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A Comprehensive Study of Whole-Brain Functional Connectivity in Children and Young Adults
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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]
In the citing paper
“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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Cited by
Sorted by citations
Understanding adolescence as a period of social–affective engagement and goal flexibility
Crone, E. A., & Dahl, R. E. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3313 · Cited by 2,507
Self-citationExtraordinary neoteny of synaptic spines in the human prefrontal cortex
Petanjek, Z., Judaš, M., Šimić, G., Rašin, M. R., Uylings, H. B. M., Rakic, P., & Kostović, I. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1105108108 · Cited by 1,411
“Taken together, the previous data and the present findings strongly indicate that anatomical (23, 24, 26–28, 31) and functional changes (15, 18, 19, 21, 22, 25, 35) in the prefrontal cortex observed in vivo during late adolescence and young adulthood reflect the dynamic reorganization of synaptic circuitry rather than…”
ResultImaging brain development: The adolescent brain
Blakemore, S.-J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.080 · Cited by 649
“…networks, such as the default mode network (the network of brain regions that are active during baseline), have been reported during adolescence across several studies employing different analytic approaches (Fair et al., 2008; Jolles et al., 2011; Lopez-Larson et al., 2011; Supekar et al., 2010).”
ResultSalience Network–Based Classification and Prediction of Symptom Severity in Children With Autism
Uddin, L. Q., Supekar, K., Lynch, C. J., Khouzam, A., Phillips, J., Feinstein, C., Ryali, S., & Menon, V. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.104 · Cited by 621
Resting-State Functional MR Imaging: A New Window to the Brain
Barkhof, F., Haller, S., & Rombouts, S. A. R. B. (2014) · Radiology · doi:10.1148/radiol.14132388 · Cited by 397
Brenhouse, H. C., & Andersen, S. L. (2011) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.04.013 · Cited by 363
“67 [SD] years) in mixed sex groups, 13 main functional networks were identified (Jolles et al., 2010).”
BackgroundInfluentialThe Default Mode Network in Healthy Individuals: A Systematic Review and Meta-Analysis
Mak, L. E., Minuzzi, L., MacQUEEN, G. M., Hall, G. B., Kennedy, S. H., & Milev, R. V. (2016) · Brain Connectivity · doi:10.1089/brain.2016.0438 · Cited by 325
“In contrast, other studies suggest similar patterns of functional connectivity and ReHo in adults and children, but strength is greater in children (Jolles et al., 2011; Lopez-Larson et al., 2011) (Supplementary Table S1; Supplementary Data are available online at www.liebertpub.com/brain).”
Sherman, L. E., Rudie, J. D., Pfeifer, J. H., Masten, C. L., McNealy, K., & Dapretto, M. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.08.002 · Cited by 349
Raznahan, A., Lerch, J. P., Lee, N., Greenstein, D. K., Wallace, G. L., Stockman, M., CLASEN, L. S., Shaw, P. W., & Giedd, J. N. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.028 · Cited by 304
“, 2008) stable across childhood and adulthood (Jolles et al., 2011; Supekar et al., 2010; Thomason et al., 2011); and highly invariable in its composition within and between individuals (Damoiseaux et al.”
Emerging Adulthood, a Pre-adult Life-History Stage
Hochberg, Z., & Konner, M. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00918 · Cited by 204
“Jolles and colleagues investigated the association between whole-brain functional connectivity and cognitive and emotional functions in children (11–13 years) and young adults (19–25 years) (34).”
BackgroundFunctional brain connectivity at rest changes after working memory training
Jolles, D. D., van Buchem, M. A., Crone, E. A., & Rombouts, S. A. R. B. (2013) · Human Brain Mapping · doi:10.1002/hbm.21444 · Cited by 183
“…have found reduced functional connectivity between anterior and posterior default network regions in children [Fair et al., 2008; Kelly et al., 2009; Supekar et al., 2010], other studies, including the study presented here, did not report any differences [Jolles et al., 2011; Littow et al., 2010].”
BackgroundResultInfluentialAsymmetric development of dorsal and ventral attention networks in the human brain
Farrant, K., & Uddin, L. Q. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.02.001 · Cited by 189
“A previous independent component analysis (ICA) study examining developmental ive Neuroscience 12 (2015) 165–174 differences in the dorsal attention network found stronger within-network connectivity in the DAN in 11–13 year-old children compared with 19–25 year old adults (Jolles et al., 2011).”
