Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.
paper
Cited
Public
- Authors
- Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi
- Year
- 2013
- Journal
- PloS one
- PMID
- 23390528
- DOI
- 10.1371/journal.pone.0055347
- PMCID
- PMC3563524
Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.
Global network properties.(A) The clustering coefficient and (B) the characteristic path length are shown as a function of cost thresholds and compared to the matched random networks. (C) The normalized clustering coefficient, the normalized characteristic path length, and (D) the small-worldness are shown as a function of cost thresholds. Note that the small-world regime of cost threshold adopted in this study was from 0.2 to 0.35. (E) The local efficiency and (F) the global efficiency are shown as a function of cost thresholds and compared to the matched random networks. Error bars indicate standard error in all subjects.
Global hubs in functional brain networks.Global hubs are defined as the brain regions with higher values (>Mean + SD) in any of (A) node degree, (B) node efficiency, and (C) node betweenness. The global hubs are shown in red with node sizes that indicate the values in regional nodal parameters. For a description of the abbreviations, see Table S1.
Effect of age on regional nodal properties.Significant linear positive, linear negative, quadratic positive, and quadratic negative correlations are indicated by red, green, yellow, and blue spheres, respectively. The significances of p<0.05 and p<0.01(uncorrected) are shown by spheres in small and big size, respectively. For a description of the abbreviations, see Table S1.
Effect of sex on regional nodal properties.The significant higher values of regional nodal parameters in female and male groups are shown in red and blue, respectively. The significances of p<0.05 and p<0.01 (uncorrected) are indicated by spheres in small and big size, respectively. For a description of the abbreviations, see Table S1.
Age-by-sex interaction on regional nodal properties.The significant age-by-sex interactions on regional nodal parameters are shown. The correlation between age and regional nodal parameters are shown in female and male groups, respectively. For a description of the abbreviations, see Table S1.
Effect of IQ on regional nodal properties.The significant positive and negative correlation between IQ and regional nodal parameters are shown in red and blue, respectively. The significances of p<0.05 and p<0.01 (uncorrected) are indicated by spheres in small and big size, respectively. For a description of the abbreviations, see Table S1.
| Name | Type |
|---|---|
| adolescents | cohort |
| adults | cohort |
| age | phenotype |
| Age-related increase local | phenotype |
| Anatomical connectivity local | anatomy |
| angular gyrus | anatomy |
| anterior cingulate cortex | anatomy |
| attention deficit hyperactivity disorder | phenotype |
| Attention system local | anatomy |
| Auditory functions local | phenotype |
| autism | phenotype |
| Automated Anatomical Labeling atlas local | anatomy |
| bilateral inferior parietal cortex | anatomy |
| brain | anatomy |
| brain anatomical networks local | anatomy |
| brain network properties local | phenotype |
| brain networks | anatomy |
| Brain perfusion local | anatomy |
| brain structure | anatomy |
| Calcarine Cortex local | anatomy |
| CAL.R local | anatomy |
| characteristic path length | phenotype |
| children | cohort |
| children and young adults local | cohort |
| children with normal development local | cohort |
| clustering coefficient local | phenotype |
| Clustering coefficient local | phenotype |
| cognition | phenotype |
| control system local | anatomy |
| Control system local | anatomy |
| CUN.L local | anatomy |
| default mode network | anatomy |
| default mode system local | anatomy |
| Default mode system local | anatomy |
| development | phenotype |
| dorsal superior frontal gyrus local | anatomy |
| Dorsal Superior Frontal Gyrus local | anatomy |
| DTI | drug |
| DVARS local | phenotype |
| Emotion | phenotype |
| Emotion system local | anatomy |
| Excluded subjects (9 subjects) local | cohort |
| executive functioning | phenotype |
| Frame-wise displacement local | phenotype |
| frontal cortex | anatomy |
| functional brain network local | anatomy |
| functional connectivity | phenotype |
| functional network measures local | phenotype |
| fusiform gyrus | anatomy |
| girl local | cohort |
| global efficiency local | phenotype |
| Global efficiency local | phenotype |
| global hub local | phenotype |
| gyrus rectus | anatomy |
| head motion | phenotype |
| healthy children local | phenotype |
| Healthy Japanese children local | cohort |
| Healthy pediatric subjects local | cohort |
| heschl gyrus | anatomy |
| HES.L local | anatomy |
| HES.R local | anatomy |
| Higher-order cognitive functions local | phenotype |
| HIP.L local | anatomy |
| hippocampus | anatomy |
| HIP.R local | anatomy |
| human brain | anatomy |
| human brain networks local | anatomy |
| human connectome local | cohort |
| IFGtriang.L local | anatomy |
| Infant brain local | cohort |
| inferior occipital gyrus | anatomy |
| inferior orbital frontal cortex local | anatomy |
| inferior orbitofrontal cortex local | anatomy |
| insula | anatomy |
| intelligence | phenotype |
| IPL | anatomy |
| IQ | phenotype |
| ITG.L local | anatomy |
| language system local | anatomy |
| Language system local | anatomy |
| left cuneus | anatomy |
| left hemispheric network local | anatomy |
| left Heschl's gyrus local | anatomy |
| left hippocampal formation local | anatomy |
| left inferior orbital frontal cortex local | anatomy |
| left inferior parietal lobule | anatomy |
| left inferior temporal gyrus | anatomy |
| left lingual gyrus local | anatomy |
| left medial superior frontal gyrus local | anatomy |
| left middle frontal gyrus | anatomy |
| left olfactory cortex local | anatomy |
| Left REC local | anatomy |
| left rectus gyrus local | anatomy |
| Left SPG local | anatomy |
