 14 · 2016: 10 · 2015: 11 · 2014: 15 · 2013: 14 · 2012: 12
- FWCI
- 6.96
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cerebral Cortex (publishedVersion)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (91786368, 452-07-011)
- Gratama Stichting
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- whole-brain functional connectivity, brain development, adolescence, children, young adults, default mode network, gray matter density
- MeSH terms
- Adolescent, Adult, Aging, Brain, Brain Mapping, Child, Child Development, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Oxygen, Young Adult
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