Cited by 599Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesComplex Network Analysis Techniques

The DOI matches its Crossref record; 81 of the 81 references it cites were found in a registry or an index.

Brain Anatomical Network and Intelligence

Open access

Li, Yonghui, Liu, Yong, Li, Jun, Qin, Wen, Li, Kuncheng, Yu, Chunshui, Jiang, Tianzi·2009·PLoS Computational Biology

DOI 10.1371/journal.pcbi.1000395PMC PMC2683575

Open this paper in CoChat — free account Open PDF

Abstract

Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1371/journal.pcbi.1000395

Cites

81 of 81 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single subject brain
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319
Complex networks: structure and dynamics
BOCCALETTI, S., LATORA, V, MORENO, Y., CHAVEZ, M., & HWANG, D. (2006) · Physics Reports · doi:10.1016/j.physrep.2005.10.009 · Cited by 11,010
Exploring complex networks
Strogatz, S. H. (2001) · Nature · doi:10.1038/35065725 · Cited by 8,236
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368
Efficient behavior of small-world networks
Latora, V., & Marchiori, M. (2001) · Physical Review Letters · doi:10.1103/physrevlett.87.198701 · Cited by 5,119
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173
The architecture of complex weighted networks.
Barrat, A., Barthelemy, M., Pastor-Satorras, R., & Vespignani, A. (2003) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.0400087101 · Cited by 4,084
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. M. (1999) · Annals of Neurology · doi:10.1002/1531-8249(199902)45:2 · Cited by 3,513
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471

