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Functional connectivity in the developing brain: A longitudinal study from 4 to 9months of age
Open accessAbstract
We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age.
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“Over the course of the first two years of life, these regions undergo a precise evolution to gradually bring the network ‘online’ (Damaraju et al., 2014; Gao et al., 2013; Gao et al., 2009).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Damaraju et al., 2014
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“In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al., 2014; Fransson et al., 2007; Gao et al., 2009; Smyser et al., 2010; Wylie et al., 2014).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Damaraju et al., 2014
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BackgroundResultInfluentialConsistent resting-state networks across healthy subjects
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Dosenbach, N. U. F., Nardos, B., Cohen, A. L., Fair, D. A., Power, J. D., Church, J. A., Nelson, S. M., Wig, G. S., Vogel, A. C., Lessov-Schlaggar, C. N., et al. (2010) · Science · doi:10.1126/science.1194144 · Cited by 2,183 · cited 2×
“…work identifying ICNs in infants (Fransson et al., 2007) and numerous subsequent studies of resting state connectivity have provided greater understanding of the functional architecture of the human brain during early development (Doria et al., 2010; Dosenbach et al., 2010; Gao et al., 2009).”
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Time–frequency dynamics of resting-state brain connectivity measured with fMRI
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BackgroundIntrinsic functional architecture in the anaesthetized monkey brain
Vincent, J. L., Patel, G. H., Fox, M. D., Snyder, A. Z., Baker, J. T., Van Essen, D. C., Zempel, J. M., Snyder, L. H., Corbetta, M., & Raichle, M. E. (2007) · Nature · doi:10.1038/nature05758 · Cited by 1,786 · cited 2×
“Furthermore ICNs are shown to be present under the conditions of mild anesthesia (Greicius et al., 2008; Vincent et al., 2007) as well as sleep (Larson-Prior et al.”
BackgroundDistinct patterns of brain activity in young carriers of the APOE -ε4 allele
Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811879106 · Cited by 1,613 · cited 3×
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BackgroundMethodFunctional brain networks develop from a local to distributed organization
Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000381 · Cited by 1,530 · cited 1×
“It has been suggested that functional brain networks develop in a local to distributed fashion (Fair et al., 2009), and indeed the increased coherencewe found between The quality index (Iq) associated with each ICN is listed in parentheses adjacent to the component number.”
BackgroundDefault Mode Network Activity and Connectivity in Psychopathology
Whitfield-Gabrieli, S., & Ford, J. M. (2012) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032511-143049 · Cited by 1,465 · cited 1×
“…2000) and is related to a child's early social development and attachment, as is commonly noted when a typically developing 6 to 9 month old child screams when a stranger walks into the room, or when mother walks out of sight (Hay et al., 2012), for review see Whitfield-Gabrieli and Ford (2012).”
BackgroundPermutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses
Niknian, M., & Good, P. (1995) · Technometrics · doi:10.2307/1269919 · Cited by 1,463
Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461 · cited 3×
“…measures have recommended using a subject motion summary measure such as mean framewise displacement (meanFD) as a subject level nuisance covariate during group-level statistical comparisons to mitigate motion effects on connectivity measures (Satterthwaite et al., 2012; Yan et al., 2013).”
BackgroundMethodInfluentialExtraordinary 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 · cited 2×
“Such imaging studies are consistent with previous post-mortem investigations identifying cellular processes in early childhood such as dendritic maturation, fluctuating synaptic density, and myelination that vary depending on brain region and age (Glantz et al., 2007; Huttenlocher and Dabholkar, 1997; Petanjek et al.,…”
BackgroundResultCastelli, F. (2002) · Brain · doi:10.1093/brain/awf189 · Cited by 1,377 · cited 2×
“…changes in cortical thickness and volume that vary throughout the brain (Giedd and Rapoport, 2010) and may be sensitive to disorders such as prematurity (Phillips et al., 2011), autism (Castelli et al., 2002; McAlonan et al., 2005) or other developmental disabilities (Seidman et al., 2005).”
BackgroundA Baseline for the Multivariate Comparison of Resting-State Networks
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W. E., Segall, J. M., Silva, R. F., Havlíček, M., Rachakonda, S., Fries, J. F., Kalyanam, R., et al. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00002 · Cited by 1,329 · cited 1×
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Self-citationValidating the independent components of neuroimaging time series via clustering and visualization
Himberg, J., Hyvärinen, A., & Esposito, F. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.027 · Cited by 1,246 · cited 1×
“The stability of the ICA decomposition was estimated by calculating a cluster quality index for each component cluster, which ranges between 0 and 1 (Himberg et al., 2004).”