| left superior temporal gyrus | anatomy |
| Linear age-related decrease local | phenotype |
| linear decrease in node degree local | phenotype |
| linear increase in node degree local | phenotype |
| LING.L local | anatomy |
| lingual gyrus | anatomy |
| local efficiency local | phenotype |
| Local efficiency local | phenotype |
| Locally specialized processing local | phenotype |
| matched random networks local | anatomy |
| MCG.R local | anatomy |
| medial orbitofrontal cortex | anatomy |
| medial prefrontal cortex | anatomy |
| medial superior frontal gyrus | anatomy |
| MFG.L local | anatomy |
| Middle Cingulate Gyrus local | anatomy |
| middle frontal gyrus | anatomy |
| Miyagi child cohort local | cohort |
| negative quadratic trajectory of node degree local | phenotype |
| neurological disorders | phenotype |
| node betweenness local | phenotype |
| Node betweenness local | phenotype |
| Node betweenness in left REC local | phenotype |
| node degree local | phenotype |
| Node degree in left SPG local | phenotype |
| node efficiency local | phenotype |
| Node efficiency local | phenotype |
| Node efficiency in left cuneus local | phenotype |
| Node efficiency in left SPG local | phenotype |
| normalized characteristic path length local | phenotype |
| Normalized characteristic path length local | phenotype |
| normalized clustering coefficient local | phenotype |
| Normalized clustering coefficient local | phenotype |
| Occipital brain region local | anatomy |
| occipital cortex | anatomy |
| OLF.L local | anatomy |
| ORBinf local | anatomy |
| ORBinf.L local | anatomy |
| ORBinf.R local | anatomy |
| ORBmed.R local | anatomy |
| PAL.L local | anatomy |
| pallidum | anatomy |
| paracentral lobule | anatomy |
| Parietal brain region local | anatomy |
| parietal cortex | anatomy |
| PCG.L local | anatomy |
| PCUN.L local | anatomy |
| positive quadratic trajectory of node degree local | phenotype |
| postcentral gyrus | anatomy |
| posterior cingulate cortex | anatomy |
| precuneus | anatomy |
| precuneus/posterior cingulate regions local | anatomy |
| prefrontal lobe local | anatomy |
| Primary motor/somatosensory functions local | phenotype |
| psychiatric disorders | phenotype |
| putamen | anatomy |
| PUT.L local | anatomy |
| Quadratic developmental trajectory local | phenotype |
| REC local | anatomy |
| REC.L local | anatomy |
| resting-state fMRI local | drug |
| right-handed children local | phenotype |
| right hemispheric network local | anatomy |
| right inferior orbital frontal cortex local | anatomy |
| right inferior parietal lobule | anatomy |
| right medial superior frontal gyrus local | anatomy |
| right middle cingulate gyrus local | anatomy |
| right middle frontal gyrus | anatomy |
| right paracentral lobule local | anatomy |
| Right REC local | anatomy |
| rolandic operculum | anatomy |
| rs-fMRI local | drug |
| schizophrenia | phenotype |
| sex | phenotype |
| sex differences | phenotype |
| sexes local | phenotype |
| SFGdor.L local | anatomy |
| SFGmed.R local | anatomy |
| SFMmed.R local | anatomy |
| SMA.L local | anatomy |
| small-worldness local | phenotype |
| Small-worldness local | phenotype |
| Small-world organization local | phenotype |
| Small-world properties | phenotype |
| small-world regime local | phenotype |
| SMA.R local | anatomy |
| SPG.L local | anatomy |
| SPG.R local | anatomy |
| STG.L local | anatomy |
| structural brain networks local | anatomy |
| structural brain networks local | phenotype |
| Structural brain networks local | anatomy |
| structural MRI | drug |
| Study cohort (51 subjects) local | cohort |
| Summary network parameter local | phenotype |
| summary network parameters local | phenotype |
| superior occipital gyrus | anatomy |
| superior orbitofrontal cortex local | anatomy |
| superior parietal gyrus local | anatomy |
| Superior Parietal Gyrus local | anatomy |
| superior temporal gyrus | anatomy |
| superior temporal pole local | anatomy |
| supplementary motor area | anatomy |
| supramarginal gyrus | anatomy |
| Temporal brain region local | anatomy |
| triangular part of inferior frontal gyrus local | anatomy |
| vision system local | anatomy |
| Visual functions local | phenotype |
| Visual-input analysis local | phenotype |
| visual processing | phenotype |
| visuospatial function local | phenotype |
| whole brain | anatomy |
| young adults | cohort |
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| Citation | PMID | DOI | Status |
|---|---|---|---|
| AchardS, BullmoreE (2007) Efficiency and cost of economical brain functional networks. PLoS Comput Biol 3: e17.1727468410.1371/journal.pcbi.0030017PMC1794324 | — | — | — |
| AchardS, SalvadorR, WhitcherB, SucklingJ, BullmoreE (2006) A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci 26: 63–72.1639967310.1523/JNEUROSCI.3874-05.2006PMC6674299 | — | — | — |
| AkaikeH (1974) A new look at the statistical model identification. IEEE Trans Automatic Control 19: 716–723. | — | — | — |
| AshburnerJ, FristonKJ (1999) Nonlinear spatial normalization using basis functions. Hum Brain Mapp 7: 254–266.1040876910.1002/(SICI)1097-0193(1999)7:4<254::AID-HBM4>3.0.CO;2-GPMC6873340 | — | — | — |
| Azuma H, Ueno K, Fujita K, Maekawa H, Ishikuma T, et al.. (1998) Japanese Wechsler Intelligence Scale for Children. Tokyo: Nihon Bunka Kagakusha. | — | — | — |
| BarttfeldP, WickerB, CukierS, NavartaS, LewS, et al (2011) A big-world network in ASD: dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections. Neuropsychologia 49: 254–263.2111098810.1016/j.neuropsychologia.2010.11.024 | — | — | — |
| BassettDS, BullmoreE, VerchinskiBA, MattayVS, WeinbergerDR, et al (2008) Hierarchical organization of human cortical networks in health and schizophrenia. J Neurosci 28: 9239–9248.1878430410.1523/JNEUROSCI.1929-08.2008PMC2878961 | — | — | — |
| BassettDS, BullmoreET (2009) Human brain networks in health and disease. Curr Opin Neurol 22: 340–347 310.1097/WCO.1090b1013e32832d32893dd.1949477410.1097/WCO.0b013e32832d93ddPMC2902726 | — | — | — |