The relationship between MEG and fMRI
Hall, E. L., Robson, S. E., Morris, P. G., & Brookes, M. J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.005 · Cited by 195
“The current use of fcMRI is nowwide-ranging, from clinical studies in Alzheimer's disease (Liu et al., 2013b) and Parkinson's disease (Liu et al., 2013a), to the study of neurodevelopment (Jolles et al., 2011) and the effect of pharmacological agents (Liao et al., 2012).”
Hoekzema, E. A., Carmona, S., Ramos‐Quiroga, J. A., Vanesa Richarte, B., Bosch, R., Soliva, J. C., Rovira, M., Bulbena, A., Tobeña, A., Casas, M., et al. (2013) · Human Brain Mapping · doi:10.1002/hbm.22250 · Cited by 181
“During childhood, resting state networks are still undergoing a maturation process [Dosenbach et al., 2010; Fransson et al., 2011; Jolles et al., 2011; Kelly et al., 2009; Uddin et al., 2010], and at an early stage an equivalent of the DMN cannot yet be identified [Fransson et al.”
BackgroundResting-state network dysconnectivity in ADHD: A system-neuroscience-based meta-analysis
Sütçübaşı, B., Metin, B., Kurban, K., Metin, Z. E., Beşer, B., & Sonuga-Barke, E. J. S. (2020) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2020.1775889 · Cited by 183
“The feasibility of this account is supported by previous literature, which has shown that resting state brain networks continue to mature throughout adolescence (Kelly et al. 2009; Dosenbach et al. 2010; Uddin 2010; Fransson et al. 2011; Jolles et al. 2011).”
ResultLifespan age differences in working memory: A two-component framework
Sander, M. C., Lindenberger, U., & Werkle‐Bergner, M. (2012) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.06.004 · Cited by 171
Pannekoek, J. N., van der Werff, S. J. A., Meens, P. H. F., van den Bulk, B. G., Jolles, D. D., Veer, I. M., van Lang, N. D. J., Rombouts, S. A. R. B., van der Wee, N. J. A., & Vermeiren, R. R. J. M. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12266 · Cited by 150
“A study comparing RSFC between healthy children and young adults found that the size of functional connectivity (number of voxels) and RSFC strength di!ered between the two groups, independent of grey matter di!erences (Jolles et al., 2011).”
BackgroundResting-state networks in awake five- to eight-year old children
de Bie, H. M. A., Boersma, M., Adriaanse, S., Veltman, D. J., Wink, A. M., Roosendaal, S. D., Barkhof, F., Stam, C. J., Oostrom, K. J., Delemarre‐van de Waal, H. A., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.21280 · Cited by 143
“In older children, around 8 years of age, resting-state studies indicate that these networks have a robust functional organization but still show immature characteristics [Fair et al., 2009; Jolles et al., 2010; Supekar et al., 2009].”
BackgroundThe brain matures with stronger functional connectivity and decreased randomness of its network
Smit, D. J. A., Boersma, M., Schnack, H. G., Micheloyannis, S., Boomsma, D. I., Hulshoff Pol, H. E., Stam, C. J., & de Geus, E. J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036896 · Cited by 143
Stevens, M. C. G. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.027 · Cited by 145
van Duijvenvoorde, A. C. K., Achterberg, M., Braams, B. R., Peters, S., & Crone, E. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.069 · Cited by 138
“In addition,we selected two other functional networks that overlapped with previously studies: i) An anterior defaultmode network (J) comprising a largemedial frontal cluster (medial PFC, subcallosal cortex, orbital frontal cortex, and ACC) and limbic regions including the nAcc and caudate nucleus (Jolles et al., 2011…”
BackgroundMethodInfluentialAchterberg, M., van Duijvenvoorde, A. C. K., Bakermans-Kranenburg, M. J., & Crone, E. A. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsv154 · Cited by 125
Changes in Plasticity Across the Lifespan
Oberman, L. M., & Pascual‐Leone, Á. (2013) · Progress in brain research · doi:10.1016/b978-0-444-63327-9.00016-3 · Cited by 134
“During developmental years, children and young adults appear to have similar patterns of functionally connected regions but with differences in the size of functionally connected regions and in the strength of functional connectivity between brain regions (Jolles et al., 2011).”
