The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Neurophysiological Architecture of Functional Magnetic Resonance Images of Human Brain
Abstract
We investigated large-scale systems organization of the whole human brain using functional magnetic resonance imaging (fMRI) data acquired from healthy volunteers in a no-task or 'resting' state. Images were parcellated using a prior anatomical template, yielding regional mean time series for each of 90 regions (major cortical gyri and subcortical nuclei) in each subject. Significant pairwise functional connections, defined by the group mean inter-regional partial correlation matrix, were mostly either local and intrahemispheric or symmetrically interhemispheric. Low-frequency components in the time series subtended stronger inter-regional correlations than high-frequency components. Intrahemispheric connectivity was generally related to anatomical distance by an inverse square law; many symmetrical interhemispheric connections were stronger than predicted by the anatomical distance between bilaterally homologous regions. Strong interhemispheric connectivity was notably absent in data acquired from a single patient, minimally conscious following a brainstem lesion. Multivariate analysis by hierarchical clustering and multidimensional scaling consistently defined six major systems in healthy volunteers-- corresponding approximately to four neocortical lobes, medial temporal lobe and subcortical nuclei- - that could be further decomposed into anatomically and functionally plausible subsystems, e.g. dorsal and ventral divisions of occipital cortex. An undirected graph derived by thresholding the healthy group mean partial correlation matrix demonstrated local clustering or cliquishness of connectivity and short mean path length compatible with prior data on small world characteristics of non-human cortical anatomy. Functional MRI demonstrates a neurophysiological architecture of the normal human brain that is anatomically sensible, strongly symmetrical, disrupted by acute brain injury, subtended predominantly by low frequencies and consistent with a small world network topology.
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
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
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
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Common regions of the human frontal lobe recruited by diverse cognitive demands
Duncan, J., & Owen, A. M. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01633-7 · Cited by 2,498
‘What’ and ‘where’ in the human brain
Ungerleider, L. G., & Haxby, J. V. (1994) · Current Opinion in Neurobiology · doi:10.1016/0959-4388(94)90066-3 · Cited by 1,913 · cited 1×
“4) and predicted by prior anatomical and functional neuroimaging studies (McIntosh et al., 1994; Ungerleider and Haxby, 1994); and the inverse square law relating anatomical distance to intrahemispheric functional connectivity (Fig.”
BackgroundDetection of functional connectivity using temporal correlations in MR images
Hampson, M., Peterson, B. S., Skudlarski, P., Gatenby, J. C., & Gore, J. C. (2002) · Human Brain Mapping · doi:10.1002/hbm.10022 · Cited by 699
Zilles, K. (2002) · European Neuropsychopharmacology · doi:10.1016/s0924-977x(02)00108-6 · Cited by 244
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
Self-citationSpontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics
Xia, M., Wang, J., & He, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068910 · Cited by 4,106
Synchronization in complex networks
Arenas, A., Díaz-Guilera, A., Kurths, J., Moreno, Y., & Zhou, C. (2008) · Physics Reports · doi:10.1016/j.physrep.2008.09.002 · Cited by 3,713
Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhx179 · Cited by 3,657
Predicting human resting-state functional connectivity from structural connectivity
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811168106 · Cited by 3,307
Exploring the brain network: A review on resting-state fMRI functional connectivity
van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2010.03.008 · Cited by 3,326
The economy of brain network organization
Bullmore, E., & Sporns, O. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3214 · Cited by 3,284
Self-citationDynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962
Distinct brain networks for adaptive and stable task control in humans
Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., Fox, M. D., Snyder, A. Z., Vincent, J. L., Raichle, M. E., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704320104 · Cited by 2,632
Bassett, D. S., & Bullmore, E. (2006) · The Neuroscientist · doi:10.1177/1073858406293182 · Cited by 2,600
Self-citationEfficiency 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
Self-citationAchard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3874-05.2006 · Cited by 2,393
Self-citationFunctional brain networks develop from a local to distributed organization
Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000381 · Cited by 1,530
Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461
Fransson, P., & Marrelec, G. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.059 · Cited by 1,213
Emergent complex neural dynamics
Chialvo, D. R. (2010) · Nature Physics · doi:10.1038/nphys1803 · Cited by 1,165
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
Self-citationComparing 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
Modular and hierarchically modular organization of brain networks
Meunier, D., Lambiotte, R., & Bullmore, E. T. (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00200 · Cited by 1,156
Self-citationNetwork Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease
Supekar, K., Menon, V., Rubin, D., Musen, M., & Greicius, M. D. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000100 · Cited by 1,148