MethodA Structural MRI Study of Human Brain Development from Birth to 2 Years
Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., Hamer, R. M., Lin, W., Gerig, G., & Gilmore, J. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.3479-08.2008 · Cited by 1,151 · cited 1×
“The majority of previous work characterizes children over 3 years of age (for review see Giedd and Rapoport, 2010), although recent reports include children in the first several years of life — when a dramatic increase in volume occurs (Gilmore et al., 2011; Knickmeyer et al., 2008).”
BackgroundJafri, M. J., Pearlson, G. D., Stevens, M. C. G., & Calhoun, V. D. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.11.001 · Cited by 996 · cited 1×
“Time courses of retained ICNs were used to compute 1) power spectra and2) functional network connectivity (FNC), defined as the pairwise correlation between ICA time courses (Jafri et al., 2008).”
MethodSelf-citationEstimating the number of independent components for functional magnetic resonance imaging data
Li, Y., Adalı, T., & Calhoun, V. D. (2007) · Human Brain Mapping · doi:10.1002/hbm.20359 · Cited by 923 · cited 2×
“Here, we follow their recommendation and use a model order of 30, the average Minimum Description Length (MDL) for single subject datasets (Li et al., 2007), and a high model order of 100, the upper limit recommendedbyAbou-Elseoud et al. (2010) beyond which network stability was found to decrease.”
MethodSelf-citationMapping functionally related regions of brain with functional connectivity MR imaging.
Cordes, D., Haughton, V. M., Arfanakis, K., Wendt, G. J., Turski, P. A., Moritz, C. H., Quigley, M., & Meyerand, M. E. (2000) · PubMed Central · Cited by 908
Structural MRI of pediatric brain development: what have we learned and where are we going?
Giedd, J. N., & Rapoport, J. L. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.040 · Cited by 836 · cited 3×
“Recent high-resolution MRI studies identify age-dependent changes in cortical thickness and volume that vary throughout the brain (Giedd and Rapoport, 2010) and may be sensitive to disorders such as prematurity (Phillips et al., 2011), autism (Castelli et al., 2002; McAlonan et al., 2005) or other…”
BackgroundMitra, P. P., & Bokil, H. (2007) · doi:10.1093/acprof:oso/9780195178081.001.0001 · Cited by 827
Longitudinal Analysis of Neural Network Development in Preterm Infants
Smyser, C. D., Inder, T. E., Shimony, J. S., Hill, J. E., Degnan, A. J., Snyder, A. Z., & Neil, J. J. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhq035 · Cited by 791 · cited 1×
“Smyser et al. (2010) used seed-based correlational analysis in neonates beginning at 26 week gestation, identifying neural networks which increase in distance and coherence through gestation.”
MethodSynaptogenesis in human visual cortex—evidence for synapse elimination during normal development
Huttenlocher, P. R., de Courten, C., Garey, L. J., & Van der Loos, H. (1982) · Neuroscience Letters · doi:10.1016/0304-3940(82)90379-2 · Cited by 745 · cited 2×
“…becomes more efficient and thus requires fewer neuronal circuits, which is consistentwith post-mortem studies at this age demonstrating synaptic pruning and cortical thinning as part of normal development (Huttenlocher and Dabholkar, 1997; Huttenlocher et al., 1982; Shankle et al., 1999).”
BackgroundComparison of multi‐subject ICA methods for analysis of fMRI data
Erhardt, E. B., Rachakonda, S., Bedrick, E. J., Allen, E. A., Adalı, T., & Calhoun, V. D. (2010) · Human Brain Mapping · doi:10.1002/hbm.21170 · Cited by 733 · cited 3×
“Subject-specific ICA spatial maps and corresponding time courses were computed by back-reconstruction using spatio-temporal or dual regression (Erhardt et al., 2011).”
BackgroundMethodSelf-citationUnderstanding Other Minds: Linking Developmental Psychology and Functional Neuroimaging
Saxe, R., Carey, S., & Kanwisher, N. (2004) · Annual Review of Psychology · doi:10.1146/annurev.psych.55.090902.142044 · Cited by 726 · cited 2×
“Components of the default mode network putatively support self reflection (Whitfield-Gabrieli et al., 2011) and social cognition (Saxe et al., 2004), with the posterior cingulate cortex particularly important for emotional processing of faces (Ramasubbu et al., 2007).”
