The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Parcellation‐dependent small‐world brain functional networks: A resting‐state fMRI study
Open accessAbstract
Recent studies have demonstrated small‐world properties in both functional and structural brain networks that are constructed based on different parcellation approaches. However, one fundamental but vital issue of the impact of different brain parcellation schemes on the network topological architecture remains unclear. Here, we used resting‐state functional MRI (fMRI) to investigate the influences of different brain parcellation atlases on the topological organization of brain functional networks. Whole‐brain fMRI data were divided into ninety and seventy regions of interest according to two predefined anatomical atlases, respectively. Brain functional networks were constructed by thresholding the correlation matrices among the parcellated regions and further analyzed using graph theoretical approaches. Both atlas‐based brain functional networks were found to show robust small‐world properties and truncated power‐law connectivity degree distributions, which are consistent with previous brain functional and structural networks studies. However, more importantly, we found that there were significant differences in multiple topological parameters (e.g., small‐worldness and degree distribution) between the two groups of brain functional networks derived from the two atlases. This study provides quantitative evidence on how the topological organization of brain networks is affected by the different parcellation strategies applied. Hum Brain Mapp 2009. © 2008 Wiley‐Liss, Inc.
Overview
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
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
The Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051
Efficiency and Cost of Economical Brain Functional Networks
Achard, S., & Bullmore, E. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030017 · Cited by 2,553
He, Y., Chen, Z., & Evans, A. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.0141-08.2008 · Cited by 965
Self-citationAdaptive reconfiguration of fractal small-world human brain functional networks
Bassett, D. S., Meyer-Lindenberg, A., Achard, S., Duke, T., & Bullmore, E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606005103 · Cited by 814
Mapping Human Whole-Brain Structural Networks with Diffusion MRI
Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V. J., Meuli, R., & Thiran, J.-P. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000597 · Cited by 788
Studying the human brain anatomical network via diffusion-weighted MRI and graph theory
Iturria-Medina, Y., Sotero, R. C., Canales-Rodríguez, E. J., Alemán-Gómez, Y., & Melie-García, L. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.060 · Cited by 506
Three-dimensional statistical analysis of sulcal variability in the human brain
Thompson, P. M., Schwartz, C., Lin, R. T., Khan, A. A., & Toga, A. W. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-13-04261.1996 · Cited by 346
Cited by
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
Rich-club organization of the human connectome
van den Heuvel, M. P., & Sporns, O. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3539-11.2011 · Cited by 2,354
Dynamic reconfiguration of human brain networks during learning
Bassett, D. S., Wymbs, N. F., Porter, M. A., Mucha, P. J., Carlson, J. M., & Grafton, S. T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018985108 · Cited by 1,705
A whole brain fMRI atlas generated via spatially constrained spectral clustering
Craddock, R. C., James, G. A., Holtzheimer, P. E., Hu, X. P., & Mayberg, H. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.21333 · Cited by 1,636
Whole-brain anatomical networks: does the choice of nodes matter?
Zalesky, A., Fornito, A., Harding, I. H., Cocchi, L., Yücel, M., Pantelis, C., & Bullmore, E. T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.027 · Cited by 1,169
Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory
van Wijk, B. C. M., Stam, C. J., & Daffertshofer, A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013701 · Cited by 1,161
Disrupted brain connectivity networks in drug-naive, first-episode major depressive disorder
Zhang, J., Wang, J., Wu, Q., Kuang, W., Huang, X., He, Y., & Gong, Q. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.05.018 · Cited by 951
Self-citationSchizophrenia, neuroimaging and connectomics
Fornito, A., Zalesky, A., Pantelis, C., & Bullmore, E. T. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.090 · Cited by 716
Graph analysis of the human connectome: Promise, progress, and pitfalls
Fornito, A., Zalesky, A., & Breakspear, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.087 · Cited by 743
Learning-induced autonomy of sensorimotor systems
Bassett, D. S., Yang, M., Wymbs, N. F., & Grafton, S. T. (2015) · Nature Neuroscience · doi:10.1038/nn.3993 · Cited by 603
Graph-based network analysis of resting-state functional MRI
Wang, J. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00016 · Cited by 614