Efficiency of Functional Brain Networks and Intellectual Performance
van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1443-09.2009 · Cited by 1,078
Gong, G., He, Y., Concha, L., Lebel, C., Gross, D. W., Evans, A. C., & Beaulieu, C. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn102 · Cited by 1,112
Zhou, J., Greicius, M. D., Gennatas, E. D., Growdon, M. E., Jang, J. Y., Rabinovici, G. D., Kramer, J. H., Weiner, M., Miller, B. L., & Seeley, W. W. (2010) · Brain · doi:10.1093/brain/awq075 · Cited by 1,016
van den Heuvel, M. P., Mandl, R. C. W., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Human Brain Mapping · doi:10.1002/hbm.20737 · Cited by 987
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
He, Y., Chen, Z., & Evans, A. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.0141-08.2008 · Cited by 965
Adaptive 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
Self-citationDevelopment of large-scale functional brain networks in children
Supekar, K., Musen, M., & Menon, V. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000157 · Cited by 807
Age-related changes in modular organization of human brain functional networks
Meunier, D., Achard, S., Morcom, A., & Bullmore, E. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.062 · Cited by 756
Self-citationThe development of human functional brain networks
Power, J. D., Fair, D. A., Schlaggar, B. L., & Petersen, S. E. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.017 · Cited by 751
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
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
Brain Anatomical Network and Intelligence
Li, Y., Liu, Y., Li, J., Qin, W., Li, K., Yu, C., & Jiang, T. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000395 · Cited by 597
Broadband criticality of human brain network synchronization
Kitzbichler, M. G., Smith, M. L., Christensen, S. R., & Bullmore, E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000314 · Cited by 527
Self-citationUddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4465-11.2011 · Cited by 520
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
Alexander-Bloch, A. F., Gogtay, N., Meunier, D., Birn, R., Clasen, L., Lalonde, F., Lenroot, R., Giedd, J., & Bullmore, E. T. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00147 · Cited by 480
Self-citationChen, Z. J., He, Y., Rosa-Neto, P., Germann, J., & Evans, A. C. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn003 · Cited by 484
The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder
Hahamy, A., Behrmann, M., & Malach, R. (2015) · Nature Neuroscience · doi:10.1038/nn.3919 · Cited by 416
Understanding brain networks and brain organization
Pessoa, L. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.03.005 · Cited by 464
“In one study of resting-state activity [121], the pattern of co-activations between 90 regions (involving major cortical gyri and subcortical nuclei) were submitted to hierarchical clustering, which identified six major systems corresponding approximately to four cortical lobes, a medial temporal cluster, and a cluste…”
MethodUndirected graphs of frequency-dependent functional connectivity in whole brain networks
Salvador, R., Suckling, J., Schwarzbauer, C., & Bullmore, E. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1645 · Cited by 437
Self-citationAn anatomical substrate for integration among functional networks in human cortex
van den Heuvel, M. P., & Sporns, O. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2128-13.2013 · Cited by 404
Networks of anatomical covariance
Evans, A. C. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.054 · Cited by 429
Braun, U., Plichta, M. M., Esslinger, C., Sauer, C., Haddad, L., Grimm, O., Mier, D., Mohnke, S., Heinz, A., Erk, S., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.044 · Cited by 424
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex
Arslan, S., Ktena, S. I., Makropoulos, A., Robinson, E. C., Rueckert, D., & Parisot, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.014 · Cited by 374
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
The Neonatal Connectome During Preterm Brain Development
van den Heuvel, M. P., Kersbergen, K. J., de Reus, M. A., Keunen, K., Kahn, R. S., Groenendaal, F., de Vries, L. S., & Benders, M. J. N. L. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu095 · Cited by 386
At the heart of the ventral attention system: The right anterior insula
Eckert, M. A., Menon, V., Walczak, A., Ahlstrom, J., Denslow, S., Horwitz, A., & Dubno, J. R. (2009) · Human Brain Mapping · doi:10.1002/hbm.20688 · Cited by 406
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
Brain activity at rest: a multiscale hierarchical functional organization
Doucet, G., Naveau, M., Petit, L., Delcroix, N., Zago, L., Crivello, F., Jobard, G., Tzourio-Mazoyer, N., Mazoyer, B., Mellet, E., et al. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00895.2010 · Cited by 319
van den Heuvel, M., Mandl, R., Luigjes, J., & Hulshoff Pol, H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2964-08.2008 · Cited by 349
Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain
Sepulcre, J., Sabuncu, M. R., Yeo, T. B., Liu, H., & Johnson, K. A. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0759-12.2012 · Cited by 323
Small worlds inside big brains
Sporns, O., & Honey, C. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609523103 · Cited by 307
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
Ploran, E. J., Nelson, S. M., Velanova, K., Donaldson, D. I., Petersen, S. E., & Wheeler, M. E. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.3522-07.2007 · Cited by 282
“To objectively identify such areas (from other response profiles), we used hierarchical cluster analysis (Cordes et al., 2002; Salvador et al., 2005; Dosenbach et al., 2007) to classify the time course profiles in the 73 Exp1 regions of interest (ROI).”