Flagged first, then by citations

Show all 81 references

Sorted by citations

Items 201–300 of 599

Connectome analysis for pre-operative brain mapping in neurosurgery
Hart, M. G., Price, S. J., & Suckling, J. (2016) · British Journal of Neurosurgery · doi:10.1080/02688697.2016.1208809 · Cited by 60
Association of Brain Network Efficiency with Aging, Depression, and Cognition
Ajilore, O., Lamar, M., & Kumar, A. (2013) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2013.10.004 · Cited by 57
Resting-State EEG Oscillatory Dynamics in Fragile X Syndrome: Abnormal Functional Connectivity and Brain Network Organization
van der Molen, M. J. W., Stam, C. J., & van der Molen, M. W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0088451 · Cited by 61
Childhood maltreatment is associated with alteration in global network fiber-tract architecture independent of history of depression and anxiety
Ohashi, K., Anderson, C. M., Bolger, E. A., Khan, A., McGreenery, C. E., & Teicher, M. H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.037 · Cited by 60
Graph theoretical analysis of human brain structural networks
Lo, C. Z., Yong He, A., & Lin, C. (2011) · Reviews in the Neurosciences · doi:10.1515/rns.2011.039 · Cited by 57
Long-Term Effects of Attentional Performance on Functional Brain Network Topology
Breckel, T. P. K., Thiel, C. M., Bullmore, E. T., Zalesky, A., Patel, A. X., & Gießing, C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074125 · Cited by 58
Quantifying the Link between Anatomical Connectivity, Gray Matter Volume and Regional Cerebral Blood Flow: An Integrative MRI Study
Várkuti, B., Çavuşoğlu, M., Kullik, A., Schiffler, B. C., Veit, R., Yilmaz, Ö., Rosenstiel, W., Braun, C., Uludaǧ, K., Birbaumer, N., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0014801 · Cited by 58
Brain Structural Networks Associated with Intelligence and Visuomotor Ability
Yoon, Y. B., Shin, W.-G., Lee, T. Y., Hur, J., Cho, K. I. K., Sohn, W. S., Kim, S., Lee, K.-H., & Kwon, J. S. (2017) · Scientific Reports · doi:10.1038/s41598-017-02304-z · Cited by 58
Gene Expression in the Rodent Brain is Associated with Its Regional Connectivity
Wolf, L., Goldberg, C., Manor, N., Sharan, R., & Ruppin, E. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002040 · Cited by 56
The salience network contributes to an individual's fluid reasoning capacity
Yuan, Z., Qin, W., Wang, D., Jiang, T., Zhang, Y., & Yu, C. (2012) · Behavioural Brain Research · doi:10.1016/j.bbr.2012.01.037 · Cited by 57
Self-citation
Rich Club Organization and Cognitive Performance in Healthy Older Participants
Baggio, H. C., Segura, B., Junqué, C., de Reus, M. A., Sala‐Llonch, R., & van den Heuvel, M. P. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00821 · Cited by 54
Altered brain structural connectivity in post-traumatic stress disorder: A diffusion tensor imaging tractography study
Long, Z., Duan, X., Xie, B., Du, H., Li, R., Xu, Q., Wei, L., Zhang, S., Wu, Y., Gao, Q. C., et al. (2013) · Journal of Affective Disorders · doi:10.1016/j.jad.2013.03.004 · Cited by 55
Structural MRI connectome in development: challenges of the changing brain
Tymofiyeva, O., Hess, C. P., Xu, D., & Barkovich, A. J. (2014) · British Journal of Radiology · doi:10.1259/bjr.20140086 · Cited by 55
Reduced efficiency of functional brain network underlying intellectual decline in patients with low-grade glioma
Xu, H., Ding, S., Hu, X., Yang, K., Xiao, C., Zou, Y., Chen, Y., Tao, L., Liu, H., & Qian, Z. (2013) · Neuroscience Letters · doi:10.1016/j.neulet.2013.02.062 · Cited by 54
Ventral medial prefrontal functional connectivity and emotion regulation in chronic schizophrenia: A pilot study
Fan, F., Tan, S., Yang, F., Tan, Y., Zhao, Y., Chen, N., Li, B.-B., Song, C.-S., Wang, Y., Jin, Z. H., et al. (2013) · Neuroscience Bulletin · doi:10.1007/s12264-013-1300-8 · Cited by 53
Connectomic correlates of response to treatment in first-episode psychosis
Crossley, N. A., Marques, T. R., Taylor, H., Chaddock, C., Dell’Acqua, F., Reinders, A. A. T. S., Mondelli, V., Forti, M. D., Simmons, A., David, A. S., et al. (2016) · Brain · doi:10.1093/brain/aww297 · Cited by 53
Structural brain network of gifted children has a more integrated and versatile topology
Solé‐Casals, J., Serra-Grabulosa, J. M., Romero-García, R., Vilaseca, G., Adán, A., Vilaró, N., Bargalló, N., & Bullmore, E. T. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01914-9 · Cited by 65
Structural brain networks and neuropsychiatric disorders
Wen, W. X., Yong He, A., & Sachdev, P. S. (2011) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e32834591f8 · Cited by 56
neuroVIISAS: Approaching Multiscale Simulation of the Rat Connectome
Schmitt, O., & Eipert, P. (2012) · Neuroinformatics · doi:10.1007/s12021-012-9141-6 · Cited by 51
Convergence and divergence across construction methods for human brain white matter networks: An assessment based on individual differences
Zhong, S., Yong He, A., & Gong, G. (2015) · Human Brain Mapping · doi:10.1002/hbm.22751 · Cited by 52