BackgroundTypical and atypical brain development: a review of neuroimaging studies
Dennis, E. L., & Thompson, P. M. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.3/edennis · Cited by 126
“A study that focused less on the specific regions connected and more on the quality of the connections found that children’s functional networks tended to include more voxels and than did those of adults.(68) This supports earlier hypotheses that maturation is marked by a process of refining and “focusing” of brain ne…”
ResultWang, X., Foryt, P., Ochs, R., Chung, J.-H., Wu, Y. G., Parrish, T. B., & Ragin, A. B. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0016 · Cited by 112
“This approach has been used in a number of recent studies (Jolles et al., 2010; Mohammadi et al., 2011; Werner et al., 2010b).”
On development of functional brain connectivity in the young brain
Hoff, G. E. A.-J., van den Heuvel, M. P., Benders, M. J. N. L., Kersbergen, K. J., & de Vries, L. S. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00650 · Cited by 114
“At 12 years of age, overall FC as well as network size is still decreased in comparison with adults (Jolles et al., 2011).”
BackgroundResultAtypical developmental of dorsal and ventral attention networks in autism
Farrant, K., & Uddin, L. Q. (2015) · Developmental Science · doi:10.1111/desc.12359 · Cited by 101
Thermenos, H. W., Keshavan, M. S., Juelich, R. J., Molokotos, E. K., Whitfield, S., Brent, B., Makris, N., & Seidman, L. J. (2013) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32170 · Cited by 105
“The final maturation of the PFC in late adolescence and young adulthood [Feinberg, 1982; Selemon and Goldman-Rakic, 1999] may be particularly at risk [Weinberger, 1987], with adverse implications for both PFC structure and function (including maturation of activity, connectivity and network topology) [Menon et al., 20…”
BackgroundMental time travel and default-mode network functional connectivity in the developing brain
Østby, Y., Walhovd, K. B., Tamnes, C. K., Grydeland, H., Westlye, L. T., & Fjell, A. M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1210627109 · Cited by 109
“A previous study found negative age-connectivity relationships in development and speculated that this could reflect the higher number of synapses in children (40).”
BackgroundStudholme, C. (2011) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071910-124654 · Cited by 97
“Work on resting-state activations (without stimuli) have shown great promise in mapping the development of the so-called default mode in infants (162) and children (163, 164), and extending this work to show earlier stages of this process is of significant interest.”
BackgroundIntrinsic connectivity networks from childhood to late adolescence: Effects of age and sex
Solé‐Padullés, C., Castro‐Fornieles, J., de la Serna, E., Calvo, R. M., Baeza, I., Moyá, J., Lázaro, L., Rosa, M., Bargalló, N., & Sugranyes, G. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.11.004 · Cited by 94
“I E C , N a b B c d e f a A R R 1 A A K F ( R D I 1 e d r a m h 2 P 0 h 1 Developmental Cognitive Neuroscience 17 (2016) 35–44 Contents lists available at ScienceDirect Developmental Cognitive Neuroscience j o ur nal ho me pa ge: ht tp : / /www.e lsev ier .com/ locate /dcn ntrinsic connectivity networks from childhood…”
BackgroundInfluentialFunctional network integration and attention skills in young children
Rohr, C. S., Arora, A. K., Cho, I. Y. K., Katlariwala, P., Dimond, D., Dewey, D., & Bray, S. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.007 · Cited by 90
Bos, D. J., Oranje, B., Achterberg, M., Vlaskamp, C., Ambrosino, S., de Reus, M. A., van den Heuvel, M. P., Rombouts, S. A. R. B., & Durston, S. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12712 · Cited by 84
“Specifically, Default Mode, frontal-attentional, or executive RSNs have been observed to show more diffuse, mostly increased patterns of connectivity during childhood (Jolles, van Buchem, Crone, & Rombouts, 2011).”
Age-related neuronal loss in the rat brain starts at the end of adolescence
Morterá, P., & Herculano-Houzel, S. (2012) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2012.00045 · Cited by 79
“Adolescence has been increasingly recognized as a period of brain remodeling, with profound changes in the cortical gray and white matter (Giedd and Rapoport, 2010), cortical connectivity (Jolles et al., 2011), and brain function (Baird and Fugelsang, 2004).”