BackgroundResting-state networks in the infant brain
Fransson, P., Skiöld, B., Horsch, S., Nordell, A., Blennow, M., Lagercrantz, H., & Åden, U. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704380104 · Cited by 696 · cited 3×
“Fransson et al. published the initial work identifying ICNs in infants (Fransson et al., 2007) and numerous subsequent studies of resting state connectivity have provided greater understanding of the functional architecture of the human brain during early development (Doria et al., 2010; Dosenbach…”
BackgroundMethodInfluentialStructural Brain Imaging of Attention-Deficit/Hyperactivity Disorder
Seidman, L. J., Valera, E. M., & Makris, N. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.11.019 · Cited by 676 · cited 2×
“…changes in cortical thickness and volume that vary throughout the brain (Giedd and Rapoport, 2010) and may be sensitive to disorders such as prematurity (Phillips et al., 2011), autism (Castelli et al., 2002; McAlonan et al., 2005) or other developmental disabilities (Seidman et al., 2005).”
BackgroundSakoğlu, Ü., Pearlson, G. D., Kiehl, K. A., Wang, Y. M., Michael, A. M., & Calhoun, V. D. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0197-8 · Cited by 623 · cited 1×
“Recent studies have demonstrated non-stationarity in fMRI time courses (Chang and Glover, 2010; Jones et al., 2012; Sakoglu et al., 2010); therefore future work should consider probing the changes in the dynamics of ICNs (Allen et al., 2012; Cribben et al., 2012).”
BackgroundSelf-citationGao, W., Zhu, H., Giovanello, K. S., Smith, J. K., Shen, D., Gilmore, J. H., & Lin, W. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811221106 · Cited by 601 · cited 4×
“Using ICA to identify regions associatedwith the adult defaultmode network, therewas evidence for a rudimentary default mode network consisting of 6 regions in the infants that expanded to 13 regions at 1 year of age and 19 regions at 2 years (Gao et al., 2009).”
BackgroundMethodInfluentialEmergence of resting state networks in the preterm human brain
Doria, V., Beckmann, C. F., Arichi, T., Merchant, N., Groppo, M., Turkheimer, F. E., Counsell, S. J., Murgasova, M., Aljabar, P., Nunes, R. G., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1007921107 · Cited by 574 · cited 6×
“Consistentwith a prior report (Doria et al., 2010), it is possible that these primary sensory networks are present from birth.”
BackgroundMethodResultInfluentialCalhoun, V. D., Kiehl, K. A., & Pearlson, G. D. (2008) · Human Brain Mapping · doi:10.1002/hbm.20581 · Cited by 567 · cited 1×
“Intrinsic connectivity networks (ICNs) observed during resting state fMRI (rsfMRI) have shown close correspondence to networks observed across several tasks (Calhoun et al., 2008; Filippini et al., 2009) thereby providing an objective way to probe network organization without task confounds.”
BackgroundSelf-citationPersistent default‐mode network connectivity during light sedation
Greicius, M. D., Kiviniemi, V. J., Tervonen, O. A., Vainionpää, V., Alahuhta, S., Reiss, A. L., & Menon, V. (2008) · Human Brain Mapping · doi:10.1002/hbm.20537 · Cited by 514 · cited 2×
“Furthermore ICNs are shown to be present under the conditions of mild anesthesia (Greicius et al., 2008; Vincent et al., 2007) as well as sleep (Larson-Prior et al.”
BackgroundMcAlonan, G. M. (2004) · Brain · doi:10.1093/brain/awh332 · Cited by 491 · cited 2×
“…changes in cortical thickness and volume that vary throughout the brain (Giedd and Rapoport, 2010) and may be sensitive to disorders such as prematurity (Phillips et al., 2011), autism (Castelli et al., 2002; McAlonan et al., 2005) or other developmental disabilities (Seidman et al., 2005).”
BackgroundAberrant Striatal Functional Connectivity in Children with Autism
Di Martino, A., Kelly, C., Grzadzinski, R., Zuo, X.-N., Mennes, M., Mairena, M. A., Lord, C., Castellanos, F. X., & Milham, M. P. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.10.029 · Cited by 483 · cited 1×
“This approach has been used to better characterize clinical disorders of abnormal brain network development such as schizophrenia (Filippini et al., 2009), autism (Di Martino et al., 2011; Jones et al., 2010) and attention deficit hyperactivity disorder (Mennes et al., 2011).”
MethodLongitudinal Development of Cortical and Subcortical Gray Matter from Birth to 2 Years
Gilmore, J. H., Shi, F., Woolson, S. L., Knickmeyer, R. C., Short, S. J., Lin, W., Zhu, H., Hamer, R. M., Styner, M., & Shen, D. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr327 · Cited by 456
Cortical network functional connectivity in the descent to sleep
Larson-Prior, L. J., Zempel, J. M., Nolan, T. S., Prior, F. W., Snyder, A. Z., & Raichle, M. E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900924106 · Cited by 450 · cited 2×
“, 2007) as well as sleep (Larson-Prior et al., 2009).”
BackgroundNon-Stationarity in the “Resting Brain’s” Modular Architecture
Jones, D. T., Vemuri, P., Murphy, M. C., Gunter, J. L., Senjem, M. L., Machulda, M. M., Przybelski, S. A., Gregg, B. E., Kantarci, K., Knopman, D. S., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039731 · Cited by 435 · cited 1×
“Recent studies have demonstrated non-stationarity in fMRI time courses (Chang and Glover, 2010; Jones et al., 2012; Sakoglu et al., 2010); therefore future work should consider probing the changes in the dynamics of ICNs (Allen et al., 2012; Cribben et al., 2012).”
BackgroundAssociations and dissociations between default and self-reference networks in the human brain
Whitfield-Gabrieli, S., Moran, J. M., Nieto-Castañón, A., Triantafyllou, C., Saxe, R., & Gabrieli, J. D. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.048 · Cited by 394 · cited 2×
“Components of the default mode network putatively support self reflection (Whitfield-Gabrieli et al., 2011) and social cognition (Saxe et al.”
BackgroundFunctional segmentation of the brain cortex using high model order group PICA
Kiviniemi, V. J., Starck, T., Remes, J. J., Long, X., Nikkinen, J., Haapea, M., Veijola, J. M., Moilanen, I. K., Isohanni, M. K., Zang, Y., et al. (2009) · Human Brain Mapping · doi:10.1002/hbm.20813 · Cited by 376 · cited 6×
“This approach has been used to study ICNs in adults (Kiviniemi et al., 2009) but it has not previously been applied to children.”
BackgroundMethodResultInfluentialThe effect of model order selection in group PICA
Abou‐Elseoud, A., Starck, T., Remes, J. J., Nikkinen, J., Tervonen, O. A., & Kiviniemi, V. J. (2010) · Human Brain Mapping · doi:10.1002/hbm.20929 · Cited by 366 · cited 3×
“A clear advantage of the higher order ICA decomposition was that it divided relatively large spatial networks into smaller sub-networks such that we could study the functional connectivity between them (Abou-Elseoud et al., 2010).”
BackgroundMethodDynamic connectivity regression: Determining state-related changes in brain connectivity
Cribben, I., Haraldsdottir, R., Atlas, L. Y., Wager, T. D., & Lindquist, M. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.070 · Cited by 289 · cited 1×
“Recent studies have demonstrated non-stationarity in fMRI time courses (Chang and Glover, 2010; Jones et al., 2012; Sakoglu et al., 2010); therefore future work should consider probing the changes in the dynamics of ICNs (Allen et al., 2012; Cribben et al., 2012).”
BackgroundGlantz, L. A., Gilmore, J. H., Hamer, R. M., Lieberman, J. A., & Jarskog, L. F. (2007) · Neuroscience · doi:10.1016/j.neuroscience.2007.06.036 · Cited by 270 · cited 1×
“…post-mortem investigations identifying cellular processes in early childhood such as dendritic maturation, fluctuating synaptic density, and myelination that vary depending on brain region and age (Glantz et al., 2007; Huttenlocher and Dabholkar, 1997; Petanjek et al., 2011; Webster et al., 2011).”
BackgroundSmyser, C. D., Snyder, A. Z., & Neil, J. J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.073 · Cited by 259 · cited 1×
“The technology needed for optimal data acquisition and processing methods for infant studies, and the factors involved in the interpretation of cerebral development in infants on the basis of intrinsic networks obtained from fcMRI, has been recently reviewed (Smyser et al., 2011).”
BackgroundFunctional connectivity MR imaging reveals cortical functional connectivity in the developing brain
Lin, W., Zhu, Q., Gao, W., Chen, Y., Toh, C.-H., Styner, M., Gerig, G., Smith, J. K., Biswal, B., & Gilmore, J. H. (2008) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1256 · Cited by 222 · cited 1×
“Using children from this same cross sectional dataset, Lin et al. (2008) showed that the sensorimotor cortex had functional connectivity with larger areas of the brain than the visual cortex did at 1 year of age, but by 2 years both areas were similar.”
Spectral characteristics of resting state networks
Niazy, R. K., Xie, J., Miller, K., Beckmann, C. F., & Smith, S. M. (2011) · Progress in brain research · doi:10.1016/b978-0-444-53839-0.00017-x · Cited by 175 · cited 1×
“A slightly higher upper frequency cut off of 0.15 Hzwas chosen instead of typical 0.08 or 0.1 Hz for the bandpassfiltering as some recent studies have demonstrated the broadband nature of neuronal signals underlying BOLD time courses (Niazy et al., 2011).”
BackgroundInfluentialJones, T. B., Bandettini, P. A., Kenworthy, L., Case, L. K., Milleville, S. C., Martin, A., & Birn, R. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.07.051 · Cited by 172 · cited 2×
“This approach has been used to better characterize clinical disorders of abnormal brain network development such as schizophrenia (Filippini et al., 2009), autism (Di Martino et al., 2011; Jones et al., 2010) and attention deficit hyperactivity disorder (Mennes et al., 2011).”
BackgroundMethodInfant brain probability templates for MRI segmentation and normalization
Altaye, M., Holland, S. K., Wilke, M., & Christian Gaser, B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.060 · Cited by 145 · cited 3×
“The common template was the 9 month template in the MNI stereotaxic standard space as provided by Cincinnati children's research hospital (Altaye et al., 2008).”
MethodInfluentialGroup-ICA Model Order Highlights Patterns of Functional Brain Connectivity
Elseoud, A. A., Littow, H., Remes, J. J., Starck, T., Nikkinen, J., Nissilä, J., Timonen, M., Tervonen, O. A., & Kiviniemi, V. J. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00037 · Cited by 142 · cited 1×
“Additionally as more common group variance is captured at highmodel order ICA, the ICA algorithmwill be able to separate cleaner sources thereby increasing the ability to detect differences between groups (Abou-Elseoud et al., 2011).”
BackgroundTouchpoints: Your Child's Emotional and Behavioral Development
Brazelton, T. B. (1992) · Medical Entomology and Zoology · Cited by 135
P4‐158: Nonstationarity in the ‘resting brain's’ modular architecture
Jones, D. T., Vemuri, P., Murphy, M. C., Gunter, J. L., Senjem, M. L., Machulda, M. M., Przybelski, S. A., Gregg, B. E., Kantarci, K., Knopman, D. S., et al. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2012.05.1862 · Cited by 116
Resting-state functional connectivity differences in premature children
Damaraju, E. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00023 · Cited by 112
Self-citationFunctional connectivity of the sensorimotor area in naturally sleeping infants
Liu, W.-C., Flax, J. F., Guise, K. G., Sukul, V., & Benasich, A. A. (2008) · Brain Research · doi:10.1016/j.brainres.2008.05.054 · Cited by 110 · cited 2×
“…based analysis of children at 12 months of age, Liu evaluated functional connectivity with the sensorimotor cortex and found greater intrahemispheric than interhemispheric connectivity, suggesting that cross-callosal connectivity develops later than within-hemisphere networks (Liu et al., 2008).”
BackgroundMennes, M., Potler, N. V., Kelly, C. A. M., Martino, A. D., Castellanos, F. X., & Milham, M. P. (2012) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2011.00083 · Cited by 66 · cited 2×
“This approach has been used to better characterize clinical disorders of abnormal brain network development such as schizophrenia (Filippini et al., 2009), autism (Di Martino et al., 2011; Jones et al., 2010) and attention deficit hyperactivity disorder (Mennes et al., 2011).”
BackgroundMethodShankle, W. R., Rafii, M. S., Landing, B. H., & Fallon, J. H. (1999) · Pediatric and Developmental Pathology · doi:10.1007/s100249900120 · Cited by 58 · cited 1×
“…becomes more efficient and thus requires fewer neuronal circuits, which is consistentwith post-mortem studies at this age demonstrating synaptic pruning and cortical thinning as part of normal development (Huttenlocher and Dabholkar, 1997; Huttenlocher et al., 1982; Shankle et al., 1999).”
BackgroundWebster, M. J., Elashoff, M. R., & Weickert, C. S. (2010) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2010.09.006 · Cited by 49 · cited 2×
“Such imaging studies are consistent with previous post-mortem investigations identifying cellular processes in early childhood such as dendritic maturation, fluctuating synaptic density, and myelination that vary depending on brain region and age (Glantz et al., 2007; Huttenlocher and Dabholkar, 1997; Petanjek et al.,…”
BackgroundResultAltered resting-state activity in seasonal affective disorder
Elseoud, A. A., Nissilä, J., Liettu, A., Remes, J. J., Jokelainen, J. J., Takala, T., Aunio, A., Starck, T., Nikkinen, J., Koponen, H., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.22164 · Cited by 40
Prematurity Affects Cortical Maturation in Early Childhood
Phillips, J., Montague, E. Q., Aragón, M., Lowe, J. R., Schrader, R. M., Ohls, R. K., & Caprihan, A. (2011) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2011.06.001 · Cited by 33 · cited 2×
“Recent high-resolution MRI studies identify age-dependent changes in cortical thickness and volume that vary throughout the brain (Giedd and Rapoport, 2010) and may be sensitive to disorders such as prematurity (Phillips et al., 2011), autism (Castelli et al.”
BackgroundSelf-citationExtracting functional networks with spatial independent component analysis
Esposito, F., & Goebel, R. (2011) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32834897a5 · Cited by 31 · cited 1×
“Accounting for more variance at the subject level data reduction improves the estimation of group aggregate spatial maps as well as back reconstructed subjectspecific maps and time-courses (Erhardt et al., 2011; Esposito and Goebel, 2011).”
BackgroundNeural Representation of Maternal Face Processing: A Functional Magnetic Resonance Imaging Study
Ramasubbu, R., Masalovich, S. E., Peltier, S., Holtzheimer, P. E., Heim, C. C., & Mayberg, H. S. (2007) · The Canadian Journal of Psychiatry · doi:10.1177/070674370705201107 · Cited by 20 · cited 2×
“, 2004), with the posterior cingulate cortex particularly important for emotional processing of faces (Ramasubbu et al., 2007).”
BackgroundHuttenlocher (1997) · doi:10.1002/(sici)1096-9861(19971020)387:2
Cited by
Sorted by citations
Grayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411
“In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al., 2014; Fransson et al., 2007; Gao et al., 2009; Smyser et al., 2010; Wylie et al., 2014).”
BackgroundThe UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development
Howell, B., Styner, M. A., Gao, W., Yap, P., Wang, L., Baluyot, K., Yacoub, E. S., Chen, G., Potts, T., Salzwedel, A., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.049 · Cited by 452
Gao, W., Alcauter, S., Elton, A., Hernandez-Castillo, C. R., Smith, J. K., Ramirez, J., & Lin, W. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu088 · Cited by 380
“Consistently, Damaraju et al. (2013) imaged normal pediatric subjects at 4 and 9 months and showed decreased local functional connectivity and increased distant connectivity, exemplifying the dynamic functional maturation process during this critical period.”
BackgroundRashid, B., Arbabshirani, M. R., Damaraju, E., Cetin, M. S., Miller, R. L., Pearlson, G. D., & Calhoun, V. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.04.051 · Cited by 335
“We expected some connectivity measures to be better captured in a static model and others in a dynamic model (Damaraju et al., 2014).”
BackgroundSelf-citationThe 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
“By 4 years of age, there is marked increase in connectivity and the DMN becomes similar to what is observed in adults (Damaraju et al., 2014; Gao et al., 2009; Lee et al., 2013).”
Metadata
- Authors
- Damaraju, E., Caprihan, A., Lowe, J. R., Allen, E. A., Calhoun, V. D., & Phillips, J. P.
- Affiliations
- Mind Research Network (US)
- University of New Mexico (US)
- Corresponding author
- Damaraju, E.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 84
- Pages
- 169-180
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3881974
- OpenAlex
- W1967832316
- Cited by
- 103
- References
- 69
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 10 · 2023: 4 · 2022: 5 · 2021: 11 · 2020: 14 · 2019: 5 · 2018: 11 · 2017: 4 · 2016: 9 · 2015: 8 · 2014: 4
- FWCI
- 4.01
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Delle Foundation
- NIH (R01-EB000840)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- functional connectivity, brain development, infants, resting-state networks, resting-state fMRI, default mode network, posterior cingulate cortex, longitudinal development
- MeSH terms
- Aging, Brain, Child, Child, Preschool, Female, Humans, Image Interpretation, Computer-Assisted, Longitudinal Studies, Male, Nerve Net, Neural Pathways, Neuronal Plasticity, Sensitivity and Specificity, Sleep, Reproducibility of Results, Connectome
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