Network Approaches to Understand Individual Differences in Brain Connectivity: Opportunities for Personality Neuroscience
Tompson, S., Falk, E. B., Vettel, J. M., & Bassett, D. S. (2018) · Personality Neuroscience · doi:10.1017/pen.2018.4 · Cited by 51
Estimating individual contribution from group-based structural correlation networks
Saggar, M., Hosseini, S. M. H., Bruno, J. L., Quintin, E., Raman, M. M., Kesler, S. R., & Reiss, A. L. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.006 · Cited by 51
Neurodevelopmental alterations of large‐scale structural networks in children with new‐onset epilepsy
Bonilha, L., Tabesh, A., Dabbs, K., Hsu, D., Stafstrom, C. E., Hermann, B. P., & Lin, J. J. (2014) · Human Brain Mapping · doi:10.1002/hbm.22428 · Cited by 52
Common and unique neuro-functional basis of induction, visualization, and spatial relationships as cognitive components of fluid intelligence
Ebisch, S. J. H., Perrucci, M. G., Mercuri, P., Romanelli, R., Mantini, D., Romani, G. L., Colom, R., & Saggino, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.04.053 · Cited by 53
Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study
Sun, Y., Yu, C., Lee, R., Bezerianos, A., Collinson, S. L., & Sim, K. (2016) · Schizophrenia Research · doi:10.1016/j.schres.2016.01.025 · Cited by 52
Self-citation
Metrics of brain network architecture capture the impact of disease in children with epilepsy
Paldino, M. J., Zhang, W., Chu, Z. D., & Golriz, F. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.12.005 · Cited by 50
Cluster-based statistics for brain connectivity in correlation with behavioral measures.
Han, C. E., Yoo, S. W., Seo, S. W., Na, D. L., & Seong, J.-K. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072332 · Cited by 49
Intelligence and eeg measures of information flow: efficiency and homeostatic neuroplasticity
Thatcher, R. W., Palmero‐Soler, E., North, D. M., & Biver, C. J. (2016) · Scientific Reports · doi:10.1038/srep38890 · Cited by 49
Whole-brain white matter organization, intelligence, and educational attainment
Bathelt, J., Scerif, G., Nobre, A. C., & Astle, D. E. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.02.004 · Cited by 49
White matter integrity and structural brain network topology in cerebral small vessel disease: The Hamburg city health study
Frey, B. M., Petersen, M., Schlemm, E., Mayer, C., Hanning, U. M. P., Engelke, K., Fiehler, J., Borof, K., Jagodzinski, A., Gerloff, C. P., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25301 · Cited by 51
Altered Topological Organization of White Matter Structural Networks in Patients with Neuromyelitis Optica
Liu, Y., Duan, Y., Yong He, A., Wang, J., Xia, M., Yu, C., Dong, H., Ye, J., Butzkueven, H., Li, K., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048846 · Cited by 48
Self-citation
Attention Performance Measured by Attention Network Test Is Correlated with Global and Regional Efficiency of Structural Brain Networks
Xiao, M., Ge, H., Khundrakpam, B. S., Xu, J., Bezgin, G., Leng, Y., Zhao, L., Tang, Y., Ge, X., Jeon, S., et al. (2016) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2016.00194 · Cited by 48
Anatomical Brain Networks on the Prediction of Abnormal Brain States
Iturria‐Medina, Y. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0122 · Cited by 51
Age of Onset of Blindness Affects Brain Anatomical Networks Constructed Using Diffusion Tensor Tractography
Li, J., Liu, Y., Qin, W., Jiang, J., Qiu, Z., Xu, J., Yu, C., & Jiang, T. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs034 · Cited by 48
Self-citation
Structural efficiency within a parieto-frontal network and cognitive differences
Pineda‐Pardo, J. A., Martínez, K., Román, F. J., & Colom, R. (2015) · Intelligence · doi:10.1016/j.intell.2015.12.002 · Cited by 48
Organizational topology of brain and its relationship to ADHD in adolescents with d‐transposition of the great arteries
Schmithorst, V. J., Panigrahy, A., Gaynor, J. W., Watson, C. G., Lee, V., Bellinger, D. C., Rivkin, M. J., & Newburger, J. W. (2016) · Brain and Behavior · doi:10.1002/brb3.504 · Cited by 46
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
Structural–functional coupling changes in temporal lobe epilepsy
Chiang, S., Stern, J. M., Engel, J., & Haneef, Z. (2015) · Brain Research · doi:10.1016/j.brainres.2015.04.052 · Cited by 48
The Structural Connectivity Pattern of the Default Mode Network and Its Association with Memory and Anxiety
Tao, Y., Liu, B., Zhang, X., Li, J., Qin, W., Yu, C., & Jiang, T. (2015) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2015.00152 · Cited by 49
Self-citation
A strong parietal hub in the small‐world network of coloured‐hearing synaesthetes during resting state EEG
Jäncke, L., & Langer, N. (2011) · Journal of Neuropsychology · doi:10.1111/j.1748-6653.2011.02004.x · Cited by 48
Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration
Khambhati, A. N., Mattar, M. G., Wymbs, N. F., Grafton, S. T., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.015 · Cited by 46