BackgroundSolomon, M., Yoon, J. H., Ragland, J. D., Niendam, T. A., Lesh, T. A., Fairbrother, W., & Carter, C. S. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.08.036 · Cited by 78
Krafft, C. E., Pierce, J. E., Schwarz, N. F., Chi, L., Weinberger, A. L., Schaeffer, D. J., Rodrigue, A., Camchong, J., Allison, J., Yanasak, N. E., et al. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.09.052 · Cited by 77
“The right medial direction, with the exercise group showing increased synchrony with the mot anatomical image is the pediatric template that was used during alignment a references to color in this figure legend, the reader is referred to the web ve that a general pattern of refined synchrony (decreased between-network…”
BackgroundMethodInfluentialMark, C. I., Mazerolle, E. L., & Chen, J. J. (2015) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24786 · Cited by 76
Resting‐state networks in 6‐to‐10 year old children
Muetzel, R. L., Blanken, L. M. E., Thijssen, S., van der Lugt, A., Jaddoe, V. W. V., Verhulst, F. C., Tiemeier, H. W., & White, T. J. H. (2016) · Human Brain Mapping · doi:10.1002/hbm.23309 · Cited by 77
“However, heterogeneity exists in the literature in terms of the selection (subset) of components reported; for instance, one study of children reports the executive control network [Jolles et al., 2011] while another does not [de Bie et al., 2012].”
BackgroundGenes, Evolution and Intelligence
Bouchard, T. J. (2014) · Behavior Genetics · doi:10.1007/s10519-014-9646-x · Cited by 73
“This prediction has proven to be true as Jolles et al. (2011) have recently shown that functional connectivity differences between brain regions cannot be explained by gray matter density alone.”
Rohr, C. S., Vinette, S. A., Parsons, K., Cho, I. Y. K., Dimond, D., Benischek, A., Lebel, C. A., Dewey, D., & Bray, S. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw236 · Cited by 67
The neural coding of feedback learning across child and adolescent development
Peters, S., Braams, B. R., Raijmakers, M. E. J., Koolschijn, P. C. M. P., & Crone, E. A. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00594 · Cited by 65
Gabard-Durnam, L. J., Gee, D. G., Goff, B., Flannery, J., Telzer, E. H., Humphreys, K. L., Lumian, D. S., Fareri, D. S., Caldera, C., & Tottenham, N. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.0598-16.2016 · Cited by 62
“Resting-state networks show dramatic changes in composition across development (Jolles et al., 2011; Uddin et al., 2011; Barber et al., 2013; Solé-Padullés et al., 2016), but little is currently known about the mechanisms through which resting-state connections assemble into stable networks over time.”
BackgroundMapping Small-World Properties through Development in the Human Brain: Disruption in Schizophrenia
Tomasi, D. G., & Volkow, N. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096176 · Cited by 63
Barber, A. D., Srinivasan, P., Joel, S. E., Caffo, B. S., Pekar, J. J., & Mostofsky, S. H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr062 · Cited by 63
“2008) as is the motor control network (Fair et al. 2010; Jolles et al. 2010).”
BackgroundBulgarelli, C., de Klerk, C. C. J. M., Richards, J. E., Southgate, V., Hamilton, A. F. D. C., & Blasi, A. (2020) · Human Brain Mapping · doi:10.1002/hbm.24974 · Cited by 69
Petanjek, Z., Sedmak, D., Džaja, D., Hladnik, A., Rašin, M. R., & Milošević, N. J. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00122 · Cited by 67
Differences between child and adult large‐scale functional brain networks for reading tasks
Liu, X., Gao, Y., Di, Q., Hu, J., Lu, C., Nan, Y., Booth, J. R., & Liu, L. (2017) · Human Brain Mapping · doi:10.1002/hbm.23871 · Cited by 58
“This developmental trend has been reported in previous studies on general cognitive development using task-free resting-state data (Cao et al., 2014; Jolles et al., 2011; Supekar et al., 2009), and hence it may be a domain-general developmental mechanism reflected here in reading tasks.”
MethodResultde Water, E., Proal, E., Wang, V., Martínez-Medina, S., Schnaas, L., Téllez‐Rojo, M. M., Wright, R. O., Tang, C. Y., & Horton, M. K. (2017) · NeuroToxicology · doi:10.1016/j.neuro.2017.06.006 · Cited by 60
Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI
Cai, B., Zillé, P., Stephen, J. M., Wilson, T. W., Calhoun, V. D., & Wang, Y. (2017) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2786553 · Cited by 55
“Finally, hyperconnectivity between the DMN, Aud and EC in children compared with young adults was also observed, which was in agreement with the results of a similar study by Jolles et al. [43].”