| BassettDS, BullmoreET, Meyer-LindenbergA, ApudJA, WeinbergerDR, et al (2009) Cognitive fitness of cost-efficient brain functional networks. Proc Natl Acad Sci U S A 106: 11747–11752.1956460510.1073/pnas.0903641106PMC2703669 | — | — | — |
| BecharaA (2004) The role of emotion in decision-making: evidence from neurological patients with orbitofrontal damage. Brain Cogn 55: 30–40.1513484110.1016/j.bandc.2003.04.001 | — | — | — |
| BullmoreE, SpornsO (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10: 186–198.1919063710.1038/nrn2575 | — | — | — |
| BullmoreE, SpornsO (2012) The economy of brain network organization. Nat Rev Neurosci 13: 336–349.2249889710.1038/nrn3214 | — | — | — |
| BullmoreET, BassettDS (2011) Brain graphs: graphical models of the human brain connectome. Annu Rev Clin Psychol 7: 113–140.2112878410.1146/annurev-clinpsy-040510-143934 | — | — | — |
| BusseyK, BanduraA (1999) Social cognitive theory of gender development and differentiation. Psychol Rev 106: 676–713.1056032610.1037/0033-295x.106.4.676 | — | — | — |
| CaseyBJ, GieddJN, ThomasKM (2000) Structural and functional brain development and its relation to cognitive development. Biol Psychol 54: 241–257.1103522510.1016/s0301-0511(00)00058-2 | — | — | — |
| ChenZJ, HeY, Rosa-NetoP, GermannJ, EvansAC (2008) Revealing Modular Architecture of Human Brain Structural Networks by Using Cortical Thickness from MRI. Cereb Cortex 18: 2374–2381.1826795210.1093/cercor/bhn003PMC2733312 | — | — | — |
| ClaydenJD, JentschkeS, MunozM, CooperJM, ChadwickMJ, et al (2012) Normative Development of White Matter Tracts: Similarities and Differences in Relation to Age, Gender, and Intelligence. Cereb Cortex 8: 1738–1747.10.1093/cercor/bhr24321940703 | — | — | — |
| ClementsAM, RimrodtSL, AbelJR, BlanknerJG, MostofskySH, et al (2006) Sex differences in cerebral laterality of language and visuospatial processing. Brain Lang 98: 150–158.1671638910.1016/j.bandl.2006.04.007 | — | — | — |
| CohenRZ, SeemanMV, GotowiecA, KopalaL (1999) Earlier puberty as a predictor of later onset of schizophrenia in women. American Journal of Psychiatry 156: 1059–1064.1040145210.1176/ajp.156.7.1059 | — | — | — |
| CorbettaM, MiezinFM, ShulmanGL, PetersenSE (1993) A PET study of visuospatial attention. J Neurosci 13: 1202–1226.844100810.1523/JNEUROSCI.13-03-01202.1993PMC6576604 | — | — | — |
| De BellisMD, KeshavanMS, BeersSR, HallJ, FrustaciK, et al (2001) Sex differences in brain maturation during childhood and adolescence. Cereb Cortex 11: 552–557.1137591610.1093/cercor/11.6.552 | — | — | — |
| DuncanJ, SeitzRJ, KolodnyJ, BorD, HerzogH, et al (2000) A neural basis for general intelligence. Science 289: 457–460.1090320710.1126/science.289.5478.457 | — | — | — |
| FairDA, CohenAL, DosenbachNU, ChurchJA, MiezinFM, et al (2008) The maturing architecture of the brain's default network. Proc Natl Acad Sci U S A 105: 4028–4032.1832201310.1073/pnas.0800376105PMC2268790 | — | — | — |
| FairDA, CohenAL, PowerJD, DosenbachNU, ChurchJA, et al (2009) Functional brain networks develop from a “local to distributed” organization. PLoS Comput Biol 5: e1000381.1941253410.1371/journal.pcbi.1000381PMC2671306 | — | — | — |
| FairDA, DosenbachNU, ChurchJA, CohenAL, BrahmbhattS, et al (2007) Development of distinct control networks through segregation and integration. Proc Natl Acad Sci U S A 104: 13507–13512.1767969110.1073/pnas.0705843104PMC1940033 | — | — | — |
| FangmeierT, KnauffM, RuffCC, SloutskyV (2006) FMRI evidence for a three-stage model of deductive reasoning. J Cogn Neurosci 18: 320–334.1651299910.1162/089892906775990651 | — | — | — |
| FanY, ShiF, SmithJK, LinW, GilmoreJH, et al (2011) Brain anatomical networks in early human brain development. Neuroimage 54: 1862–1871.2065031910.1016/j.neuroimage.2010.07.025PMC3023885 | — | — | — |
| FoxMD, SnyderAZ, VincentJL, CorbettaM, Van EssenDC, et al (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102: 9673–9678.1597602010.1073/pnas.0504136102PMC1157105 | — | — | — |
| FranssonP (2005) Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis. Hum Brain Mapp 26: 15–29.1585246810.1002/hbm.20113PMC6871700 | — | — | — |
| FranssonP, ÅdenU, BlennowM, LagercrantzH (2011) The Functional Architecture of the Infant Brain as Revealed by Resting-State fMRI. Cerebral Cortex 21: 145–154.2042124910.1093/cercor/bhq071 | — | — | — |
| FreemanL (1977) A set of measures of centrality based upon betweenness. Sociometry 35–41. | — | — | — |
| FristonKJ, FrithCD, FrackowiakRS, TurnerR (1995) Characterizing dynamic brain responses with fMRI: a multivariate approach. Neuroimage 2: 166–172.934359910.1006/nimg.1995.1019 | — | — | — |
| FristonKJ, FrithCD, LiddlePF, FrackowiakRS (1993) Functional connectivity: the principal-component analysis of large (PET) data sets. J Cereb Blood Flow Metab 13: 5–14.841701010.1038/jcbfm.1993.4 | — | — | — |
| Fujita K, Maekawa H, Dairoku H, Yamanaka K (2006) Japanese Wechsler Adult Intelligence Scale. Tokyo: Nihon Bunka Kagakusha. | — | — | — |
| GaoW, GilmoreJH, GiovanelloKS, SmithJK, ShenD, et al (2011) Temporal and spatial evolution of brain network topology during the first two years of life. PLoS ONE 6: e25278.2196647910.1371/journal.pone.0025278PMC3179501 | — | — | — |
| GongG, HeY, ConchaL, LebelC, GrossDW, et al (2009) Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb Cortex 19: 524–536.1856760910.1093/cercor/bhn102PMC2722790 | — | — | — |
| GongG, HeY, EvansAC (2011) Brain connectivity: gender makes a difference. Neuroscientist 17: 575–591.2152772410.1177/1073858410386492 | — | — | — |
| GongG, Rosa-NetoP, CarbonellF, ChenZJ, HeY, et al (2009) Age- and gender-related differences in the cortical anatomical network. J Neurosci 29: 15684–15693.2001608310.1523/JNEUROSCI.2308-09.2009PMC2831804 | — | — | — |
| GrayJR, ChabrisCF, BraverTS (2003) Neural mechanisms of general fluid intelligence. Nat Neurosci 6: 316–322.1259240410.1038/nn1014 | — | — | — |
| HayasakaS, LaurientiPJ (2010) Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data. Neuroimage 50: 499–508.2002621910.1016/j.neuroimage.2009.12.051PMC2824075 | — | — | — |