A multisample study of longitudinal changes in brain network architecture in 4–13‐year‐old children
Wierenga, L. M., van den Heuvel, M. P., Oranje, B., Giedd, J. N., Durston, S., Peper, J. S., Brown, T. T., Crone, E. A., & The Pediatric Longitudinal Imaging, N. (2017) · Human Brain Mapping · doi:10.1002/hbm.23833 · Cited by 44
Understanding Human Intelligence by Imaging the Brain
Colom, R., & Thompson, P. M. (2011) · Wiley eBooks · doi:10.1002/9781444343120.ch12 · Cited by 44
Trajectories of brain system maturation from childhood to older adulthood: Implications for lifespan cognitive functioning.
Petrican, R., Taylor, M. J., & Grady, C. L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.025 · Cited by 43
Functional organization of intrinsic connectivity networks in Chinese-chess experts
Duan, X., Long, Z., Chen, H., Liang, D., Qiu, L., Huang, X., Liu, T. C., & Gong, Q. (2014) · Brain Research · doi:10.1016/j.brainres.2014.02.033 · Cited by 45
Graph Metrics of Structural Brain Networks in Individuals with Schizophrenia and Healthy Controls: Group Differences, Relationships with Intelligence, and Genetics
Yeo, R. A., Ryman, S. G., van den Heuvel, M. P., de Reus, M. A., Jung, R. E., Pommy, J. M., Mayer, A. R., Ehrlich, S., Schulz, S. C., Morrow, E. M., et al. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000867 · Cited by 44
Connectomics in Schizophrenia: From Early Pioneers to Recent Brain Network Findings
Collin, G., Turk, E., & van den Heuvel, M. P. (2016) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2016.01.002 · Cited by 45
Novel Cortical Thickness Pattern for Accurate Detection of Alzheimer’s Disease
Zheng, W., Yao, Z., Hu, B., Gao, X., Cai, H., Moore, P. T., & Initiative, A. F. T. A. D. N. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150311 · Cited by 42
Cognitive functioning in glioma patients is related to functional connectivity measures of the non‐tumoural hemisphere
Baene, W. D., Rutten, G.-J. M., & Sitskoorn, M. M. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14535 · Cited by 43
MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning
Wang, L., Chong-yaw Wee, A., Suk, H., Tang, X., & Shen, D. G. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117295 · Cited by 41
Intelligence and uncertainty: Implications of hierarchical predictive processing for the neuroscience of cognitive ability
Euler, M. J. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.08.013 · Cited by 42
SSVEP Response Is Related to Functional Brain Network Topology Entrained by the Flickering Stimulus
Zhang, Y., Xu, P., Huang, Y.-L., Cheng, K., & Yao, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072654 · Cited by 40
Weighted network measures reveal differences between dementia types: An EEG study
Mehraram, R., Kaiser, M., Cromarty, R. A., Graziadio, S., O'Brien, J. T., Killen, A., Taylor, J., & Peraza, L. R. (2019) · Human Brain Mapping · doi:10.1002/hbm.24896 · Cited by 43
Quantitative assessment of a framework for creating anatomical brain networks via global tractography
Li, L., Rilling, J. K., Preuss, T. M., Glasser, M. F., Damen, F. W., & Hu, X. P. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.071 · Cited by 40
Decreased between‐hemisphere connectivity strength and network efficiency in geriatric depression
Li, X., Steffens, D. C., Potter, G. G., Guo, H., Song, S., & Wang, L. (2016) · Human Brain Mapping · doi:10.1002/hbm.23343 · Cited by 41
White matter maturation in the neonatal brain is predictive of school age cognitive capacities in children born very preterm
Keunen, K., Benders, M. J. N. L., Leemans, A., Stam, P. C. F.-V., Scholtens, L. H., Viergever, M. A., Kahn, R. S., Groenendaal, F., de Vries, L. S., & van den Heuvel, M. P. (2017) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.13487 · Cited by 39
Evaluating the granularity and statistical structure of lesions and behaviour in post-stroke aphasia
Zhao, Y., Halai, A. D., & Ralph, M. A. L. (2020) · Brain Communications · doi:10.1093/braincomms/fcaa062 · Cited by 41
Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer’s Disease: A Diffusion MRI Study with DTI and HARDI Models
Wang, T., Shi, F., Jin, Y., Yap, P., Chong-yaw Wee, A., Zhang, J., Yang, C., Li, X., Xiao, S., & Shen, D. G. (2016) · Neural Plasticity · doi:10.1155/2016/2947136 · Cited by 39
Comorbidity of mental and physical disorders
(2014) · Key Issues in Mental Health · doi:10.1159/isbn.978-3-318-02604-7 · Cited by 37
A clustering coefficient for complete weighted networks
McAssey, M. P., & Bijma, F. (2015) · Network Science · doi:10.1017/nws.2014.26 · Cited by 37
Identifying 22q11.2 Deletion Syndrome and Psychosis Using Resting-State Connectivity Patterns
Scariati, E., Schaer, M., Richiardi, J., Schneider, M., Debbané, M., Ville, D. V. D., & Eliez, S. (2014) · Brain Topography · doi:10.1007/s10548-014-0356-8 · Cited by 40
Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender
Pezoulas, V. C., Zervakis, M. E., Michelogiannis, S., & Klados, M. A. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00189 · Cited by 38
Making Sense of Connectivity
Hahn, A., Lanzenberger, R. R., & Kasper, S. F. (2018) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyy100 · Cited by 40
Multivariate Lesion-Behavior Mapping of General Cognitive Ability and Its Psychometric Constituents
Bowren, M. D., Adolphs, R., Bruss, J., Manzel, K. W., Corbetta, M., Tranel, D., & Boes, A. D. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1415-20.2020 · Cited by 42
Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks
Hosseini, S. M. H., & Kesler, S. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067354 · Cited by 39
Long-term reorganization of structural brain networks in a rabbit model of intrauterine growth restriction
Batallé, D., Muñoz‐Moreno, E., Arbat‐Plana, A., Illa, M., Figueras, F., Eixarch, E., & Gratacós, E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.065 · Cited by 38
Effects of Brain Parcellation on the Characterization of Topological Deterioration in Alzheimer's Disease
Wu, Z., Xu, D., Potter, T. B. H., Zhang, Y., & Initiative, T. A. D. N. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00113 · Cited by 38
Aberrant Functional Connectivity Architecture in Alzheimer’s Disease and Mild Cognitive Impairment: A Whole-Brain, Data-Driven Analysis
Zhou, B., Yao, H., Wang, P., Zhang, Z., Zhan, Y., Ma, J., Xu, K., Wang, L., An, N., Liu, Y., et al. (2015) · BioMed Research International · doi:10.1155/2015/495375 · Cited by 38
Self-citation
Less Efficient Information Transfer in Cys-Allele Carriers of DISC1: A Brain Network Study Based on Diffusion MRI
Li, Y., Liu, B., Hou, B., Qin, W., Wang, D., Yu, C., & Jiang, T. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs167 · Cited by 35
Self-citation
Heritability of Functional Connectivity in Resting State: Assessment of the Dynamic Mean, Dynamic Variance, and Static Connectivity across Networks
Barber, A. D., Hegarty, C. E., Lindquist, M. A., & Karlsgodt, K. H. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa391 · Cited by 35
Structural integrity of the corpus callosum predicts long-term transfer of fluid intelligence-related training gains in normal aging
Wolf, D. G. F., Fischer, F. U., Fesenbeckh, J., Yakushev, I. Y., Lelieveld, I. M., Scheurich, A., Schermuly, I., Zschutschke, L., & Fellgiebel, A. (2012) · Human Brain Mapping · doi:10.1002/hbm.22177 · Cited by 35
Linking Resting-State Networks in the Prefrontal Cortex to Executive Function: A Functional Near Infrared Spectroscopy Study
Zhao, J. L., Liu, J., Jiang, X., Zhou, G., Chen, G., Ding, X. P., Fu, G., & Lee, K. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00452 · Cited by 39
White matter structural network abnormalities underlie executive dysfunction in amyotrophic lateral sclerosis
Dimond, D., Ishaque, A. H., Chenji, S., Mah, D., Chen, Z., Seres, P., Beaulieu, C., & Kalra, S. (2016) · Human Brain Mapping · doi:10.1002/hbm.23452 · Cited by 36
Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders
Sun, Y., Li, J., Suckling, J., & Feng, L. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00361 · Cited by 36
Self-citation
Alterations of Functional and Structural Networks in Schizophrenia Patients with Auditory Verbal Hallucinations
Zhu, J., Wang, C., Liu, F., Qin, W., Li, J., & Zhuo, C. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00114 · Cited by 34
Self-citation
Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study
Alloza, C., Cox, S. R., Blesa, M., Redmond, P. H., Whalley, H. C., Ritchie, S. J., Maniega, S. M., Hernández, M. D. C. V., Tucker–Drob, E. M., Lawrie, S. M., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.075 · Cited by 34
Distinct Functional Connectivity Patterns Are Associated With Social and Cognitive Lifestyle Factors: Pathways to Cognitive Reserve
Fleck, J. I., Arnold, M. S., Dykstra, B., Casario, K., Douglas, E. A., & Morris, O. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00310 · Cited by 34
Selective Aberrant Functional–Structural Coupling of Multiscale Brain Networks in Subcortical Vascular Mild Cognitive Impairment
Ma, J., Liu, F., Yang, B., Xue, K., Wang, P., Zhou, J., Wang, Y., Niu, Y., & Zhang, J. (2020) · Neuroscience Bulletin · doi:10.1007/s12264-020-00580-w · Cited by 34
Test-retest reliability of white matter structural brain networks: a multiband diffusion MRI study
Zhao, T., Duan, F., Liao, X., Dai, Z., Cao, M., Yong He, A., & Shu, N. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00059 · Cited by 36
Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography
Shu, N., Liu, Y., Duan, Y., & Li, K. (2015) · BioMed Research International · doi:10.1155/2015/908917 · Cited by 35
Self-citation
Network attributes underlying intellectual giftedness in the developing brain
Ma, J., Kang, H. J., Kim, J., Jeong, H. S., Im, J. J., Namgung, E., Kim, M. J., Lee, S. L., Kim, T. D., Oh, J. K., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-11593-3 · Cited by 34
