The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease
Open accessAbstract
Recent evidence suggests that some brain areas act as hubs interconnecting distinct, functionally specialized systems. These nexuses are intriguing because of their potential role in integration and also because they may augment metabolic cascades relevant to brain disease. To identify regions of high connectivity in the human cerebral cortex, we applied a computationally efficient approach to map the degree of intrinsic functional connectivity across the brain. Analysis of two separate functional magnetic resonance imaging datasets (each n = 24) demonstrated hubs throughout heteromodal areas of association cortex. Prominent hubs were located within posterior cingulate, lateral temporal, lateral parietal, and medial/lateral prefrontal cortices. Network analysis revealed that many, but not all, hubs were located within regions previously implicated as components of the default network. A third dataset ( n = 12) demonstrated that the locations of hubs were present across passive and active task states, suggesting that they reflect a stable property of cortical network architecture. To obtain an accurate reference map, data were combined across 127 participants to yield a consensus estimate of cortical hubs. Using this consensus estimate, we explored whether the topography of hubs could explain the pattern of vulnerability in Alzheimer's disease (AD) because some models suggest that regions of high activity and metabolism accelerate pathology. Positron emission tomography amyloid imaging in AD ( n = 10) compared with older controls ( n = 29) showed high amyloid-β deposition in the locations of cortical hubs consistent with the possibility that hubs, while acting as critical way stations for information processing, may also augment the underlying pathological cascade in AD.
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.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Additionally, studies suggest that AD pathogenesis targets high-traffic hub regions in the brain, spreading from epicenters to secondary networks as the disease progresses (Buckner et al., 2009; Dai et al., 2015; Mallio et al., 2015; Stam et al., 2009; Zhou, Gennatas, Kramer, Miller, & Seeley, 2012; Zhou & Seeley, 2014).”
From Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer’s disease (2018) · cites this paper as Buckner et al., 2009
Experimental — accuracy not yet measuredIn the citing paper
“These findings add to the growing notion that disturbances in large-scale networks take center stage in determining cognitive decline. 182,183”
From Vascular Cognitive Impairment (2017) · cites this paper as [182]
In the citing paper
“In addition, the precuneus/posterior cingulate cortex (PCC), the main functional connectivity hub in the resting brain (Buckner et al., 2009), was selected as seed region (center voxel =À2, À50, 36, see Supporting Information).”
From Oxytocin effects on complex brain networks are moderated by experiences of maternal love withdrawal (2013) · cites this paper as Buckner et al., 2009
In the citing paper
“The PCC is considered a functional connectivity hub because of its high degree of connectivity with other brain regions (Buckner et al., 2009).”
From Oxytocin effects on complex brain networks are moderated by experiences of maternal love withdrawal (2013) · cites this paper as Buckner et al., 2009
In the citing paper
“Emerging evidence indicates that AD vulnerability is strongly associated with hyperconnectivity, augmented synaptic and metabolic activities, as well as functional plasticity 52 .”
From A Chronological Atlas of Natural Selection in the Human Genome during the Past Half-million Years (2015) · cites this paper as [52]
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
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 20,012
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 18,005
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
A set of measures of centrality based upon betweenness
Freeman, L. (1977) · Sociometry · doi:10.2307/3033543 · Cited by 10,557
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
Research works printed but not linked: 2
- 10.2466/pms.1966.23.2.399 · DOI · Paper page
- Ungerleider LG Mishkin M (1982) in Analysis of visual behavior, Two cortical visual systems, eds Ingle DJ Goodale MA Mansfield RJW (MIT, Cambridge, MA), pp 549–586.
Cited by
Sorted by citations
Items 101–200 of 1,024
Eigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain
Lohmann, G., Margulies, D. S., Horstmann, A., Pleger, B., Lepsien, J., Goldhahn, D., Schloegl, H., Stümvoll, M., Villringer, A., & Turner, R. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010232 · Cited by 507
Depression, Neuroimaging and Connectomics: A Selective Overview
Gong, Q., & Yong He, A. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.08.009 · Cited by 508
Functional network disruption in the degenerative dementias
Pievani, M., de Haan, W., Wu, T., Seeley, W. W., & Frisoni, G. B. (2011) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70158-2 · Cited by 481
Understanding brain networks and brain organization
Pessoa, L. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.03.005 · Cited by 464
“The prospect of simpler structure-function relationships (hence less context dependent) is discussed by Buckner and colleagues ([57], pp.”
