The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Predicting human resting-state functional connectivity from structural connectivity
Open accessAbstract
In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks—including their spatial statistics and their persistence across time—can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed ( i ) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; ( ii ) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and ( iii ) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
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?
In the citing paper
“There is an abundance of research demonstrating a correlation between DWI-tractography connection weights and FC in adults (Hagmann et al., 2008; Hagmann et al., 2010; Honey et al., 2009).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Honey et al., 2009
In the citing paper
“Another study in healthy control subjects reported a strong relation between structural connectivity and resting state functional connectivity between regions that show a strong structural connection (23).”
From Relation Between Structural and Functional Connectivity in Major Depressive Disorder (2013) · cites this paper as [23]
In the citing paper
“This analysis, although effective in outlining the anatomical boundaries of the DMN, is unable to distinguish subtle task-related fluctuations in connectivity across various experimental conditions including, for example, lying at rest in a scanner, listening to a list of scrambled words and listening to an intact story several minutes long24–26”
From The default mode network: where the idiosyncratic self meets the shared social world (2021) · cites this paper as [24]
In the citing paper
“there is ample evidence of robust functional connectivity between brain regions that lack direct structural connections28-29, 31.”
From Evolutionarily conserved prefrontal-amygdalar dysfunction in early-life anxiety (2014) · cites this paper as [29]
In the citing paper
“fMRI-derived measures of intrinsic functional connectivity are particularly useful because they are sensitive to functional networks spanning polysynaptic circuits27-29”
From Evolutionarily conserved prefrontal-amygdalar dysfunction in early-life anxiety (2014) · cites this paper as [29]
In the citing paper
“For instance, while there is evidence for a good correlation between functional connectivity and strong short-distance connections, this is not the case for the more numerous long-distance connections (Honey et al. 2009; Adachi et al. 2012).”
From A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex (2014) · cites this paper as Honey et al. 2009
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
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
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
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Spontaneous 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
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
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
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
Self-citationSearching for a baseline: Functional imaging and the resting human brain
Gusnard, D. A., & Raichle, M. E. (2001) · Nature Reviews Neuroscience · doi:10.1038/35094500 · Cited by 3,371
Functional and effective connectivity in neuroimaging: a synthesis
Friston, K. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020107 · Cited by 2,452
Cited by
Sorted by citations
Items 101–185 of 185
Development of Human Brain Structural Networks Through Infancy and Childhood
Huang, H., Shu, N., Mishra, V., Jeon, T., Chalak, L., Wang, Z. J., Rollins, N., Gong, G., Cheng, H., Peng, Y., et al. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht335 · Cited by 223
Adachi, Y., Osada, T., Sporns, O., Watanabe, T., Matsui, T., Miyamoto, K., & Miyashita, Y. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr234 · Cited by 211
Self-citationLarge-scale topology and the default mode network in the mouse connectome
Stafford, J. M., Jarrett, B. R., Miranda-Dominguez, O., Mills, B. D., Cain, N., Mihalas, S., Lahvis, G. P., Lattal, K. M., Mitchell, S. H., David, S. V., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404346111 · Cited by 229
Relation Between Structural and Functional Connectivity in Major Depressive Disorder
de Kwaasteniet, B., Ruhe, E., Caan, M., Rive, M., Olabarriaga, S., Groefsema, M., Heesink, L., van Wingen, G., & Denys, D. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.12.024 · Cited by 229
The importance of being hierarchical
Markov, N. T., & Kennedy, H. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.12.008 · Cited by 204
Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans
Rebollo, I., Devauchelle, A.-D., Béranger, B., & Tallon-Baudry, C. (2018) · eLife · doi:10.7554/elife.33321 · Cited by 194
“With long-time scales, RSNs closely match the anatomical backbone of the brain (van den Heuvel et al., 2009; Honey et al., 2009; Shen et al., 2015).”
BackgroundSuo, C., Singh, M. F., Gates, N., Wen, W., Sachdev, P., Brodaty, H., Saigal, N., Wilson, G. C., Meiklejohn, J., Singh, N., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.19 · Cited by 212
Structural disconnections explain brain network dysfunction after stroke
Griffis, J. C., Metcalf, N. V., Corbetta, M., & Shulman, G. L. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.100 · Cited by 213
Vértes, P. E., & Bullmore, E. T. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12365 · Cited by 197
Akiki, T. J., Averill, C. L., Wrocklage, K. M., Scott, J. C., Averill, L. A., Schweinsburg, B., Alexander-Bloch, A., Martini, B., Southwick, S. M., Krystal, J. H., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.005 · Cited by 188
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
Functional connectivity of visual cortex in the blind follows retinotopic organization principles
Striem-Amit, E., Ovadia-Caro, S., Caramazza, A., Margulies, D. S., Villringer, A., & Amedi, A. (2015) · Brain · doi:10.1093/brain/awv083 · Cited by 194
Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure
Mitra, A., Kraft, A., Wright, P., Acland, B., Snyder, A. Z., Rosenthal, Z., Czerniewski, L., Bauer, A., Snyder, L., Culver, J., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.015 · Cited by 193
Structural and functional rich club organization of the brain in children and adults
Grayson, D. S., Ray, S., Carpenter, S., Iyer, S., Dias, T. G. C., Stevens, C., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0088297 · Cited by 187
Hellyer, P. J., Scott, G., Shanahan, M., Sharp, D. J., & Leech, R. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4648-14.2015 · Cited by 187
How inflammation affects the brain in depression: a review of functional and structural MRI studies
Han, K.-M., & Ham, B.-J. (2021) · Journal of Clinical Neurology · doi:10.3988/jcn.2021.17.4.503 · Cited by 187
Optimal trajectories of brain state transitions
Gu, S., Betzel, R. F., Mattar, M. G., Cieslak, M., Delio, P. R., Grafton, S. T., Pasqualetti, F., & Bassett, D. S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.003 · Cited by 183
A comprehensive study of whole-brain functional connectivity in children and young adults
Jolles, D. D., van Buchem, M. A., Crone, E. A., & Rombouts, S. A. R. B. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq104 · Cited by 181
Avery, S. N., Clauss, J. A., Winder, D. G., Woodward, N., Heckers, S., & Blackford, J. U. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.017 · Cited by 164
Identification of optimal structural connectivity using functional connectivity and neural modeling
Deco, G., McIntosh, A. R., Shen, K., Hutchison, R. M., Menon, R. S., Everling, S., Hagmann, P., & Jirsa, V. K. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4423-13.2014 · Cited by 162
Self-citationDecreased 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
“Such results implicate a possible anatomical basis for the functional disturbances observed in our sample, a hypothesis that could be tested using combined fMRI and diffusion-weighted imaging in the same participants [59].”
ResultGrayson, D. S., Bliss-Moreau, E., Machado, C. J., Bennett, J., Shen, K., Grant, K. A., Fair, D. A., & Amaral, D. G. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.005 · Cited by 172
Network structure shapes spontaneous functional connectivity dynamics
Shen, K., Hutchison, R. M., Bezgin, G., Everling, S., & McIntosh, A. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4903-14.2015 · Cited by 171
Hoffstaedter, F., Grefkes, C., Caspers, S., Roski, C., Palomero‐Gallagher, N., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2014) · Human Brain Mapping · doi:10.1002/hbm.22363 · Cited by 164
“However, it is commonly the case that strong functional connections also exist between brain regions with no direct structural connection [Honey et al., 2009].”
BackgroundEvolutionarily conserved prefrontal-amygdalar dysfunction in early-life anxiety
Birn, R. M., Shackman, A. J., Oler, J. A., Williams, L. E., McFarlin, D. R., Rogers, G. M., Shelton, S. E., Alexander, A. L., Pine, D. S., Slattery, M. J., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.46 · Cited by 159
Palva, J. M., & Palva, S. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.060 · Cited by 163
Dynamic network structure of interhemispheric coordination
Doron, K. W., Bassett, D. S., & Gazzaniga, M. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216402109 · Cited by 153
Ardesch, D. J., Scholtens, L. H., Li, L., Preuss, T. M., Rilling, J. K., & van den Heuvel, M. P. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818512116 · Cited by 152
Structural basis of large-scale functional connectivity in the mouse
Grandjean, J., Zerbi, V., Balsters, J. H., Wenderoth, N., & Rudin, M. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.0438-17.2017 · Cited by 151
Autism-Associated Promoter Variant in MET Impacts Functional and Structural Brain Networks
Rudie, J. D., Hernandez, L. M., Brown, J. A., Beck-Pancer, D., Colich, N. L., Gorrindo, P., Thompson, P. M., Geschwind, D. H., Bookheimer, S. Y., Levitt, P., et al. (2012) · Neuron · doi:10.1016/j.neuron.2012.07.010 · Cited by 142
Oxytocin׳s role in anxiety: A critical appraisal
MacDonald, K., & Feifel, D. (2014) · Brain Research · doi:10.1016/j.brainres.2014.01.025 · Cited by 139
Uehara, T., Yamasaki, T., Okamoto, T., Koike, T., Kan, S., Miyauchi, S., Kira, J.-I., & Tobimatsu, S. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht004 · Cited by 136
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
van den Heuvel, M. P., de Reus, M. A., Feldman Barrett, L., Scholtens, L. H., Coopmans, F. M. T., Schmidt, R., Preuss, T. M., Rilling, J. K., & Li, L. (2015) · Human Brain Mapping · doi:10.1002/hbm.22828 · Cited by 131
Information processing architecture of functionally defined clusters in the macaque cortex
Shen, K., Bezgin, G., Hutchison, R. M., Gati, J. S., Menon, R. S., Everling, S., & McIntosh, A. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2709-12.2012 · Cited by 123
Prefrontal connectomics: From anatomy to human imaging
Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01156-6 · Cited by 129
Harmonic brain modes: a unifying framework for linking space and time in brain dynamics
Atasoy, S., Deco, G., Kringelbach, M. L., & Pearson, J. (2018) · The Neuroscientist · doi:10.1177/1073858417728032 · Cited by 124
Ongoing physiological processes in the cerebral cortex
Leopold, D. A., & Maier, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.059 · Cited by 127
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
Self-citationComputational and dynamic models in neuroimaging
Friston, K. J., & Dolan, R. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.068 · Cited by 131
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
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
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
Turbulent-like Dynamics in the Human Brain
Deco, G., & Kringelbach, M. L. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108471 · Cited by 113
The potential of infant fMRI research and the study of early life stress as a promising exemplar
Graham, A. M., Pfeifer, J. H., Fisher, P. A., Lin, W., Gao, W., & Fair, D. A. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.09.005 · Cited by 114
Atypical network connectivity for imitation in autism spectrum disorder
Shih, P., Shen, M., Öttl, B., Keehn, B., Gaffrey, M. S., & Müller, R.-A. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.05.035 · Cited by 120
Andoh, J., Matsushita, R., & Zatorre, R. J. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2333-15.2015 · Cited by 109
Jbabdi, S., Sotiropoulos, S. N., & Behrens, T. E. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.12.004 · Cited by 107
The spatial structure of resting state connectivity stability on the scale of minutes
Gonzalez-Castillo, J., Handwerker, D. A., Robinson, M. E., Hoy, C. W., Buchanan, L. C., Saad, Z. S., & Bandettini, P. A. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00138 · Cited by 116
Kang, J., Wang, L., Yan, C., Wang, J., Liang, X., & He, Y. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.033 · Cited by 111
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
Connectivity-based parcellation of the human frontal pole with diffusion tensor imaging
Liu, H., Qin, W., Li, W., Fan, L., Wang, J., Jiang, T., & Yu, C. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4882-12.2013 · Cited by 108
Falahpour, M., Thompson, W. K., Abbott, A. E., Jahedi, A., Mulvey, M. E., Datko, M., Liu, T. T., & Müller, R.-A. (2016) · Brain Connectivity · doi:10.1089/brain.2015.0389 · Cited by 106
Kim, K., Kim, S.-W., Myung, W., Han, C. E., Fava, M., Mischoulon, D., Papakostas, G. I., Seo, S. W., Cho, H., Seong, J.-K., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-15926-0 · Cited by 107
Spontaneous Brain Activity Relates to Autonomic Arousal
Fan, J., Xu, P., Van Dam, N. T., Eilam-Stock, T., Gu, X., Luo, Y.-J., & Hof, P. R. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1172-12.2012 · Cited by 107
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
Self-citationLin, H.-Y., Tseng, W.-Y. I., Lai, M.-C., Matsuo, K., & Gau, S. S.-F. (2015) · Journal of the International Neuropsychological Society · doi:10.1017/s135561771500020x · Cited by 102
Functional connectivity and neurological recovery
Corbetta, M. (2012) · Developmental Psychobiology · doi:10.1002/dev.20507 · Cited by 96
Duncan, N. W., Wiebking, C., Tiret, B., Marjańska, M., Hayes, D. J., Lyttleton, O., Doyon, J., & Northoff, G. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060312 · Cited by 95
Transcranial magnetic stimulation (TMS) for geriatric depression
Cappon, D., den Boer, T., Jordan, C., Yu, W., Metzger, E., & Pascual-Leone, A. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101531 · Cited by 97
Naik, S., Banerjee, A., Bapi, R. S., Deco, G., & Roy, D. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.04.007 · Cited by 89
Thomason, M. E., Hect, J. L., Rauh, V. A., Trentacosta, C., Wheelock, M. D., Eggebrecht, A. T., Espinoza-Heredia, C., & Burt, S. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.017 · Cited by 94
The Motor Basis for Misophonia
Kumar, S., Dheerendra, P., Erfanian, M., Benzaquén, E., Sedley, W., Gander, P. E., Lad, M., Bamiou, D. E., & Griffiths, T. D. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.0261-21.2021 · Cited by 85
The Fine-Scale Functional Correlation of Striate Cortex in Sighted and Blind People
Butt, O. H., Benson, N. C., Datta, R., & Aguirre, G. K. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.0363-13.2013 · Cited by 84
Human functional connectivity: new tools, unresolved questions
Buckner, R. L. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1005987107 · Cited by 80
Wirsich, J., Perry, A., Ridley, B., Proix, T., Golos, M., Bénar, C., Ranjeva, J.-P., Bartolomei, F., Breakspear, M., Jirsa, V., et al. (2016) · NeuroImage: Clinical · doi:10.1016/j.nicl.2016.05.010 · Cited by 77
Cognitive and Physiologic Impacts of the Infraslow Oscillation
Watson, B. O. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00044 · Cited by 74
Enhanced functional connectivity properties of human brains during in-situ nature experience
Chen, Z., He, Y., & Yu, Y. (2016) · PeerJ · doi:10.7717/peerj.2210 · Cited by 74
“170 A small-world network is usually more efficient (Honey et al. 2009) because it is highly segregated (larger Cmean) and 171 highly integrated (shorter Lmean).”
BackgroundDong, G., Lin, X., Hu, Y., Xie, C., & Du, X. (2015) · Scientific Reports · doi:10.1038/srep09197 · Cited by 76
Balancing the Brain: Resting State Networks and Deep Brain Stimulation
Kringelbach, M. L., Green, A. L., & Aziz, T. Z. (2011) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2011.00008 · Cited by 72
Amygdala–cingulate intrinsic connectivity is associated with degree of social inhibition
Blackford, J. U., Clauss, J. A., Avery, S. N., Cowan, R. L., Benningfield, M. M., & VanDerKlok, R. M. (2014) · Biological Psychology · doi:10.1016/j.biopsycho.2014.02.003 · Cited by 67
Palva, J. M., & Palva, S. (2011) · Progress in Brain Research · doi:10.1016/b978-0-444-53839-0.00022-3 · Cited by 63
Menon, V., Cerri, D., Lee, B., Yuan, R., Lee, S.-H., & Shih, Y.-Y. I. (2023) · Nature Communications · doi:10.1038/s41467-023-36616-8 · Cited by 53
Pruett, J. R., Kandala, S., Hoertel, S., Snyder, A. Z., Elison, J. T., Nishino, T., Feczko, E., Dosenbach, N. U. F., Nardos, B., Power, J. D., et al. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.01.003 · Cited by 57
Functional network segregation is associated with attenuated tau spreading in Alzheimer's disease
Steward, A., Biel, D., Brendel, M., Dewenter, A., Roemer, S., Rubinski, A., Luan, Y., Dichgans, M., Ewers, M., Franzmeier, N., et al. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12867 · Cited by 39
Disruption of conscious access in psychosis is associated with altered structural brain connectivity
Berkovitch, L., Charles, L., Del Cul, A., Hamdani, N., Delavest, M., Sarrazin, S., Mangin, J.-F., Guevara, P., Ji, E., d'Albis, M.-A., et al. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.0945-20.2020 · Cited by 36
Yang, Y., Chattun, M. R., Yan, R., Zhao, K., Chen, Y., Zhu, R., Shi, J., Wang, X., Lu, Q., & Yao, Z. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00206-4 · Cited by 35
Optimized connectome architecture for sensory-motor integration
Worrell, J. C., Rumschlag, J., Betzel, R. F., Sporns, O., & Mišić, B. (2017) · Network Neuroscience · doi:10.1162/netn_a_00022 · Cited by 32
Self-citationLiu, Z., de Zwart, J. A., Chang, C., Duan, Q., van Gelderen, P., & Duyn, J. H. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht164 · Cited by 22
The broad edge of synchronization: Griffiths effects and collective phenomena in brain networks
Buendía, V., Villegas, P., Burioni, R., & Muñoz, M. A. (2022) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2020.0424 · Cited by 24
Dreszer, J., Grochowski, M., Lewandowska, M., Nikadon, J., Gorgol, J., Bałaj, B., Finc, K., Duch, W., Kałamała, P., Chuderski, A., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25162 · Cited by 23
Gendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20
Fetal functional imaging portrays heterogeneous development of emerging human brain networks
Jakab, A., Schwartz, E., Kasprian, G., Gruber, G. M., Prayer, D., Schöpf, V., & Langs, G. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00852 · Cited by 10
How the brain transitions from conscious to subliminal perception
Arese Lucini, F., Del Ferraro, G., Sigman, M., & Makse, H. A. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.03.047 · Cited by 3
Metadata
- Authors
- Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P.
- Affiliations
- Indiana University Bloomington (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2009-02-10
- Volume
- 106
- Issue
- 6
- Pages
- 2035-2040
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2634800
- OpenAlex
- W1850231759
- Cited by
- 3,307
- References
- 55
- Citations by year
- 2026: 162 · 2025: 209 · 2024: 197 · 2023: 190 · 2022: 252 · 2021: 223 · 2020: 229 · 2019: 196 · 2018: 230 · 2017: 196 · 2016: 184 · 2015: 203 · 2014: 211 · 2013: 201 · 2012: 146
- FWCI
- 67.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- resting-state functional connectivity, structural connectivity, cerebral cortex, indirect connections, session-to-session variability
- MeSH terms
- Brain, Brain Mapping, Cerebral Cortex, Humans, Magnetic Resonance Imaging, Models, Neurological, Neural Pathways, 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