BackgroundResultInfluentialDeep Collaborative Learning With Application to the Study of Multimodal Brain Development
Hu, W., Cai, B., Zhang, A., Calhoun, V. D., & Wang, Y. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2904301 · Cited by 53
“An assumption is that adolescence (age 8-22) is an important stage for brain development and brain FC becomes more established around age 12 [22].”
BackgroundCapturing Dynamic Connectivity From Resting State fMRI Using Time-Varying Graphical Lasso
Cai, B., Zhang, G., Zhang, A., Stephen, J. M., Wilson, T. W., Calhoun, V. D., & Wang, Y. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2880428 · Cited by 51
“young adults had hyperconnectivity within the visual system compared with children [3], [4].”
Age-related changes in spatial and temporal features of resting state fMRI
Vij, S. G., Nomi, J. S., Dajani, D. R., & Uddin, L. Q. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2018.02.066 · Cited by 48
“While these studies verify widespread age-related local changes in ICNs and suggest that topological changes can provide insights into neural substrates of individual variability (Jolles et al., 2011), no previous studies have clearly evaluated age-related changes in spatial features such as extent of ICNs across the…”
InfluentialMüller‐Oehring, E. M., Kwon, D., Nagel, B. J., Sullivan, E. V., Chu, W., Torsten Rohlfing, B., Prouty, D., Nichols, B. N., Poline, J., Tapert, S. F., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx014 · Cited by 50
“Complementing recent findings based on adolescence rs-fMRI (Fair et al. 2007, 2008, 2009; Jolles et al. 2011; Avants et al. 2015), the present study used a large sample of adolescents to investigate the effects of age, sex (Alarcon et al.”
BackgroundIntranetwork and internetwork functional connectivity abnormalities in pediatric multiple sclerosis
Rocca, M. A., Valsasina, P., Absinta, M., Moiola, L., Ghezzi, A., Veggiotti, P., Amato, M. P., Horsfield, M. A., Falini, A., Comi, G., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22469 · Cited by 50
“Indeed, it has been recently shown that, by the age of 10–12 years, only small spatial differences from adult patterns are present in all RSNs with functional relevance [Jolles et al., 2011; Supekar et al., 2010].”
BackgroundWortinger, L. A., Endestad, T., Melinder, A. M. D., Øie, M. G., Nilsen, A. S., & Wyller, V. B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159351 · Cited by 48
“During adolescence, changes in the functional connectivity of brain networks are ongoing [64], and in particularly, alterations in adolescent DMN [65, 66].”
BackgroundPetrican, R., Taylor, M. J., & Grady, C. L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.025 · Cited by 43
“All rights reserved. et al., 2015; van Duijvenvoorde et al., 2016; for exceptions, see Betzel et al., 2014; Jolles et al., 2011; Wang et al., 2012).”
Lüchinger, R., Michels, L., Martin, E., & Brandeis, D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.031 · Cited by 49
“After this age, maturational changes were described as more subtle fine tuning of within- and betweennetwork connectivity (Dosenbach et al., 2010; Fair et al., 2007, 2009; Jolles et al., 2011; Supekar et al., 2009).”
BackgroundDevelopmental differences in higher-order resting-state networks in Autism Spectrum Disorder
Bos, D. J., van Raalten, T. R., Oranje, B., Smits, A. R., Kobussen, N. A., Belle, J. V., Rombouts, S. A. R. B., & Durston, S. (2014) · NeuroImage: Clinical · doi:10.1016/j.nicl.2014.05.007 · Cited by 45
Self-citationPiras, F., Schiff, M., Chiapponi, C., Bossù, P., Mühlenhoff, M., Caltagirone, C., Gerardy‐Schahn, R., Hildebrandt, H., & Spalletta, G. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.156 · Cited by 45
Exploring resting-state functional connectivity with total interdependence
Wen, X., Mo, J., & Ding, M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.079 · Cited by 46
“, 2006), correlate with behavior during development and aging (Beason-Held et al., 2009; Church et al., 2009; Jolles et al., 2011; Kelly et al., 2009), and predict brain pathology (He et al.”
BackgroundHamza, E. A., Tindle, R., Pawlak, S., Bedewy, D., & Moustafa, A. A. (2024) · Reviews in the Neurosciences · doi:10.1515/revneuro-2023-0163 · Cited by 50
“…connectivity be-tween regions of the brain, which can be concisely de fi ned as synchronicity and communication between these brain regions (Jolles et al. 2011), which is also associated with impaired psychosocial functioning (i.e., adaptive coping and stress management) (Evans et al.…”
BackgroundLifespan Differences in Cortico-Striatal Resting State Connectivity
Bo, J., Lee, C.-M., Kwak, Y., Peltier, S., Bernard, J. A., Buschkuehl, M., Jaeggi, S. M., Wiggins, J. L., Jonides, J. J., Monk, C. S., et al. (2014) · Brain Connectivity · doi:10.1089/brain.2013.0155 · Cited by 40
“It appears that the cognitive networks exhibit more extensive developmental changes in children (de Bie et al., 2012; Jolles et al., 2011), and more declines in aging (Ystad et al.”
BackgroundResultInfluentialDiFrancesco, M. W., Gitelman, D. R., Klein‐Gitelman, M. S., Sagcal‐Gironella, A. C. P., Zelko, F. A. J., Beebe, D. W., Parrish, T. B., Hummel, J., Ying, J., & Brunner, H. I. (2013) · Arthritis Research & Therapy · doi:10.1186/ar4197 · Cited by 38
“In addition, a collection of regions that commonly deactivate during task performance, known as the default mode network, were identified using previous reports [20].”
ResultHow does the body representation system develop in the human brain?
Fontan, A., Cignetti, F., Nazarian, B., Anton, J., Vaugoyeau, M., & Assaiante, C. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.02.010 · Cited by 39
White, T. J. H., Muetzel, R. L., Schmidt, M., Langeslag, S. J. E., Jaddoe, V. W. V., Albert Hofman, D., Calhoun, V. D., Verhulst, F. C., & Tiemeier, H. W. (2014) · Brain Connectivity · doi:10.1089/brain.2013.0195 · Cited by 38
“, 2009; van den Heuvel and Hulshoff Pol, 2010), and auditory (Allen et al., 2011; Beckmann et al., 2005; Damoiseaux et al., 2006; de Bie et al., 2012; De Luca et al., 2006; Jolles et al., 2011; Mantini et al., 2007; Smith et al., 2009) networks.”
BackgroundInfluentialRelationship between functional connectivity and sensory impairment: Red flag or red herring?
Dinomais, M., Groeschel, S., Staudt, M., Krägeloh‐Mann, I., & Wilke, M. (2011) · Human Brain Mapping · doi:10.1002/hbm.21227 · Cited by 36
Zillé, P., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2017) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2721640 · Cited by 32
Refined measure of functional connectomes for improved identifiability and prediction
Cai, B., Zhang, G., Hu, W., Zhang, A., Zillé, P., Zhang, Y., Stephen, J. M., Wilson, T. W., Calhoun, V. D., & Wang, Y. (2019) · Human Brain Mapping · doi:10.1002/hbm.24741 · Cited by 30
“Previous studies have suggested that the visual system was highly associated with group factors (Cai, Zhang, et al., 2018; Cai, Zille, et al., 2018; Jolles, van Buchem, Crone, & Rombouts, 2010; Zille, Calhoun, Stephen, Wilson, & Wang, 2017).”
BackgroundProtracted Development of the Proprioceptive Brain Network During and Beyond Adolescence
Cignetti, F., Fontan, A., Menant, J. C., Nazarian, B., Anton, J., Vaugoyeau, M., & Assaiante, C. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhv323 · Cited by 35
“A main finding was the transition from diffuse to more focal FC patterns during adolescence, which echoes previous results on the development of intrinsic FC networks (Kelly et al. 2009; Jolles et al. 2011) and structural (graymatter) covariance networks (Zielinski et al. 2010).”
BackgroundResultInfluentialLow-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol
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) · Scientific Reports · doi:10.1038/s41598-020-78885-z · Cited by 31
“Our aim in this paper is three-fold: (1) build on the tradition of using mock scans and show that such an approach can be used with in-scan methods to achieve low-motion data in pediatric participants (age range: 7–17 years old) undergoing a 60 min MRI protocol; (2) compare results to a group who did not receive a moc…”
Resultde Water, E., Papazaharias, D. M., Ambrosi, C., Mascaro, L., Iannilli, E., Gasparotti, R., Lucchini, R. G., Austin, C. E., Arora, M., Tang, C. Y., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0220790 · Cited by 30
Egimendia, A., Minassian, A., Diedenhofen, M., Wiedermann, D., Ramos‐Cabrer, P., & Hoehn, M. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00277 · Cited by 28
zhong, J., Nantes, J. C., Holmes, S. A., Gallant, S., Narayanan, S., & Koski, L. M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23307 · Cited by 27
Jiang, P., Vuontela, V., Tokariev, M., Lin, H., Aronen, E. T., Ma, Y., & Carlson, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205690 · Cited by 30
“Overall, the results of the resting state ICA are in line with earlier literature [38,43,84] suggesting that the general architecture of ICNs is already established in young school aged children.”
ResultThe Role of Gender and Age in the Emotional Well-Being Outcomes of Young Adults
López-Madrigal, C., de la Fuente, J., García‐Manglano, J., Vicente, J. M. M., Sánchez, F. J. P., & Romera, J. A. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18020522 · Cited by 33
“Changes in neurocognitive skills are influenced by social and psychological experiences; functional connections of the brain are essential for the development of psychological functions [14].”
BackgroundSon, J. J., Schantell, M. D., Picci, G., Wang, Y., Stephen, J. M., Calhoun, V. D., Doucet, G. E., Taylor, B. K., & Wilson, T. W. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101216 · Cited by 29
Relative stability of neurocognitive deficits in early onset schizophrenia spectrum patients
Juuhl‐Langseth, M., Holmén, A., Thormodsen, R., Øie, M. G., & Rund, B. R. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.04.014 · Cited by 26
Ghetti, S., & Lee, J. K. (2013) · Wiley eBooks · doi:10.1002/9781118597705.ch14 · Cited by 26
Jolles, D., Mennigen, E., Gupta, M. W., Hegarty, C. E., Bearden, C. E., & Karlsgodt, K. H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117202 · Cited by 24
“…findings, low model-order ICA usually identifies left and right lateralized FP networks as separate components, whereas other networks are commonly represented in bilateral components (e.g., Beckmann et al., 2005 ; Damoiseaux et al., 2006 ; Jolles et al., 2011 ; van Duijvenvoorde et al., 2016 ).”
Fu, Z., Batta, I., Wu, L., Abrol, A., Agcaoglu, O., Salman, M. S., Du, Y., Iraji, A., Shultz, S., Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., et al. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120617 · Cited by 26
“Functional network differences between children and adults have also been reported in many studies (Jolles et al., 2011; Liu et al., 2018; Sato et al., 2021).”
Vinette, S. A., & Bray, S. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.04.004 · Cited by 26
“…dorsal attention network; FPN, fronto-parietal network; DMN, m spectrum disorders; TR, repetition time; TE, echo time; FOV, field of view; MNI, r; FG, fusiform gyrus; Calc, peri-calcarine cortex; OT, occipto-temporal; MO, mid rietal lobule; PCUN, precuneus; Mid Temp, middle temporal; CN, caudate…”
BackgroundOrigin, synchronization, and propagation of sleep slow waves in children
Castelnovo, A., Lividini, A., Riedner, B. A., Avvenuti, G., Jones, S. G., Miano, S., Tononi, G., Manconi, M., & Bernardi, G. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120133 · Cited by 23
Discovery of genes that affect human brain connectivity: A genome-wide analysis of the connectome
Jahanshad, N., Hibar, D. P., Ryles, A. B., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., Hansell, N. K., Montgomery, G. W., Martin, N. G., Wright, M. J., et al. (2012) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2012.6235605 · Cited by 22
“Index Terms— genetics, high angular resolution diffusion imaging (HARDI), cortical surfaces, twin modeling, human connectome”
BackgroundRamage, A. E., Lin, A., Olvera, R. L., Fox, P. T., & Williamson, D. E. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2015.01.012 · Cited by 21
“, 2011), and atrophy in middle-aged, long term abstinent alcoholic men (Fein et al., 2006; Jolles et al., 2011).”