Abnormal topological organization in white matter structural networks revealed by diffusion tensor tractography in unmedicated patients with obsessive–compulsive disorder
Zhong, Z., Zhao, T., Luo, J., Guo, Z., Guo, M., Li, P., Sun, J., Yong He, A., & Li, Z. (2014) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2014.01.005 · Cited by 34
Fronto‐Parietal gray matter and white matter efficiency differentially predict intelligence in males and females
Ryman, S. G., Yeo, R. A., Witkiewitz, K. A., Vakhtin, A. A., van den Heuvel, M. P., de Reus, M. A., Flores, R. A., Wertz, C. J., & Jung, R. E. (2016) · Human Brain Mapping · doi:10.1002/hbm.23291 · Cited by 32
The graph theoretical analysis of the SSVEP harmonic response networks
Zhang, Y., Guo, D., Cheng, K., Yao, D., & Xu, P. (2015) · Cognitive Neurodynamics · doi:10.1007/s11571-015-9327-3 · Cited by 31
Quantification of changes in language-related brain areas in autism spectrum disorders using large-scale network analysis
Goch, C. J., Stieltjes, B., Henze, R., Hering, J., Poustka, L., Meinzer, H.-P., & Maier-Hein, K. H. (2014) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-014-0977-0 · Cited by 30
Abnormal synchronization of functional and structural networks in schizophrenia
Zhu, J., Qian, Y., Zhang, B., Li, X., Bai, Y., Li, X., & Yu, Y. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00175-8 · Cited by 30
Altered white matter connectivity and network organization in polymicrogyria revealed by individual gyral topology-based analysis
Im, K., Paldino, M. J., Poduri, A., Sporns, O., & Grant, P. E. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.011 · Cited by 31
Brain structural connectivity correlates with fluid intelligence in children: A DTI graph analysis
Kocevar, G., Suprano, I., Stamile, C., Hannoun, S., Fourneret, P., Revol, O., Nusbaum, F., & Sappey‐Marinier, D. (2018) · Intelligence · doi:10.1016/j.intell.2018.12.003 · Cited by 32
Linking brain network reconfiguration and intelligence: Are we there yet?
Girn, M., Mills, C., & Kalina Christoff, A. (2019) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2019.04.001 · Cited by 29
Interindividual reaction time variability is related to resting-state network topology: an electroencephalogram study
Zhou, G., Liu, P., He, J., Dong, M., Yang, X., Hou, B., von Deneen, K. M., Qin, W., & Tian, J. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2011.11.048 · Cited by 29
Self-citation
Compromised small-world efficiency of structural brain networks in schizophrenic patients and their unaffected parents
Yan, H., Tian, L., Wang, Q., Zhao, Q., Yue, W., Yan, J., Liu, B., & Zhang, D. (2015) · Neuroscience Bulletin · doi:10.1007/s12264-014-1518-0 · Cited by 29
Human navigation network: the intrinsic functional organization and behavioral relevance
Kong, X., Wang, X., Pu, Y., Huang, L., Hao, X., Zhen, Z., & Liu, J. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1243-8 · Cited by 30
A smarter brain is associated with stronger neural interaction in healthy young females: A resting EEG coherence study
Lee, T., Wu, Y., Yu, Y. W. ‐., Wu, H., & Chen, T.-J. (2011) · Intelligence · doi:10.1016/j.intell.2011.11.001 · Cited by 29
Differential Patterns of Gyral and Sulcal Morphological Changes During Normal Aging Process
Lin, H.-Y., Huang, C., Chou, K., Yang, A. C., Lo, C. Z., Tsai, S., & Lin, C. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.625931 · Cited by 29
Cognitive behavioral therapy eases orthodontic pain: EEG states and functional connectivity analysis
Wang, J., Wu, D., Shen, Y., Zhang, Y., Xu, Y., Tang, X., & Wang, R. (2015) · Oral Diseases · doi:10.1111/odi.12314 · Cited by 27
Disrupted cerebellar connectivity reduces whole‐brain network efficiency in multiple system atrophy
Lu, C., Soong, B., Wu, H., Teng, S., Wang, P., & Wu, Y. (2013) · Movement Disorders · doi:10.1002/mds.25314 · Cited by 27
The envirome and the connectome: exploring the structural noise in the human brain associated with socioeconomic deprivation
Krishnadas, R., Kim, J., McLean, J., Batty, G. D., McLean, J. S., Millar, K., Packard, C. J., & Cavanagh, J. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00722 · Cited by 27
Serotonin and the Brain's Rich Club—Association Between Molecular Genetic Variation on the TPH2 Gene and the Structural Connectome
Markett, S. A., de Reus, M. A., Reuter, M., Montag, C., Weber, B., Schoene‐Bake, J., & van den Heuvel, M. P. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw059 · Cited by 27
Graph Theoretical Analysis of Brain Network Characteristics in Brain Tumor Patients: A Systematic Review
Semmel, E. S., Quadri, T. R., & King, T. Z. (2021) · Neuropsychology Review · doi:10.1007/s11065-021-09512-5 · Cited by 26
Diabetes Mellitus and Disturbances in Brain Connectivity: A Bidirectional Relationship?
Mansur, R. B., Cha, D. S., Woldeyohannes, H. O., Soczynska, J. K., Zugman, A., Brietzke, E. M., & McIntyre, R. S. (2014) · NeuroMolecular Medicine · doi:10.1007/s12017-014-8316-8 · Cited by 27