BackgroundA cross-disorder connectome landscape of brain dysconnectivity
van den Heuvel, M. P., & Sporns, O. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0177-6 · Cited by 462
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
Human Neuroscience and the Aging Mind: A New Look at Old Problems
Reuter‐Lorenz, P. A., & Park, D. C. (2010) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbq035 · Cited by 516
Resting‐state network dysfunction in Alzheimer's disease: A systematic review and meta‐analysis
Badhwar, A., Tam, A., Dansereau, C. L., Orban, P., Hoffstaedter, F., & Bellec, P. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.03.007 · Cited by 453
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
Yan, C.-G., Craddock, R. C., Zuo, X.-N., Zang, Y.-F., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.081 · Cited by 440
Disrupted axonal fiber connectivity in schizophrenia
Zalesky, A., Fornito, A., Seal, M. L., Cocchi, L., Westin, C.-F., Bullmore, E. T., Egan, G. F., & Pantelis, C. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.08.022 · Cited by 439
Association between Functional Connectivity Hubs and Brain Networks
Tomasi, D. G., & Volkow, N. D. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq268 · Cited by 441
Decreased interhemispheric functional connectivity in autism
Anderson, J. S., Druzgal, T. J., Froehlich, A., DuBray, M. B., Lange, N., Alexander, A. L., Abildskov, T., Nielsen, J. A., Cariello, A. N., Cooperrider, J. R., et al. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq190 · Cited by 438
Network scaling effects in graph analytic studies of human resting-state fMRI data
Fornito, A. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00022 · Cited by 439
Small-world human brain networks: Perspectives and challenges
Liao, X., Vasilakos, A. V., & Yong He, A. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.03.018 · Cited by 443
Disrupted Functional Brain Connectome in Individuals at Risk for Alzheimer's Disease
Wang, J., Zuo, X., Dai, Z., Xia, M., Zhao, Z., Zhao, X., Jia, J., Han, Y., & He, Y. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.03.026 · Cited by 432
Networks of anatomical covariance
Evans, A. C. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.054 · Cited by 429
The Organization of Local and Distant Functional Connectivity in the Human Brain
Sepulcre, J., Liu, H., Talukdar, T., Martincorena, I., Yeo, B. T. T., & Buckner, R. L. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000808 · Cited by 428
Self-citationA Cortical Core for Dynamic Integration of Functional Networks in the Resting Human Brain
de Pasquale, F., Penna, S. D., Snyder, A. Z., Marzetti, L., Pizzella, V., Romani, G. L., & Corbetta, M. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.031 · Cited by 422
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
Alzheimer's disease: connecting findings from graph theoretical studies of brain networks
Tijms, B. M., Wink, A. M., de Haan, W., van der Flier, W. M., Stam, C. J., Scheltens, P., & Barkhof, F. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.02.020 · 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
Transcutaneous Vagus Nerve Stimulation Modulates Default Mode Network in Major Depressive Disorder
Fang, J., Rong, P., Yang, H., Fan, Y., Liu, J. H., Wang, H., Zhang, G., Chen, X., Shi, S. R., Wang, L., et al. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.03.025 · Cited by 416
Evidence from intrinsic activity that asymmetry of the human brain is controlled by multiple factors
Liu, H., Stufflebeam, S. M., Sepulcre, J., Hedden, T., & Buckner, R. L. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908073106 · Cited by 413
Self-citationVilleneuve, S., Rabinovici, G. D., Cohn-Sheehy, B. I., Madison, C., Ayakta, N., Ghosh, P. M., La Joie, R., Arthur-Bentil, S. K., Vogel, J. W., Marks, S. M., et al. (2015) · Brain · doi:10.1093/brain/awv112 · Cited by 408
Rashid, B., Damaraju, E., Pearlson, G. D., & Calhoun, V. D. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00897 · Cited by 412
Martin, A. D. (2015) · Psychonomic Bulletin & Review · doi:10.3758/s13423-015-0842-3 · Cited by 406
Resting-state fMRI changes in Alzheimer's disease and mild cognitive impairment
Binnewijzend, M. A. A., Schoonheim, M. M., Sanz‐Arigita, E., Wink, A. M., van der Flier, W. M., Tolboom, N., Adriaanse, S. M., Damoiseaux, J. S., Scheltens, P., van Berckel, B. N. M., et al. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.07.003 · Cited by 407
Associations and dissociations between default and self-reference networks in the human brain
Whitfield-Gabrieli, S., Moran, J. M., Nieto-Castañón, A., Triantafyllou, C., Saxe, R., & Gabrieli, J. D. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.048 · Cited by 394
Activity Dependent Degeneration Explains Hub Vulnerability in Alzheimer's Disease
de Haan, W., Mott, K. K., van Straaten, E. C. W., Scheltens, P., & Stam, C. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002582 · Cited by 400
The structure of creative cognition in the human brain
Jung, R. E. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00330 · Cited by 391
On the nature and use of models in network neuroscience
Bassett, D. S., Zurn, P., & Gold, J. I. (2018) · Nature reviews. Neuroscience · doi:10.1038/s41583-018-0038-8 · Cited by 392
Resting-State Functional MR Imaging: A New Window to the Brain
Barkhof, F., Haller, S., & Rombouts, S. A. R. B. (2014) · Radiology · doi:10.1148/radiol.14132388 · Cited by 397
Rich-club organization of the newborn human brain
Ball, G., Aljabar, P., Zebari, S., Tusor, N., Arichi, T., Merchant, N., Robinson, E. C., Ogundipe, E., Rueckert, D., Edwards, A. D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1324118111 · Cited by 360
Anticevic, A., Haut, K. M., Murray, J. D., Repovš, G., Yang, G., Diehl, C., McEwen, S. C., Bearden, C. E., Addington, J., Goodyear, B. G., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0566 · Cited by 387
Drzezga, A. E., Becker, J. A., Dijk, K. R. A. V., Sreenivasan, A., Talukdar, T., Sullivan, C., Schultz, A. P., Sepulcre, J., Putcha, D., Greve, D. N., et al. (2011) · Brain · doi:10.1093/brain/awr066 · Cited by 385
Self-citationFunctional connectivity and graph theory in preclinical Alzheimer's disease
Brier, M. R., Thomas, J., Fagan, A. M., Hassenstab, J. J., Holtzman, D. M., Benzinger, T. L. S., Morris, J. C., & Ances, B. M. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.10.081 · Cited by 394
The Default Mode Network in Autism
Padmanabhan, A., Lynch, C. J., Schaer, M., & Menon, V. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.04.004 · Cited by 396
La Joie, R., Perrotin, A., Barré, L., Hommet, C., Mézenge, F., Ibazizene, M., Camus, V., Abbas, A., Landeau, B., Guilloteau, D., et al. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2170-12.2012 · Cited by 374
Hayasaka, S., & Laurienti, P. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.051 · Cited by 380
Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity
Hillary, F. G., & Grafman, J. H. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.03.003 · Cited by 388
Krienen, F. M., Yeo, B. T. T., & Buckner, R. L. (2014) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0526 · Cited by 372
Self-citationCui, Z., & Gong, G. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.001 · Cited by 367
A tutorial in connectome analysis: Topological and spatial features of brain networks
Kaiser, M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.025 · Cited by 371
Fractionation of social brain circuits in autism spectrum disorders
Gotts, S. J., Simmons, W. K., Milbury, L. A., Wallace, G. L., Cox, R. W., & Martin, A. (2012) · Brain · doi:10.1093/brain/aws160 · Cited by 369
The inferior parietal lobule and temporoparietal junction: A network perspective
Igelström, K. M., & Graziano, M. S. A. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.01.001 · Cited by 367
Functional connectivity hubs in the human brain