| HeY, ChenZ, EvansA (2008) Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's disease. J Neurosci 28: 4756–4766.1844865210.1523/JNEUROSCI.0141-08.2008PMC6670444 | — | — | — |
| HeY, ChenZJ, EvansAC (2007) Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex 17: 2407–2419.1720482410.1093/cercor/bhl149 | — | — | — |
| HeY, EvansA (2010) Graph theoretical modeling of brain connectivity. Curr Opin Neurol 23: 341–350.2058168610.1097/WCO.0b013e32833aa567 | — | — | — |
| HeY, WangJ, WangL, ChenZJ, YanC, et al (2009) Uncovering intrinsic modular organization of spontaneous brain activity in humans. PLoS ONE 4: e5226.1938129810.1371/journal.pone.0005226PMC2668183 | — | — | — |
| HinesM (2011) Gender development and the human brain. Annu Rev Neurosci 34: 69–88.2143868510.1146/annurev-neuro-061010-113654 | — | — | — |
| Humphries MD, Gurney K, Prescott TJ (2006) The brainstem reticular formation is a small-world, not scale-free network. pp. 503–511.10.1098/rspb.2005.3354PMC156020516615219 | — | — | — |
| HynesCA, BairdAA, GraftonST (2006) Differential role of the orbital frontal lobe in emotional versus cognitive perspective-taking. Neuropsychologia 44: 374–383.1611214810.1016/j.neuropsychologia.2005.06.011 | — | — | — |
| IkedaY, KameyamaM, NaritaK, TakeiY, SudaM, et al (2010) Total and regional brain volume reductions due to the Syndrome of Irreversible Lithium-Effectuated Neurotoxicity (SILENT): a voxel-based morphometric study. Prog Neuropsychopharmacol Biol Psychiatry 34: 244–246.1985299610.1016/j.pnpbp.2009.10.010 | — | — | — |
| Iturria-MedinaY, SoteroRC, Canales-RodriguezEJ, Aleman-GomezY, Melie-GarciaL (2008) Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. Neuroimage 40: 1064–1076.1827240010.1016/j.neuroimage.2007.10.060 | — | — | — |
| JungRE, HaierRJ (2007) The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav Brain Sci 30: 135–154 discussion 154–187.1765578410.1017/S0140525X07001185 | — | — | — |
| LatoraV, MarchioriM (2001) Efficient behavior of small-world networks. Phys Rev Lett 87: 198701.1169046110.1103/PhysRevLett.87.198701 | — | — | — |
| LeeKH, ChoiYY, GrayJR, ChoSH, ChaeJH, et al (2006) Neural correlates of superior intelligence: stronger recruitment of posterior parietal cortex. Neuroimage 29: 578–586.1612294610.1016/j.neuroimage.2005.07.036 | — | — | — |
| LenrootRK, GieddJN (2010) Sex differences in the adolescent brain. Brain Cogn 72: 46–55.1991396910.1016/j.bandc.2009.10.008PMC2818549 | — | — | — |
| LenrootRK, GogtayN, GreensteinDK, WellsEM, WallaceGL, et al (2007) Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage 36: 1065–1073.1751313210.1016/j.neuroimage.2007.03.053PMC2040300 | — | — | — |
| LiuY, LiangM, ZhouY, HeY, HaoY, et al (2008) Disrupted small-world networks in schizophrenia. Brain 131: 945–961.1829929610.1093/brain/awn018 | — | — | — |
| LiY, LiuY, LiJ, QinW, LiK, et al (2009) Brain anatomical network and intelligence. PLoS Comput Biol 5: e1000395.1949208610.1371/journal.pcbi.1000395PMC2683575 | — | — | — |
| MarguliesDS, BottgerJ, LongX, LvY, KellyC, et al (2010) Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity. MAGMA 23: 289–307.2097288310.1007/s10334-010-0228-5 | — | — | — |
| Maslov S, Sneppen K (2002) Specificity and Stability in Topology of Protein Networks. pp. 910–913.10.1126/science.106510311988575 | — | — | — |
| MesulamMM (1998) From sensation to cognition. Brain 121: 1013–1052.964854010.1093/brain/121.6.1013 | — | — | — |
| MurphyK, BirnRM, HandwerkerDA, JonesTB, BandettiniPA (2009) The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage 44: 893–905.1897671610.1016/j.neuroimage.2008.09.036PMC2750906 | — | — | — |
| NewmanMEJ (2003) The Structure and Function of Complex Networks. SIAM Review 45: 167–256. | — | — | — |
| OldfieldRC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9: 97–113.514649110.1016/0028-3932(71)90067-4 | — | — | — |
| PangelinanMM, ZhangG, VanMeterJW, ClarkJE, HatfieldBD, et al (2011) Beyond age and gender: relationships between cortical and subcortical brain volume and cognitive-motor abilities in school-age children. Neuroimage 54: 3093–3100.2107840210.1016/j.neuroimage.2010.11.021PMC3020257 | — | — | — |
| PessoaL, McKennaM, GutierrezE, UngerleiderLG (2002) Neural processing of emotional faces requires attention. Proc Natl Acad Sci U S A 99: 11458–11463.1217744910.1073/pnas.172403899PMC123278 | — | — | — |
| PowerJD, BarnesKA, SnyderAZ, SchlaggarBL, PetersenSE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59: 2142–2154.2201988110.1016/j.neuroimage.2011.10.018PMC3254728 | — | — | — |
| PowerJD, FairDA, SchlaggarBL, PetersenSE (2010) The development of human functional brain networks. Neuron 67: 735–748.2082630610.1016/j.neuron.2010.08.017PMC2941973 | — | — | — |
| RaichleME, MacLeodAM, SnyderAZ, PowersWJ, GusnardDA, et al (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98: 676–682.1120906410.1073/pnas.98.2.676PMC14647 | — | — | — |
| RaichleME, SnyderAZ (2007) A default mode of brain function: a brief history of an evolving idea. Neuroimage 37: 1083–1090 discussion 1097–1089.1771979910.1016/j.neuroimage.2007.02.041 | — | — | — |
| RubiaK, HydeZ, HalariR, GiampietroV, SmithA (2010) Effects of age and sex on developmental neural networks of visual-spatial attention allocation. Neuroimage 51: 817–827.2018884110.1016/j.neuroimage.2010.02.058 | — | — | — |
| RubinovM, SpornsO (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52: 1059–1069.1981933710.1016/j.neuroimage.2009.10.003 | — | — | — |
| SchmithorstVJ (2009) Developmental Sex Differences in the Relation of Neuroanatomical Connectivity to Intelligence. Intelligence 37: 164–173.2129796610.1016/j.intell.2008.07.001PMC3032174 | — | — | — |
| SchmithorstVJ, HollandSK (2006) Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls. Neuroimage 31: 1366–1379.1654035010.1016/j.neuroimage.2006.01.010 | — | — | — |
| SchmithorstVJ, HollandSK (2007) Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis. Neuroimage 35: 406–419.1722357810.1016/j.neuroimage.2006.11.046PMC2100392 | — | — | — |
| SeemanMV (1997) Psychopathology in women and men: focus on female hormones. Am J Psychiatry 154: 1641–1647.939694010.1176/ajp.154.12.1641 | — | — | — |
| ShawP, GreensteinD, LerchJ, ClasenL, LenrootR, et al (2006) Intellectual ability and cortical development in children and adolescents. Nature 440: 676–679.1657217210.1038/nature04513 | — | — | — |
| ShuN, LiuY, LiK, DuanY, WangJ, et al (2011) Diffusion Tensor Tractography Reveals Disrupted Topological Efficiency in White Matter Structural Networks in Multiple Sclerosis. Cereb Cortex 21: 2565–2577.2146720910.1093/cercor/bhr039 | — | — | — |
| SongM, ZhouY, LiJ, LiuY, TianL, et al (2008) Brain spontaneous functional connectivity and intelligence. Neuroimage 41: 1168–1176.1843420310.1016/j.neuroimage.2008.02.036 | — | — | — |
| SpornsO (2011) The human connectome: a complex network. Ann N Y Acad Sci 1224: 109–125.2125101410.1111/j.1749-6632.2010.05888.x | — | — | — |
| SpornsO, HoneyCJ, KotterR (2007) Identification and classification of hubs in brain networks. PLoS ONE 2: e1049.1794061310.1371/journal.pone.0001049PMC2013941 | — | — | — |
| SpornsO, TononiG (2001) Classes of network connectivity and dynamics. Complexity 7: 28–38. | — | — | — |
| SpornsO, ZwiJ (2004) The small world of the cerebral cortex. Neuroinformatics 2: 145–162.1531951210.1385/NI:2:2:145 | — | — | — |
| StamCJ (2004) Functional connectivity patterns of human magnetoencephalographic recordings: a ‘small-world’ network? Neurosci Lett 355: 25–28.1472922610.1016/j.neulet.2003.10.063 | — | — | — |
| SupekarK, MusenM, MenonV (2009) Development of large-scale functional brain networks in children. PLoS Biol 7: e1000157.1962106610.1371/journal.pbio.1000157PMC2705656 | — | — | — |
| TakiY, HashizumeH, SassaY, TakeuchiH, AsanoM, et al (2010) Breakfast staple types affect brain gray matter volume and cognitive function in healthy children. PLoS ONE 5: e15213.2117033410.1371/journal.pone.0015213PMC2999543 | — | — | — |
| TakiY, HashizumeH, SassaY, TakeuchiH, AsanoM, et al (2012) Correlation among body height, intelligence, and brain gray matter volume in healthy children. Neuroimage 59: 1023–1027.2193021510.1016/j.neuroimage.2011.08.092 | — | — | — |
| TakiY, HashizumeH, SassaY, TakeuchiH, WuK, et al (2011) Correlation between gray matter density-adjusted brain perfusion and age using brain MR images of 202 healthy children. Hum Brain Mapp 32: 1973–1985.2125938410.1002/hbm.21163PMC6870039 | — | — | — |
| TakiY, HashizumeH, SassaY, TakeuchiH, WuK, et al (2011) Gender differences in partial-volume corrected brain perfusion using brain MRI in healthy children. Neuroimage 58: 709–715.2178295810.1016/j.neuroimage.2011.07.020 | — | — | — |
| TakiY, HashizumeH, ThyreauB, SassaY, TakeuchiH, et al (2012) Sleep duration during weekdays affects hippocampal gray matter volume in healthy children. Neuroimage 60: 471–475.2219774210.1016/j.neuroimage.2011.11.072 | — | — | — |
| Talairach J, Tournoux P (1998) Co-Planar Stereotaxic Atlas of the Human Brain New York: Thieme. | — | — | — |
| TianL, WangJ, YanC, HeY (2011) Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study. Neuroimage 54: 191–202.2068817710.1016/j.neuroimage.2010.07.066 | — | — | — |
| TomasiD, VolkowND (2012) Aging and functional brain networks. Mol Psychiatry 17: 549–558.10.1038/mp.2011.81PMC319390821727896 | — | — | — |
| Tzourio-MazoyerN, LandeauB, PapathanassiouD, CrivelloF, EtardO, et al (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15: 273–289.1177199510.1006/nimg.2001.0978 | — | — | — |
| UddinLQ, SupekarK, MenonV (2010) Typical and atypical development of functional human brain networks: insights from resting-state FMRI. Front Syst Neurosci 4: 21.2057758510.3389/fnsys.2010.00021PMC2889680 | — | — | — |
| van den HeuvelMP, SpornsO (2011) Rich-club organization of the human connectome. J Neurosci 31: 15775–15786.2204942110.1523/JNEUROSCI.3539-11.2011PMC6623027 | — | — | — |
| van den HeuvelMP, StamCJ, KahnRS, Hulshoff PolHE (2009) Efficiency of functional brain networks and intellectual performance. J Neurosci 29: 7619–7624.1951593010.1523/JNEUROSCI.1443-09.2009PMC6665421 | — | — | — |
| Van DijkKR, SabuncuMR, BucknerRL (2012) The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59: 431–438.2181047510.1016/j.neuroimage.2011.07.044PMC3683830 | — | — | — |
| VogelAC, PowerJD, PetersenSE, SchlaggarBL (2010) Development of the brain's functional network architecture. Neuropsychol Rev 20: 362–375.2097656310.1007/s11065-010-9145-7PMC3811138 | — | — | — |
| WangJ, WangL, ZangY, YangH, TangH, et al (2009) Parcellation-dependent small-world brain functional networks: a resting-state fMRI study. Hum Brain Mapp 30: 1511–1523.1864935310.1002/hbm.20623PMC6870680 | — | — | — |
| WangJ, ZuoX, HeY (2010) Graph-based network analysis of resting-state functional MRI. Front Syst Neurosci 4: 16.2058909910.3389/fnsys.2010.00016PMC2893007 | — | — | — |
| WangL, ShenH, TangF, ZangY, HuD (2012) Combined structural and resting-state functional MRI analysis of sexual dimorphism in the young adult human brain: an MVPA approach. Neuroimage 61: 931–940.2249865710.1016/j.neuroimage.2012.03.080 | — | — | — |
| WangL, ZhuC, HeY, ZangY, CaoQ, et al (2009) Altered small-world brain functional networks in children with attention-deficit/hyperactivity disorder. Hum Brain Mapp 30: 638–649.1821962110.1002/hbm.20530PMC6870909 | — | — | — |
| WattsDJ, StrogatzSH (1998) Collective dynamics of ‘small-world’ networks. Nature 393: 440–442.962399810.1038/30918 | — | — | — |
| WigGS, SchlaggarBL, PetersenSE (2011) Concepts and principles in the analysis of brain networks. Ann N Y Acad Sci 1224: 126–146.2148629910.1111/j.1749-6632.2010.05947.x | — | — | — |
| WuK, TakiY, SatoK, KinomuraS, GotoR, et al (2012) Age-related changes in topological organization of structural brain networks in healthy individuals. Hum Brain Mapp 33: 552–568.2139127910.1002/hbm.21232PMC6870030 | — | — | — |
| WuK, TakiY, SatoK, SassaY, InoueK, et al (2011) The overlapping community structure of structural brain network in young healthy individuals. PLoS ONE 6: e19608.2157311110.1371/journal.pone.0019608PMC3089616 | — | — | — |
| YanC, CheungB, LiQ, ColcombeS, CraddockRC, KellyC, Di MartinoA, CastellanosFX, MilhamM (2012) Regional Differences in the Impact of Head Motion on R-fMRI Measures: A Voxelwise Analysis. 18th Annual Meeting of the Organization for Human Brain Mapping. Beijing | — | — | — |
| YanC, GongG, WangJ, WangD, LiuD, et al (2011) Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study. Cereb Cortex 21: 449–458.2056231810.1093/cercor/bhq111 | — | — | — |
| YanC-G, ZangY-F (2010) DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Front Syst Neurosci 4: 13.2057759110.3389/fnsys.2010.00013PMC2889691 | — | — | — |
| YapPT, FanY, ChenY, GilmoreJH, LinW, et al (2011) Development trends of white matter connectivity in the first years of life. PLoS ONE 6: e24678.2196636410.1371/journal.pone.0024678PMC3179462 | — | — | — |
| ZaleskyA, FornitoA, SealML, CocchiL, WestinCF, et al (2011) Disrupted axonal fiber connectivity in schizophrenia. Biol Psychiatry 69: 80–89.2103579310.1016/j.biopsych.2010.08.022PMC4881385 | — | — | — |
| ZuoXN, EhmkeR, MennesM, ImperatiD, CastellanosFX, et al (2012) Network Centrality in the Human Functional Connectome. Cereb Cortex 22: 1862–1875.2196856710.1093/cercor/bhr269 | — | — | — |
| ZuoXN, KellyC, Di MartinoA, MennesM, MarguliesDS, et al (2010) Growing together and growing apart: regional and sex differences in the lifespan developmental trajectories of functional homotopy. J Neurosci 30: 15034–15043.2106830910.1523/JNEUROSCI.2612-10.2010PMC2997358 | — | — | — |
In this knowledge base
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Differential effects of local and general fatigue on brain network efficiency, corticospinal and neuromuscular excitability. | Yu C et al. | — | 2026 | → |
| Sex-specific neurodevelopmental pathways to depressive symptoms. | Chan SY et al. | — | 2026 | → |
| The promise of infant MRI in psychiatry: toward a framework for neural network measures in early emotional and behavioral risk identification and new intervention targets. | Banihashemi L et al. | — | 2026 | → |
| Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence. | Duffy KA et al. | — | 2025 | → |
| Fiber length distribution characterizes the brain network maturation during early school-age. | Yu Y et al. | — | 2025 | → |
| Fitbit-measured sleep duration in young adolescents is associated with functional connectivity in attentional, executive control, memory, and sensory networks. | Turan O et al. | — | 2025 | → |
| Human lifespan changes in the brain's functional connectome. | Sun L et al. | — | 2025 | → |
| Regional, but not brain-wide, graph theoretic measures are robustly and reproducibly linked to general cognitive ability. | Molloy MF et al. | — | 2025 | → |
| Digital Media and Developing Brains: Concerns and Opportunities. | Hutton JS et al. | — | 2024 | → |
| Distinct structural brain network properties in children with familial versus non-familial attention-deficit/hyperactivity disorder (ADHD). | Baboli R et al. | — | 2024 | → |
| Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy. | Luo AC et al. | — | 2024 | → |
| Local gradient analysis of human brain function using the Vogt-Bailey Index. | Farrugia C et al. | — | 2024 | → |
| Macronutrient intake is associated with intelligence and neural development in adolescents. | Nakamura Y et al. | — | 2024 | → |
| Neural Signature of Rhyming Ability During Story Listening in Preschool-Age Children. | Hutton JS et al. | — | 2024 | → |
| Sex differences in human brain networks in normal and psychiatric populations from the perspective of small-world properties. | Zhou Y et al. | — | 2024 | → |
| Sex-related patterns of functional brain networks in children and adolescents with autism spectrum disorder. | Li C et al. | — | 2024 | → |
| The aging trajectories of brain functional hierarchy and its impact on cognition across the adult lifespan. | Wang X et al. | — | 2024 | → |
| The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis. | Kristanto D et al. | — | 2024 | → |
| Brain Networks and Adolescent Alcohol Use. | Yip SW et al. | — | 2023 | → |
| Diffusion tensor imaging reveals sex differences in pain sensitivity of rats. | Cha M et al. | — | 2023 | → |
| Early infant prefrontal gray matter volume is associated with concurrent and future infant emotionality. | Zhang Y et al. | — | 2023 | → |
| Fine-grained functional parcellation maps of the infant cerebral cortex. | Wang F et al. | — | 2023 | → |
| Functional and structural brain network development in children with attention deficit hyperactivity disorder. | Soman SM et al. | — | 2023 | → |
| Improvement of semantic processing ability of Chinese characters in school children: A comparative study based on 2009 and 2019 data. | Zhang Q et al. | — | 2023 | → |
| Neighborhood Socio-Economic Status Influences Motor Performance and Inhibitory Control in Kindergarten Children-Findings from the Cross-Sectional Kitafit Study. | Schott N et al. | — | 2023 | → |
| Richer than we thought: neurophysiological methods reveal rich-club network development is frequency- and sex-dependent. | Vandewouw MM et al. | — | 2023 | → |
| Robust sex differences in functional brain connectivity are present in utero. | Cook KM et al. | — | 2023 | → |
| Testosterone and the Amygdala's Functional Connectivity in Women and Men. | Kogler L et al. | — | 2023 | → |
| The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review. | Su WC et al. | — | 2023 | → |
| Association between the Use of Folic Acid Supplements during Pregnancy and Children's Cognitive Function at 7-9 Years of Age in the INMA Cohort Study. | Compañ-Gabucio LM et al. | — | 2022 | → |
| Associations between digital media use and brain surface structural measures in preschool-aged children. | Hutton JS et al. | — | 2022 | → |
| Cognitive stimulation has potential for brain activation in individuals with Rett syndrome. | Migliorelli C et al. | — | 2022 | → |
| Disrupted Resting State Attentional Network Connectivity in Adolescent and Young Adult Cannabis Users following Two-Weeks of Monitored Abstinence. | Harris JC et al. | — | 2022 | → |
| The impact of micronutrient supplementation in alcohol-exposed pregnancies on reaction time responses of preschoolers in Ukraine. | Kable JA et al. | — | 2022 | → |
| White matter and sustained attention in children with attention/deficit-hyperactivity disorder: A longitudinal fixel-based analysis. | Thomson P et al. | — | 2022 | → |
| Cerebral blood flow and cognitive outcome after pediatric stroke in the middle cerebral artery. | Steiner L et al. | — | 2021 | → |
| Cerebral microinfarcts affect brain structural network topology in cognitively impaired patients. | Zhang L et al. | — | 2021 | → |
| Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study. | Fan F et al. | — | 2021 | → |
| Differences between the child and adult brain in the local functional structure of the cerebral cortex. | Pujol J et al. | — | 2021 | → |
| Global Network Organization of the Fetal Functional Connectome. | De Asis-Cruz J et al. | — | 2021 | → |
| Intelligence and academic performance: Is it all in your head? | Bottenhorn KL et al. | — | 2021 | — |
| Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians. | González A et al. | — | 2021 | → |
| The maturation and cognitive relevance of structural brain network organization from early infancy to childhood. | Woodburn M et al. | — | 2021 | → |
| The neurodevelopmental basis of humor appreciation: A fNIRS study of young children. | Mayseless N et al. | — | 2021 | → |
| The Use of Lower or Higher Than Recommended Doses of Folic Acid Supplements during Pregnancy Is Associated with Child Attentional Dysfunction at 4-5 Years of Age in the INMA Project. | Compañ Gabucio LM et al. | — | 2021 | → |
| Within node connectivity changes, not simply edge changes, influence graph theory measures in functional connectivity studies of the brain. | Luo W et al. | — | 2021 | → |
| A Novel Individual Metabolic Brain Network for 18F-FDG PET Imaging. | Huang SY et al. | — | 2020 | → |
| Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective. | Hu Z et al. | — | 2020 | → |
| Associations between Neighborhood SES and Functional Brain Network Development. | Tooley UA et al. | — | 2020 | → |
| Development of Network Topology and Functional Connectivity of the Prefrontal Cortex. | Lopez KC et al. | — | 2020 | → |
| Predicting full-scale and verbal intelligence scores from functional Connectomic data in individuals with autism Spectrum disorder. | Dryburgh E et al. | — | 2020 | → |
| Sex Differences in Functional Connectivity of the Salience, Default Mode, and Central Executive Networks in Youth with ASD. | Lawrence KE et al. | — | 2020 | → |
| Transcranial photobiomodulation-induced changes in human brain functional connectivity and network metrics mapped by whole-head functional near-infrared spectroscopy <i>in vivo</i>. | Urquhart EL et al. | — | 2020 | → |
| Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review. | Farahani FV et al. | — | 2019 | → |
| Developmental changes in functional brain networks from birth through adolescence. | Gozdas E et al. | — | 2019 | → |
| First-year development of modules and hubs in infant brain functional networks. | Wen X et al. | — | 2019 | → |
| Functional near-infrared spectroscopy evidence for the development of topological asymmetry between hemispheric brain networks from childhood to adulthood. | Cai L et al. | — | 2019 | → |
| Hemisphere and Gender Differences in the Rich-Club Organization of Structural Networks. | Wang B et al. | — | 2019 | → |
| The development of brain network hubs. | Oldham S et al. | — | 2019 | → |
| What has sex got to do with it? The role of hormones in the transgender brain. | Nguyen HB et al. | — | 2019 | → |
| Age Related Changes in Topological Properties of Brain Functional Network and Structural Connectivity. | Shah C et al. | — | 2018 | → |
| Alterations in Brain Network Topology and Structural-Functional Connectome Coupling Relate to Cognitive Impairment. | Wang J et al. | — | 2018 | → |
| Alterations in Normal Aging Revealed by Cortical Brain Network Constructed Using IBASPM. | Li W et al. | — | 2018 | → |
| A Network Neuroscience Approach to Typical and Atypical Brain Development. | Morgan SE et al. | — | 2018 | → |
| A systematic literature review of sex differences in childhood language and brain development. | Etchell A et al. | — | 2018 | → |
| EEG Resting State Functional Connectivity in Adult Dyslexics Using Phase Lag Index and Graph Analysis. | Fraga González G et al. | — | 2018 | → |
| Key Brain Network Nodes Show Differential Cognitive Relevance and Developmental Trajectories during Childhood and Adolescence. | Kolskår KK et al. | — | 2018 | → |
| PAGANI Toolkit: Parallel graph-theoretical analysis package for brain network big data. | Du H et al. | — | 2018 | → |
| The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study. | Cai L et al. | — | 2018 | → |
| Biological Relevance of Network Architecture. | Gkigkitzis I et al. | — | 2017 | → |
| Complementarity of sex differences in brain and behavior: From laterality to multimodal neuroimaging. | Gur RC et al. | — | 2017 | → |
| Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature. | Grayson DS et al. | — | 2017 | → |
| Effect of Resting-State fNIRS Scanning Duration on Functional Brain Connectivity and Graph Theory Metrics of Brain Network. | Geng S et al. | — | 2017 | → |
| Functional connectivity abnormalities and associated cognitive deficits in fetal alcohol Spectrum disorders (FASD). | Wozniak JR et al. | — | 2017 | → |
| Genetic correlates of the development of theta event related oscillations in adolescents and young adults. | Chorlian DB et al. | — | 2017 | → |
| Is the Internet gaming-addicted brain close to be in a pathological state? | Park CH et al. | — | 2017 | → |
| Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects. | Li J et al. | — | 2017 | → |