Authors: Li, Y., Liu, Y., Li, J., Qin, W., Li, K., Yu, C., & Jiang, T.
Affiliations: Chinese Academy of Sciences (CN)
Capital Medical University (CN)
Corresponding author: Yu, Chunshui
Jiang, Tianzi
ORCID: Li, Yonghui
Liu, Yong
Li, Jun
Qin, Wen
Li, Kuncheng
Yu, Chunshui
Jiang, Tianzi
Venue: PLoS Computational Biology
Publisher: Public Library of Science (PLoS)
Published: 2009-05-29
Volume: 5
Issue: 5
Pages: e1000395
ISSN: 1553-734X (ISSN-L)
1553-7358
DOI: 10.1371/journal.pcbi.1000395
PMC: PMC2683575
OpenAlex: W2073017605
Cited by: 597
References: 81
Citations by year: 2026: 9 · 2025: 9 · 2024: 14 · 2023: 18 · 2022: 26 · 2021: 41 · 2020: 29 · 2019: 53 · 2018: 27 · 2017: 40 · 2016: 56 · 2015: 54 · 2014: 43 · 2013: 59 · 2012: 50
FWCI: 29.97
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS Computational Biology (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Figshare (submittedVersion, cc-by)
Funders: National Natural Science Foundation of China (30730035, 60675033, 30670601)
Chinese Academy of Sciences
Program for New Century Excellent Talents in University (NCET-07-0568)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords: intelligence, global efficiency, average path length, individual differences in intelligence, structural connectivity, diffusion tensor tractography, graph theory, information transmission efficiency, IQ
MeSH terms: Adolescent, Adult, Brain, Brain Mapping, Female, Humans, Intelligence, Intelligence Tests, Male, Models, Neurological, Nerve Net, Neural Pathways, Cluster Analysis, Diffusion Magnetic Resonance Imaging

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Brain Anatomical Network and Intelligence

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks