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Efficiency of Functional Brain Networks and Intellectual Performance
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Our brain is a complex network in which information is continuously processed and transported between spatially distributed but functionally linked regions. Recent studies have shown that the functional connections of the brain network are organized in a highly efficient small-world manner, indicating a high level of local neighborhood clustering, together with the existence of more long-distance connections that ensure a high level of global communication efficiency within the overall network. Such an efficient network architecture of our functional brain raises the question of a possible association between how efficiently the regions of our brain are functionally connected and our level of intelligence. Examining the overall organization of the brain network using graph analysis, we show a strong negative association between the normalized characteristic path length lambda of the resting-state brain network and intelligence quotient (IQ). This suggests that human intellectual performance is likely to be related to how efficiently our brain integrates information between multiple brain regions. Most pronounced effects between normalized path length and IQ were found in frontal and parietal regions. Our findings indicate a strong positive association between the global efficiency of functional brain networks and intellectual performance.
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“advancements in the study of structural and functional connectomics have provided substantial evidence of distinct patterns of brain activity organization, with segregated, yet integrated modules that dynamically interact during rest and task-based activity (van den Heuvel et al. 2009; Eickhoff et al. 2011; Laird et al. 2013; Raichle 2015; Margulies et al. 2016; Basile et al. 2022a)”
From Neuroanatomical correlates of peripersonal space: bridging the gap between perception, action, emotion and social cognition (2024) · cites this paper as van den Heuvel et al. 2009
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“the medial prefrontal cortex and precuneus (among other regions) were identified as having the greatest effect on network organization and global network efficiency.”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [98]
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“Experiments examining intelligence and network topology found that a higher IQ was negatively correlated with path length but not with clustering or overall connectivity.98”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [98]
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Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
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
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
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
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
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
Efficient behavior of small-world networks
Latora, V., & Marchiori, M. (2001) · Physical Review Letters · doi:10.1103/physrevlett.87.198701 · Cited by 5,119
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
Self-citationMapping 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
Searching 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
Cited by
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Items 101–200 of 1,000
Hyperconnectivity is a fundamental response to neurological disruption.
Hillary, F. G., Román, C. A. F., Venkatesan, U. M., Rajtmajer, S. M., Bajo, R., & Castellanos, N. P. (2014) · Neuropsychology · doi:10.1037/neu0000110 · Cited by 265
Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration
Schultz, D. H., & Cole, M. W. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.0358-16.2016 · Cited by 272
Rest Is Not Idleness: Implications of the Brain’s Default Mode for Human Development and Education
Immordino-Yang, M. H., Christodoulou, J. A., & Singh, V. (2012) · Perspectives on Psychological Science · doi:10.1177/1745691612447308 · Cited by 245
A Graph Signal Processing Perspective on Functional Brain Imaging
Huang, W., Bolton, T. A. W., Medaglia, J. D., Bassett, D. S., Ribeiro, A., & Ville, D. V. D. (2018) · Proceedings of the IEEE · doi:10.1109/jproc.2018.2798928 · Cited by 247
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
Network analysis of resting state EEG in the developing young brain: structure comes with maturation
Boersma, M., Smit, D. J. A., de Bie, H. M. A., Van Baal, G. C. M., Boomsma, D. I., de Geus, E. J. C., Delemarre‐van de Waal, H. A., & Stam, C. J. (2011) · Human Brain Mapping · doi:10.1002/hbm.21030 · Cited by 235
Self-citationSchwarz, A. J., & McGonigle, J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.047 · Cited by 235
Tucker–Drob, E. M., & Briley, D. A. (2014) · Psychological Bulletin · doi:10.1037/a0035893 · Cited by 241
A dynamic network perspective of chronic pain
Farmer, M. A., Baliki, M. N., & Apkarian, A. V. (2012) · Neuroscience Letters · doi:10.1016/j.neulet.2012.05.001 · Cited by 216
The Effects of Brain Lateralization on Motor Control and Adaptation
Mutha, P. K., Haaland, K. Y., & Sainburg, R. L. (2012) · Journal of Motor Behavior · doi:10.1080/00222895.2012.747482 · Cited by 217
Assessment of system dysfunction in the brain through MRI-based connectomics