Self-citationBetzel, R. F., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.006 · Cited by 587
Brain hyperconnectivity in children with autism and its links to social deficits
Supekar, K., Uddin, L. Q., Khouzam, A., Phillips, J., Gaillard, W. D., Kenworthy, L. E., Yerys, B. E., Vaidya, C. J., & Menon, V. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.10.001 · Cited by 538
Cubillo, A., Halari, R., Smith, A., Taylor, E., & Rubia, K. (2012) · Cortex · doi:10.1016/j.cortex.2011.04.007 · Cited by 520
Topological organization of the human brain functional connectome across the lifespan
Cao, M., Wang, J.-H., Dai, Z.-J., Cao, X.-Y., Jiang, L.-L., Fan, F.-M., Song, X.-W., Xia, M.-R., Shu, N., Dong, Q., et al. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2013.11.004 · Cited by 440
Self-citationRobust detection of dynamic community structure in networks
Bassett, D. S., Porter, M. A., Wymbs, N. F., Grafton, S. T., Carlson, J. M., & Mucha, P. J. (2013) · Chaos: An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.4790830 · Cited by 425
Cognitive Network Neuroscience
Medaglia, J. D., Lynall, M.-E., & Bassett, D. S. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00810 · Cited by 419
Wang, J.-H., Zuo, X.-N., Gohel, S., Milham, M. P., Biswal, B. B., & He, Y. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021976 · Cited by 416
Self-citationAltered functional and structural brain network organization in autism
Rudie, J. D., Brown, J. A., Beck-Pancer, D., Hernandez, L. M., Dennis, E. L., Thompson, P. M., Bookheimer, S. Y., & Dapretto, M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2012.11.006 · Cited by 411
Exploring the network dynamics underlying brain activity during rest
Cabral, J., Kringelbach, M. L., & Deco, G. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.12.005 · Cited by 351
Task-Based Core-Periphery Organization of Human Brain Dynamics
Bassett, D. S., Wymbs, N. F., Rombach, M. P., Porter, M. A., Mucha, P. J., & Grafton, S. T. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003171 · Cited by 356
The parcellation-based connectome: limitations and extensions
de Reus, M. A., & van den Heuvel, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.053 · Cited by 282
Structural network efficiency is associated with cognitive impairment in small-vessel disease
Lawrence, A. J., Chung, A. W., Morris, R. G., Markus, H. S., & Barrick, T. R. (2014) · Neurology · doi:10.1212/wnl.0000000000000612 · Cited by 285
Development of a large-scale functional brain network during human non-rapid eye movement sleep
Spoormaker, V. I., Schröter, M. S., Gleiser, P. M., Andrade, K. C., Dresler, M., Wehrle, R., Sämann, P. G., & Czisch, M. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2015-10.2010 · Cited by 273
Liang, X., Zou, Q., He, Y., & Yang, Y. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhu316 · Cited by 261
Connectivity differences in brain networks
Zalesky, A., Cocchi, L., Fornito, A., Murray, M. M., & Bullmore, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.068 · Cited by 260
One-year test-retest reliability of intrinsic connectivity network fMRI in older adults
Guo, C. C., Kurth, F., Zhou, J., Mayer, E. A., Eickhoff, S. B., Kramer, J. H., & Seeley, W. W. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.027 · Cited by 252
Developmental Changes in Organization of Structural Brain Networks
Khundrakpam, B. S., Reid, A., Brauer, J., Carbonell, F., Lewis, J., Ameis, S., Karama, S., Lee, J., Chen, Z., Das, S., et al. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs187 · Cited by 234
Self-citationLearning and comparing functional connectomes across subjects
Varoquaux, G., & Craddock, R. C. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.007 · Cited by 233
Cao, H., Plichta, M. M., Schäfer, A., Haddad, L., Grimm, O., Schneider, M., Esslinger, C., Kirsch, P., Meyer-Lindenberg, A., & Tost, H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.013 · Cited by 227
Childhood maltreatment: altered network centrality of cingulate, precuneus, temporal pole and insula
Teicher, M. H., Anderson, C. M., Ohashi, K., & Polcari, A. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.09.016 · Cited by 202
Development Trends of White Matter Connectivity in the First Years of Life
Yap, P.-T., Fan, Y., Chen, Y., Gilmore, J. H., Lin, W., & Shen, D. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024678 · Cited by 190
Modeling the outcome of structural disconnection on resting-state functional connectivity
Cabral, J., Hugues, E., Kringelbach, M. L., & Deco, G. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.007 · Cited by 182
Decreased Functional Brain Connectivity in Adolescents with Internet Addiction
Hong, S.-B., Zalesky, A., Cocchi, L., Fornito, A., Choi, E.-J., Kim, H.-H., Suh, J.-E., Kim, C.-D., Kim, J.-W., & Yi, S.-H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057831 · Cited by 175
“Given that brain network properties are known to be sensitive to the choice of parcellation template, we investigated several alternative parcellation schemes in order to assess the reproducibility of any findings to changes in nodal definitions [45,56,57].”