Tomasi, D., & Volkow, N. D. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.024 · Cited by 367
Abnormal Functional Connectivity in Children with Attention-Deficit/Hyperactivity Disorder
Tomasi, D., & Volkow, N. D. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.11.003 · Cited by 363
Hosseini, S. M. H., Hoeft, F., & Kesler, S. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040709 · Cited by 365
The structural–functional connectome and the default mode network of the human brain
Horn, A., Ostwald, D., Reisert, M., & Blankenburg, F. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.069 · Cited by 381
Brain default-mode network dysfunction in addiction
Zhang, R., & Volkow, N. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.036 · Cited by 386
The effect of model order selection in group PICA
Abou‐Elseoud, A., Starck, T., Remes, J. J., Nikkinen, J., Tervonen, O. A., & Kiviniemi, V. J. (2010) · Human Brain Mapping · doi:10.1002/hbm.20929 · Cited by 366
High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain
Avanaki, K., Xia, J., Wan, H., Bauer, A. Q., Culver, J. P., & Wang, L. V. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1311868111 · Cited by 350
Segregated Systems of Human Brain Networks
Wig, G. S. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.09.006 · Cited by 374
Network neuroscience theory of human intelligence
Barbey, A. K. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.10.001 · Cited by 355
The Neural Career of Sensory-motor Metaphors
Desai, R. H., Binder, J. R., Conant, L. L., Mano, Q. R., & Seidenberg, M. S. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21596 · Cited by 362
Chen, X., Lu, B., & Yan, C. (2018) · Human Brain Mapping · doi:10.1002/hbm.23843 · Cited by 340
Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia
Ewers, M., Sperling, R. A., Klunk, W. E., Weiner, M. W., & Hampel, H. J. (2011) · Trends in Neurosciences · doi:10.1016/j.tins.2011.05.005 · Cited by 360
Self-citationAmyloid‐β associated cortical thinning in clinically normal elderly
Becker, J. A., Hedden, T., Carmasin, J., Maye, J., Rentz, D. M., Putcha, D., Fischl, B., Greve, D. N., Marshall, G. A., Salloway, S., et al. (2011) · Annals of Neurology · doi:10.1002/ana.22333 · Cited by 342
Self-citationStepwise 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
Self-citationDementia Resulting From Traumatic Brain Injury: What Is the Pathology?
Shively, S., Scher, A. I., Perl, D. P., & Diaz-Arrastia, R. (2012) · Archives of Neurology · doi:10.1001/archneurol.2011.3747 · Cited by 346
Di Martino, A., Zuo, X.-N., Kelly, C., Grzadzinski, R., Mennes, M., Schvarcz, A., Rodman, J., Lord, C., Castellanos, F. X., & Milham, M. P. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.02.011 · Cited by 345
Default Mode of Brain Function in Monkeys
Mantini, D., Gerits, A., Nelissen, K., Durand, J., Joly, O., Simone, L., Sawamura, H., Wardak, C., Orban, G. A., Buckner, R. L., et al. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.2318-11.2011 · Cited by 343
Self-citationAssociation of Lifetime Cognitive Engagement and Low β-Amyloid Deposition
Marks, S. M. (2012) · Archives of Neurology · doi:10.1001/archneurol.2011.2748 · Cited by 359
The cerebellum in Alzheimer’s disease: evaluating its role in cognitive decline
Jacobs, H. I. L., Hopkins, D. A., Mayrhofer, H. C., Bruner, E., van Leeuwen, F. W., Raaijmakers, W., & Schmahmann, J. D. (2017) · Brain · doi:10.1093/brain/awx194 · Cited by 349
Lehmann, M., Ghosh, P. M., Madison, C., Laforce, R., Corbetta-Rastelli, C., Weiner, M. W., Greicius, M. D., Seeley, W. W., Gorno-Tempini, M. L., Rosen, H. J., et al. (2013) · Brain · doi:10.1093/brain/aws327 · Cited by 325
Mormino, E. C., Smiljic, A., Hayenga, A. O., Onami, S. H., Greicius, M. D., Rabinovici, G. D., Janabi, M., Baker, S. L., Yen, I. V., Madison, C. M., et al. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr025 · Cited by 344
Gratton, C., Nomura, E. M., Pérez, F., & D’Esposito, M. (2012) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00222 · Cited by 353
Nielsen, J. A., Zielinski, B. A., Ferguson, M. A., Lainhart, J. E., & Anderson, J. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071275 · Cited by 339
Measuring macroscopic brain connections in vivo
Jbabdi, S., Sotiropoulos, S. N., Haber, S. N., Van Essen, D. C., & Behrens, T. E. (2015) · Nature Neuroscience · doi:10.1038/nn.4134 · Cited by 334
Schultz, A. P., Chhatwal, J. P., Hedden, T., Mormino, E. C., Hanseeuw, B. J., Sepulcre, J., Huijbers, W., LaPoint, M., Buckley, R. F., Johnson, K. A., et al. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3263-16.2017 · Cited by 330
Self-citationDefault Mode Dynamics for Global Functional Integration
Vatansever, D., Menon, D. K., Manktelow, A. E., Sahakian, B. J., & Stamatakis, E. A. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2135-15.2015 · Cited by 333
The role of the salience network in cognitive and affective deficits
Schimmelpfennig, J., Topczewski, J., Zajkowski, W. K., & Jankowiak-Siuda, K. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1133367 · Cited by 379
Jiang, L., & Zuo, X. (2015) · The Neuroscientist · doi:10.1177/1073858415595004 · Cited by 338
The functional role of the precuneus
Dadario, N. B., & Sughrue, M. E. (2023) · Brain · doi:10.1093/brain/awad181 · Cited by 339
Glerean, E., Salmi, J., Lahnakoski, J. M., Jääskeläinen, I. P., & Sams, M. (2012) · Brain Connectivity · doi:10.1089/brain.2011.0068 · Cited by 325
A common brain network links development, aging, and vulnerability to disease
Douaud, G., Groves, A. R., Tamnes, C. K., Westlye, L. T., Duff, E. P., Engvig, A., Walhovd, K. B., James, A., Gass, A., Monsch, A. U., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1410378111 · Cited by 317
NPTX2 and cognitive dysfunction in Alzheimer’s Disease
Xiao, M.-F., Xu, D., Craig, M. T., Pelkey, K. A., Chien, C.-C., Shi, Y., Zhang, J., Resnick, S., Pletnikova, O., Salmon, D., et al. (2017) · eLife · doi:10.7554/elife.23798 · Cited by 316
A Neurocomputational Model of the N400 and the P600 in Language Processing
Brouwer, H., Crocker, M. W., Venhuizen, N. J., & Hoeks, J. C. J. (2016) · Cognitive Science · doi:10.1111/cogs.12461 · Cited by 335
Imaging the default mode network in aging and dementia
Hafkemeijer, A., van der Grond, J., & Rombouts, S. A. R. B. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.07.008 · Cited by 336
Andrews-Hanna, J. R., Saxe, R., & Yarkoni, T. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.032 · Cited by 313
Self-citationSimilarity-Based Extraction of Individual Networks from Gray Matter MRI Scans
Tijms, B. M., Seriès, P., Willshaw, D. J., & Lawrie, S. M. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr221 · Cited by 304
Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment
Mito, R., Raffelt, D., Dhollander, T., Vaughan, D. N., Tournier, J.-D., Salvado, O., Brodtmann, A., Rowe, C. C., Villemagne, V. L., & Connelly, A. (2018) · Brain · doi:10.1093/brain/awx355 · Cited by 309
Yan, C., Liu, D., Yong He, A., Zou, Q., Zhu, C., Zuo, X., Long, X., & Zang, Y. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005743 · Cited by 310
Concept representation reflects multimodal abstraction: A framework for embodied semantics
Fernandino, L., Binder, J. R., Desai, R. H., Pendl, S. L., Humphries, C. J., Gross, W. L., Conant, L. L., & Seidenberg, M. S. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhv020 · Cited by 305
Suspected non-Alzheimer disease pathophysiology — concept and controversy
Jack, C. R., Knopman, D. S., Chételat, G., Dickson, D. W., Fagan, A. M., Frisoni, G. B., Jagust, W. J., Mormino, E. C., Petersen, R. C., Sperling, R. A., et al. (2016) · Nature Reviews Neurology · doi:10.1038/nrneurol.2015.251 · Cited by 313
Self-citationThe serendipitous discovery of the brain's default network
Buckner, R. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.035 · Cited by 304
Self-citationSaltmarche, A. E., Naeser, M. A., Ho, K. F., Hamblin, M. R., & Lim, L. (2017) · Photomedicine and Laser Surgery · doi:10.1089/pho.2016.4227 · Cited by 302
The Default Mode Network in Healthy Aging and Alzheimer′s Disease
Mevel, K., Chételat, G., Eustache, F., & Desgranges, B. (2011) · International Journal of Alzheimer’s Disease · doi:10.4061/2011/535816 · Cited by 302
Guye, M., Bettus, G., Bartoloméi, F., & Cozzone, P. J. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0205-z · Cited by 314
Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease
Dai, Z., Yan, C., Li, K., Wang, Z., Wang, J., Cao, M., Lin, Q., Shu, N., Xia, M., Bi, Y., et al. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu246 · Cited by 298
Default mode network connectivity in stable vs progressive mild cognitive impairment
Petrella, J. R., Sheldon, F. C., Prince, S. E., Calhoun, V. D., & Doraiswamy, P. M. (2011) · Neurology · doi:10.1212/wnl.0b013e31820af94e · Cited by 300
Mapping neuroplastic potential in brain-damaged patients
Herbet, G., Maheu, M., Costi, E., Lafargue, G., & Duffau, H. (2016) · Brain · doi:10.1093/brain/awv394 · Cited by 289
Bluhm, R., Williamson, P., Lanius, R., Théberge, J., Densmore, M., Bartha, R., Neufeld, R., & Osuch, E. (2009) · Psychiatry and Clinical Neurosciences · doi:10.1111/j.1440-1819.2009.02030.x · Cited by 294
The (in)stability of functional brain network measures across thresholds
Garrison, K. A., Scheinost, D., Finn, E. S., Shen, X., & Constable, R. T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.046 · Cited by 305
The Modulation of BOLD Variability between Cognitive States Varies by Age and Processing Speed
Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs055 · Cited by 276
Consciousness in humans and non-human animals: recent advances and future directions
Boly, M., Seth, A. K., Wilke, M., Ingmundson, P., Baars, B., Laureys, S., Edelman, D. B., & Tsuchiya, N. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00625 · Cited by 291
Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy
Bernhardt, B. C., Bonilha, L., & Gross, D. W. (2015) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2015.06.005 · Cited by 297
Task-based dynamic functional connectivity: Recent findings and open questions
González-Castillo, J., & Bandettini, P. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.006 · Cited by 304
Personality Is Reflected in the Brain's Intrinsic Functional Architecture
Adelstein, J. S., Shehzad, Z. E., Mennes, M., DeYoung, C. G., Zuo, X., Kelly, C. A. M., Margulies, D. S., Bloomfield, A., Gray, J. R., Castellanos, F. X., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027633 · Cited by 306
Metadata
- Authors
- Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A.
- Affiliations
- Harvard University (US)
- Athinoula A. Martinos Center for Biomedical Imaging (US)
- Brigham and Women's Hospital (US)
- ORCID
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2009-02-11
- Volume
- 29
- Issue
- 6
- Pages
- 1860-1873
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC2750039
- OpenAlex
- W2126650951
- Cited by
- 2,862
- References
- 91
- Citations by year
- 2026: 82 · 2025: 128 · 2024: 139 · 2023: 143 · 2022: 162 · 2021: 212 · 2020: 167 · 2019: 199 · 2018: 208 · 2017: 223 · 2016: 192 · 2015: 211 · 2014: 219 · 2013: 182 · 2012: 148
- FWCI
- 63.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Howard Hughes Medical Institute
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
- National Institute on Aging (AG021910, R01AG021910, AG-027435-S1, R01AG027435, R01AG034556)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- cortical hubs, intrinsic functional connectivity, default mode network, association cortex, posterior cingulate cortex, prefrontal cortex, parietal cortex, temporal cortex, network stability, Alzheimer's disease, amyloid-beta deposition, brain network architecture
- MeSH terms
- Adolescent, Aged, Aged, 80 and over, Alzheimer Disease, Brain Mapping, Cerebral Cortex, Female, Humans, Male, Middle Aged, Nerve Net, Neural Pathways, Young Adult
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