MethodBartolomei, F., Bosma, I., Klein, M., Baayen, J. C., Reijneveld, J. C., Postma, T. J., Heimans, J. J., van Dijk, B. W., de Munck, J. C., de Jongh, A., et al. (2006) · Clinical Neurophysiology · doi:10.1016/j.clinph.2006.05.018 · Cited by 276
Temporal and spatial evolution of brain network topology during the first two years of life
Gao, W., Gilmore, J. H., Giovanello, K. S., Smith, J. K., Shen, D., Zhu, H., & Lin, W. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025278 · Cited by 272
Keller, C. J., Bickel, S., Honey, C. J., Groppe, D. M., Entz, L., Craddock, R. C., Lado, F. A., Kelly, C., Milham, M., & Mehta, A. D. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4837-12.2013 · Cited by 245
Imaging of Functional Connectivity in the Mouse Brain
White, B. R., Bauer, A. Q., Snyder, A. Z., Schlaggar, B. L., Lee, J.-M., & Culver, J. P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016322 · Cited by 253
Learning and comparing functional connectomes across subjects
Varoquaux, G., & Craddock, R. C. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.007 · Cited by 233
Brain anatomical networks in early human brain development
Fan, Y., Shi, F., Smith, J. K., Lin, W., Gilmore, J. H., & Shen, D. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.025 · Cited by 225
Functional Coupling of the Amygdala in Depressed Patients Treated with Antidepressant Medication
Chen, C.-H., Suckling, J., Ooi, C., Fu, C. H. Y., Williams, S. C. R., Walsh, N. D., Mitterschiffthaler, M. T., Pich, E. M., & Bullmore, E. (2008) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301593 · Cited by 224
Self-citationA simple view of the brain through a frequency-specific functional connectivity measure
Salvador, R., Martínez, A., Pomarol-Clotet, E., Gomar, J., Vila, F., Sarró, S., Capdevila, A., & Bullmore, E. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.018 · Cited by 225
Self-citationAnand, A., Li, Y., Wang, Y., Gardner, K., & Lowe, M. J. (2007) · The Journal of Neuropsychiatry and Clinical Neurosciences · doi:10.1176/appi.neuropsych.19.3.274 · Cited by 215
Disrupted Small-World Brain Networks in Moderate Alzheimer's Disease: A Resting-State fMRI Study
Zhao, X., Liu, Y., Wang, X., Liu, B., Xi, Q., Guo, Q., Jiang, H., Jiang, T., & Wang, P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033540 · Cited by 215
Development of global cortical networks in early infancy
Homae, F., Watanabe, H., Otobe, T., Nakano, T., Go, T., Konishi, Y., & Taga, G. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5618-09.2010 · Cited by 206
Mapping the mouse brain with rs-fMRI: an optimized pipeline for functional network identification
Zerbi, V., Grandjean, J., Rudin, M., & Wenderoth, N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.090 · Cited by 178
Functional disconnectivity of the medial temporal lobe in Asperger's syndrome
Welchew, D. E., Ashwin, C., Berkouk, K., Salvador, R., Suckling, J., Baron-Cohen, S., & Bullmore, E. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.01.028 · Cited by 207
Self-citationAtypically diffuse functional connectivity between caudate nuclei and cerebral cortex in autism
Turner, K. C., Frost, L., Linsenbardt, D., McIlroy, J. R., & Müller, R.-A. (2006) · Behavioral and Brain Functions · doi:10.1186/1744-9081-2-34 · Cited by 207
Partially enhanced thalamocortical functional connectivity in autism
Mizuno, A., Villalobos, M. E., Davies, M. M., Dahl, B. C., & Müller, R.-A. (2006) · Brain Research · doi:10.1016/j.brainres.2006.05.064 · Cited by 206
Discrete neuroanatomical networks are associated with specific cognitive abilities in old age
Wen, W., Zhu, W., He, Y., Kochan, N. A., Reppermund, S., Slavin, M. J., Brodaty, H., Crawford, J., Xia, A., & Sachdev, P. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4085-10.2011 · Cited by 204
From maps to multi-dimensional network mechanisms of mental disorders
Braun, U., Schaefer, A., Betzel, R. F., Tost, H., Meyer-Lindenberg, A., & Bassett, D. S. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.007 · Cited by 177
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
Consistency-based thresholding of the human connectome
Roberts, J. A., Perry, A., Roberts, G., Mitchell, P. B., & Breakspear, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.053 · Cited by 189
How do brain tumors alter functional connectivity? A magnetoencephalography study
Bartolomei, F., Bosma, I., Klein, M., Baayen, J. C., Reijneveld, J. C., Postma, T. J., Heimans, J. J., van Dijk, B. W., de Munck, J. C., de Jongh, A., et al. (2006) · Annals of Neurology · doi:10.1002/ana.20710 · Cited by 180
Changes in Community Structure of Resting State Functional Connectivity in Unipolar Depression
Lord, A., Horn, D., Breakspear, M., & Walter, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041282 · Cited by 174
Dai, Z., & He, Y. (2014) · Neuroscience Bulletin · doi:10.1007/s12264-013-1421-0 · Cited by 173
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
Cocchi, 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
EEG functional connectivity is partially predicted by underlying white matter connectivity
Chu, C. J., Tanaka, N., Diaz, J., Edlow, B. L., Wu, O., Hämäläinen, M., Stufflebeam, S., Cash, S. S., & Kramer, M. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.033 · Cited by 135
Miranda-Dominguez, O., Mills, B. D., Grayson, D., Woodall, A., Grant, K. A., Kroenke, C. D., & Fair, D. A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.4229-13.2014 · Cited by 130
Eckert, M. A., Kamdar, N. V., Chang, C. E., Beckmann, C. F., Greicius, M. D., & Menon, V. (2008) · Human Brain Mapping · doi:10.1002/hbm.20560 · Cited by 138
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
Altered Functional and Structural Connectivity Networks in Psychogenic Non-Epileptic Seizures
Ding, J.-R., An, D., Liao, W., Li, J., Wu, G.-R., Xu, Q., Long, Z., Gong, Q., Zhou, D., Sporns, O., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063850 · Cited by 132
A Bayesian approach to determining connectivity of the human brain
Patel, R. S., Bowman, F. D., & Rilling, J. K. (2006) · Human Brain Mapping · doi:10.1002/hbm.20182 · Cited by 127
Han, K., Mac Donald, C. L., Johnson, A. M., Barnes, Y., Wierzechowski, L., Zonies, D., Oh, J., Flaherty, S., Fang, R., Raichle, M. E., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.017 · Cited by 123
Gavrilescu, M., Rossell, S., Stuart, G. W., Shea, T. L., Innes-Brown, H., Henshall, K., McKay, C., Sergejew, A. A., Copolov, D., & Egan, G. F. (2010) · Psychological Medicine · doi:10.1017/s0033291709991632 · Cited by 121
Ginestet, C. E., & Simmons, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.030 · Cited by 112
Imaging transcriptomics of brain disorders
Arnatkeviciute, A., Fulcher, B. D., Bellgrove, M. A., & Fornito, A. (2022) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2021.10.002 · Cited by 113
MR connectomics: a conceptual framework for studying the developing brain
Hagmann, P., Grant, P. E., & Fair, D. A. (2012) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00043 · Cited by 96
Disrupted brain connectome in semantic variant of primary progressive aphasia
Agosta, F., Galantucci, S., Valsasina, P., Canu, E., Meani, A., Marcone, A., Magnani, G., Falini, A., Comi, G., & Filippi, M. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.05.017 · Cited by 94
Domínguez-Iturza, N., Lo, A. C., Shah, D., Armendáriz, M., Vannelli, A., Mercaldo, V., Trusel, M., Li, K. W., Gastaldo, D., Santos, A. R., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11203-y · Cited by 96
Castellanos, F. X., Kelly, C., & Milham, M. P. (2009) · The Canadian Journal of Psychiatry · doi:10.1177/070674370905401003 · Cited by 88
Spoormaker, V. I., Gleiser, P. M., & Czisch, M. (2012) · Frontiers in Neurology · doi:10.3389/fneur.2012.00080 · Cited by 83
Graph theoretical analysis of developmental patterns of the white matter network
Chen, Z., Liu, M., Gross, D. W., & Beaulieu, C. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00716 · Cited by 77
Development of cortical anatomical properties from early childhood to early adulthood
Nie, J., Li, G., & Shen, D. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.021 · Cited by 70
Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA
Mandelli, M. L., Welch, A. E., Vilaplana, E., Watson, C., Battistella, G., Brown, J. A., Possin, K. L., Hubbard, H. I., Miller, Z. A., Henry, M. L., et al. (2018) · Cortex · doi:10.1016/j.cortex.2018.08.002 · Cited by 67
Parr, A. C., Calabro, F., Larsen, B., Tervo-Clemmens, B., Elliot, S., Foran, W., Olafsson, V., & Luna, B. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.101997 · Cited by 60
Metadata
- Authors
- Salvador, R., Suckling, J., Coleman, M. R., Pickard, J. D., Menon, D., & Bullmore, E.
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-01-05
- Volume
- 15
- Issue
- 9
- Pages
- 1332-1342
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2129109788
- Cited by
- 1,344
- References
- 7
- FWCI
- 20.70
- Type
- journal article
- Language
- en
- Open access
- closed
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.