MethodDai, Z., & He, Y. (2014) · Neuroscience Bulletin · doi:10.1007/s12264-013-1421-0 · Cited by 173
Self-citationIntrinsic connectomes are a predictive biomarker of remission in major depressive disorder
Korgaonkar, M. S., Goldstein-Piekarski, A. N., Fornito, A., & Williams, L. M. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0574-2 · Cited by 163
Shin, D.-J., Jung, W. H., He, Y., Wang, J., Shim, G., Byun, M. S., Jang, J. H., Kim, S. N., Lee, T. Y., Park, H. Y., et al. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.09.002 · Cited by 162
Self-citationCocchi, L., Bramati, I. E., Zalesky, A., Furukawa, E., Fontenelle, L. F., Moll, J., Tripp, G., & Mattos, P. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3272-12.2012 · Cited by 151
Abnormal small-world architecture of top-down control networks in obsessive-compulsive disorder
Zhang, T. (2011) · Journal of Psychiatry & Neuroscience · doi:10.1503/jpn.100006 · Cited by 134
Jiang, X., Shen, Y., Yao, J., Zhang, L., Xu, L., Feng, R., Cai, L., Liu, J., Chen, W., & Wang, J. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0467-9 · Cited by 120
Self-citationJung, W. H., Kang, D.-H., Kim, E., Shin, K. S., Jang, J. H., & Kwon, J. S. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.06.013 · Cited by 125
Sun, Y., Yin, Q., Fang, R., Yan, X., Wang, Y., Bezerianos, A., Tang, H., Miao, F., & Sun, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096505 · Cited by 122
Self-citationGinestet, C. E., & Simmons, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.030 · Cited by 112
Mapping putative hubs in human, chimpanzee and rhesus macaque connectomes via diffusion tractography
Li, L., Hu, X., Preuss, T. M., Glasser, M. F., Damen, F. W., Qiu, Y., & Rilling, J. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.024 · Cited by 109
Brain connectivity in normally developing children and adolescents
Khundrakpam, B. S., Lewis, J. D., Zhao, L., Chouinard-Decorte, F., & Evans, A. C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.062 · Cited by 91
Comparing connectomes across subjects and populations at different scales
Meskaldji, D. E., Fischi-Gomez, E., Griffa, A., Hagmann, P., Morgenthaler, S., & Thiran, J.-P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.084 · Cited by 77
Hosseini, S. M. H., & Kesler, S. R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.032 · Cited by 59
Hyperthermia-induced disruption of functional connectivity in the human brain network
Sun, G., Qian, S., Jiang, Q., Liu, K., Li, B., Li, M., Zhao, L., Zhou, Z., von Deneen, K. M., & Liu, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061157 · Cited by 58
Liang, X., Connelly, A., & Calamante, F. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.013 · Cited by 48
Yin, D., Liu, W., Zeljic, K., Wang, Z., Lv, Q., Fan, M., Cheng, W., & Wang, Z. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.1476-16.2016 · Cited by 43
Dong, D., Li, C., Ming, Q., Zhong, X., Zhang, X., Sun, X., Jiang, Y., Gao, Y., Wang, X., & Yao, S. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.03.030 · Cited by 26
Metadata
- Authors
- Wang, J., Wang, L., Zang, Y., Yang, H., Tang, H., Gong, Q., Chen, Z., Zhu, C., & He, Y.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2008-07-22
- Volume
- 30
- Issue
- 5
- Pages
- 1511-1523
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W1996630013
- Cited by
- 670
- References
- 10
- FWCI
- 12.50
- Type
- journal article
- Language
- en
- Open access
- bronze
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