| The minimum resting-state fNIRS imaging duration for accurate and stable mapping of brain connectivity network in children. | Wang J et al. | — | 2017 | → |
| An evidenced-based perspective on the validity of attention-deficit/hyperactivity disorder in the context of high intelligence. | Rommelse N et al. | — | 2016 | → |
| Awake surgery for hemispheric low-grade gliomas: oncological, functional and methodological differences between pediatric and adult populations. | Trevisi G et al. | — | 2016 | → |
| Children's intellectual ability is associated with structural network integrity. | Kim DJ et al. | — | 2016 | → |
| Development of brain networks and relevance of environmental and genetic factors: A systematic review. | Richmond S et al. | — | 2016 | → |
| Electrophysiological measures of resting state functional connectivity and their relationship with working memory capacity in childhood. | Barnes JJ et al. | — | 2016 | → |
| Functional Connectome before and following Temporal Lobectomy in Mesial Temporal Lobe Epilepsy. | Liao W et al. | — | 2016 | → |
| Gender transition affects neural correlates of empathy: A resting state functional connectivity study with ultra high-field 7T MR imaging. | Spies M et al. | — | 2016 | → |
| Intrinsic connectivity networks from childhood to late adolescence: Effects of age and sex. | Solé-Padullés C et al. | — | 2016 | → |
| Left hemisphere structural connectivity abnormality in pediatric hydrocephalus patients following surgery. | Yuan W et al. | — | 2016 | → |
| Sex differences in brain and behavior in adolescence: Findings from the Philadelphia Neurodevelopmental Cohort. | Gur RE et al. | — | 2016 | → |
| The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation. | Stevens MC | — | 2016 | → |
| The maturation of mismatch negativity networks in normal adolescence. | Cooray GK et al. | — | 2016 | → |
| Toward Developmental Connectomics of the Human Brain. | Cao M et al. | — | 2016 | → |
| Annual research review: Growth connectomics--the organization and reorganization of brain networks during normal and abnormal development. | Vértes PE et al. | — | 2015 | → |
| Away from home: the brain of the wandering mind as a model for schizophrenia. | Shin DJ et al. | — | 2015 | → |
| Changes in brain network efficiency and working memory performance in aging. | Stanley ML et al. | — | 2015 | → |
| Connectome-Scale Assessments of Functional Connectivity in Children with Primary Monosymptomatic Nocturnal Enuresis. | Lei D et al. | — | 2015 | → |
| Converging models of schizophrenia--Network alterations of prefrontal cortex underlying cognitive impairments. | Sakurai T et al. | — | 2015 | → |
| Decreased centrality of subcortical regions during the transition to adolescence: a functional connectivity study. | Sato JR et al. | — | 2015 | → |
| Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study. | Koenis MM et al. | — | 2015 | → |
| Gender differences in cerebral regional homogeneity of adult healthy volunteers: a resting-state FMRI study. | Xu C et al. | — | 2015 | → |
| Gender modulates the development of theta event related oscillations in adolescents and young adults. | Chorlian DB et al. | — | 2015 | → |
| Is "efficiency" a useful concept in cognitive neuroscience? | Poldrack RA | — | 2015 | → |
| Linked Sex Differences in Cognition and Functional Connectivity in Youth. | Satterthwaite TD et al. | — | 2015 | → |
| Neuroimaging of the developing brain. | Van Horn JD et al. | — | 2015 | → |
| Prenatal drug exposure to illicit drugs alters working memory-related brain activity and underlying network properties in adolescence. | Schweitzer JB et al. | — | 2015 | → |
| The effects of age, sex, and hormones on emotional conflict-related brain response during adolescence. | Cservenka A et al. | — | 2015 | → |
| The intrahemispheric functional properties of the developing sensorimotor cortex are influenced by maturation. | Berchicci M et al. | — | 2015 | → |
| The smarter, the stronger: intelligence level correlates with brain resilience to systematic insults. | Santarnecchi E et al. | — | 2015 | → |
| Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study. | Simos PG et al. | — | 2014 | → |
| Genetic influences on brain developmental trajectories on neuroimaging studies: from infancy to young adulthood. | Douet V et al. | — | 2014 | → |
| Identifying 22q11.2 deletion syndrome and psychosis using resting-state connectivity patterns. | Scariati E et al. | — | 2014 | → |
| Modern network science of neurological disorders. | Stam CJ | — | 2014 | → |
| Sex and the migraine brain. | Borsook D et al. | — | 2014 | → |
| The effects of pediatric epilepsy on a language connectome. | Eddin AS et al. | — | 2014 | → |
| Time of acquisition and network stability in pediatric resting-state functional magnetic resonance imaging. | White T et al. | — | 2014 | → |
| Topological organization of the human brain functional connectome across the lifespan. | Cao M et al. | — | 2014 | → |
| Unraveling the miswired connectome: a developmental perspective. | Di Martino A et al. | — | 2014 | → |
| Usefulness of the tri-axial accelerometer for assessing balance function in children. | Eguchi R et al. | — | 2014 | → |
| A machine learning approach to automated structural network analysis: application to neonatal encephalopathy. | Ziv E et al. | — | 2013 | → |
| Assessment of system dysfunction in the brain through MRI-based connectomics. | Filippi M et al. | — | 2013 | → |
| BrainNet Viewer: a network visualization tool for human brain connectomics. | Xia M et al. | — | 2013 | → |
| Graph theoretical analysis of developmental patterns of the white matter network. | Chen Z et al. | — | 2013 | → |
| Network analysis reveals patterns of antiepileptic drug use in children with medically intractable epilepsy. | Ibrahim GM et al. | — | 2013 | → |
| Reconceptualizing functional brain connectivity in autism from a developmental perspective. | Uddin LQ et al. | — | 2013 | → |
| The ontogeny of the human connectome: development and dynamic changes of brain connectivity across the life span. | Collin G et al. | — | 2013 | → |