BackgroundInfluentialNeural connectivity patterns explain why adolescents perceive the world as moving slow
Ghorbani, F., Zhou, X., Talebi, N., Roessner, V., Hommel, B., Prochnow, A., & Beste, C. (2024) · Communications Biology · doi:10.1038/s42003-024-06439-4 · Cited by 20
Reducing the Effects of Motion Artifacts in fMRI: A Structured Matrix Completion Approach
Balachandrasekaran, A., Cohen, A. L., Afacan, O., Warfield, S. K., & Gholipour, A. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3107829 · Cited by 20
Wortinger, L. A., Øie, M. G., Endestad, T., & Wyller, V. B. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184325 · Cited by 21
Fu, C., Aisikaer, A., Chen, Z., Yu, Q. B., Yin, J., & Yang, W. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.668856 · Cited by 19
Alterations 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
Burkhouse, K. L., Stange, J. P., Jacobs, R. H., Bhaumik, R., Bessette, K. L., Peters, A. T., Crane, N. A., Kreutzer, K. A., Fitzgerald, K. D., Monk, C. S., et al. (2018) · Depression and Anxiety · doi:10.1002/da.22864 · Cited by 18
“These findings replicate previous studies (Barber et al., 2013; Fair et al., 2008; Jolles et al., 2010; Power et al., 2010; Rubia, 2013; Solé-Padullés et al., 2016) by demonstrating potential maturation of the DMN and CCN at rest throughout development among a larger and broader sample of individuals with no prior his…”
ResultGotlieb, R. J. M., Yang, X., & Immordino‐Yang, M. H. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab108 · Cited by 20
“Two networks we hypothesized would be involved in forming abstract construals, as compared to concrete construals, are the default mode network (DMN) and executive control network (ECN), both of which undergo extensive development across adolescence (Fair et al., 2009; Zielinski et al., 2010; Jolles et al., 2011; Razn…”
BackgroundMeijer, A., Königs, M., Pouwels, P. J. W., Smith, J., Visscher, C., Bosker, R., Hartman, E., & Oosterlaan, J. (2022) · Psychophysiology · doi:10.1111/psyp.14034 · Cited by 20
“…state networks (RSNs) is characterized as a powerful model of brain function with proven sensitivity to developmental changes (Fan et al., 2021; Jolles et al., 2010; Stevens et al., 2009) and is related to neurocognitive functioning in children (Cabral et al., 2017; Gutierrez- Colina et al.,…”
BackgroundMandino, 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. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02779-z · Cited by 19
A GICA-TVGL Framework to Study Sex Differences in Resting State fMRI Dynamic Connectivity
Cai, B., Zhang, G.-M., Zhang, A.-Y., Hu, W.-X., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108531 · Cited by 14
Vuontela, V., Jiang, P., Tokariev, M., Savolainen, P., Ma, Y., Aronen, E. T., Fontell, T., Liiri, T., Ahlström, M., Salonen, O. L. M., et al. (2012) · Brain and Cognition · doi:10.1016/j.bandc.2012.11.003 · Cited by 18
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
Zhou, Y., Song, Y., Chen, C., Shu, Y., Chen, M., & Liu, T. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1146944 · Cited by 16
“, 2022b), attention deficit hyperactivity disorder, abnormal brain development (Jolles et al., 2011), migraine (Wang et al.”
BackgroundOtto, A., Jarvers, I., Kandsperger, S., Reichl, C., Ando, A., Koenig, J., Kaess, M., & Brunner, R. M. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.07.032 · Cited by 20
“Children ages 12 years and older display functional connectivity patterns similar to those of young adults (Jolles et al., 2011), therefore ROIs were selected from CONN ’ s standardized implemented HCP-ICA (1200 participants) and FSL Harvard-Oxford atlas of cortical and subcortical areas.”
Qiao, C., Hu, X., Xiao, L., Calhoun, V. D., & Wang, Y. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.05.003 · Cited by 16
Kennedy, M. F., Mohamed, A. Z., Schwenn, P., Beaudequin, D. A., Shan, Z., Hermens, D. F., & Lagopoulos, J. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00673-2 · Cited by 22
“These developmental differences suggest functional networks may be less specialized or efficient during childhood, thus may underlie atypical cognitive development and deficits in emotion regulation, commonly associated with anxiety and attention impairments (Jolles et al., 2011; Supekar et al., 2009).”
Background
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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