Filippi, M., van den Heuvel, M. P., Fornito, A., Yong He, A., Pol, H. E. H., Agosta, F., Comı, G., & Rocca, M. A. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70144-3 · Cited by 219
Stevens, A. A., Tappon, S. C., Garg, A., & Fair, D. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030468 · Cited by 212
Brain adaptation and alternative developmental trajectories
Johnson, M. H., Jones, E. J. H., & Gliga, T. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000073 · Cited by 213
Kapogiannis, D., Reiter, D. A., Willette, A. A., & Mattson, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.029 · Cited by 211
Sex steroids and connectivity in the human brain: A review of neuroimaging studies
Peper, J. S., van den Heuvel, M. P., Mandl, R. C. W., Pol, H. E. H., & van Honk, J. (2011) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2011.05.004 · Cited by 219
Vértes, P. E., & Bullmore, E. T. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12365 · Cited by 197
Functional brain networks related to individual differences in human intelligence at rest
Hearne, L. J., Mattingley, J. B., & Cocchi, L. (2016) · Scientific Reports · doi:10.1038/srep32328 · Cited by 217
The Neuroscience of Intelligence
Haier, R. J. (2016) · Cambridge University Press eBooks · doi:10.1017/9781316105771 · Cited by 209
Functional Interactions as Big Data in the Human Brain
Turk‐Browne, N. B. (2013) · Science · doi:10.1126/science.1238409 · Cited by 205
Disruption of Functional Connectivity of the Default-Mode Network in Alcoholism
Chanraud, S., Pitel, A., Adolf Pfefferbaum, A., & Sullivan, E. V. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq297 · Cited by 214
Jansen, A. G., Mous, S. E., White, T., Posthuma, D., & Polderman, T. J. C. (2015) · Neuropsychology Review · doi:10.1007/s11065-015-9278-9 · Cited by 184
Beaty, R. E., Kaufman, S. B., Benedek, M., Jung, R. E., Kenett, Y. N., Jauk, E., Neubauer, A. C., & Silvia, P. J. (2015) · Human Brain Mapping · doi:10.1002/hbm.23065 · Cited by 196
Memristive Ion Channel-Doped Biomembranes as Synaptic Mimics
Najem, J. S., Taylor, G. J., Weiss, R., Hasan, M. S., Rose, G. S., Schuman, C. D., Belianinov, A., Collier, C. P., & Sarles, S. A. (2018) · ACS Nano · doi:10.1021/acsnano.8b01282 · Cited by 199
The future of the human connectome
Essen, D. C. V., & Uǧurbil, K. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.032 · Cited by 197
Fronto-parietal and cingulo-opercular network integrity and cognition in health and schizophrenia
Sheffield, J. M., Repovš, G., Harms, M. P., Carter, C. S., Gold, J. M., MacDonald, A. W., Ragland, J. D., Silverstein, S. M., Godwin, D., & Barch, D. M. (2015) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2015.05.006 · Cited by 193
Brain Network Analysis: Separating Cost from Topology Using Cost-Integration
Ginestet, C. E., Nichols, T. E., Bullmore, E. T., & Simmons, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021570 · Cited by 189
Miskovic, V., Ma, X., Chou, C.-A., Fan, M., Owens, M., Sayama, H., & Gibb, B. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.06.013 · Cited by 175
Di, X., Gohel, S., Kim, E. H., & Biswal, B. B. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00493 · Cited by 193
Kambeitz, J., Kambeitz-Ilankovic, L., Cabral, C., Dwyer, D., Calhoun, V., van den Heuvel, M. P., Falkai, P., Koutsouleris, N., & Malchow, B. (2016) · Schizophrenia bulletin · doi:10.1093/schbul/sbv174 · Cited by 108
A pairwise maximum entropy model accurately describes resting-state human brain networks
Watanabe, T., Hirose, S., Wada, H., Imai, Y., Machida, T., Shirouzu, I., Konishi, S., Miyashita, Y., & Masuda, N. (2013) · Nature Communications · doi:10.1038/ncomms2388 · Cited by 186
Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley, J. B. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0485-17.2017 · Cited by 186
Verstraete, E., van den Heuvel, M. P., Veldink, J. H., Blanken, N., Mandl, R. C. W., Pol, H. E. H., & van den Berg, L. H. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013664 · Cited by 183
Toga, A. W., Clark, K. A., Thompson, P. M., Shattuck, D. W., & Horn, J. D. V. (2012) · Neurosurgery · doi:10.1227/neu.0b013e318258e9ff · Cited by 185
The effects of working memory training on functional brain network efficiency
Langer, N., von Bastian, C. C., Wirz, H., Oberauer, K., & Jäncke, L. (2013) · Cortex · doi:10.1016/j.cortex.2013.01.008 · Cited by 181
Yan, T., Wang, W., Liu, Y., Chen, K., Chen, R., & Han, Y. (2018) · Theranostics · doi:10.7150/thno.23772 · Cited by 178
Local structure-function relationships in human brain networks across the lifespan
Esfahlani, F. Z., Faskowitz, J., Slack, J., Mišić, B., & Betzel, R. F. (2022) · Nature Communications · doi:10.1038/s41467-022-29770-y · Cited by 178
Brain network connectivity assessed using graph theory in frontotemporal dementia
Agosta, F., Sala, S., Valsasina, P., Meani, A., Canu, E., Magnani, G., Cappa, S. F., Scola, E., Quatto, P., Horsfield, M. A., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e31829a33f8 · Cited by 168
Collin, G., & van den Heuvel, M. P. (2013) · The Neuroscientist · doi:10.1177/1073858413503712 · Cited by 198
Wu, K., Taki, Y., Sato, K., Hashizume, H., Sassa, Y., Takeuchi, H., Thyreau, B., Yong He, A., Evans, A. C., Li, X., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055347 · Cited by 185
Efficiency of weak brain connections support general cognitive functioning
Santarnecchi, E., Galli, G., Polizzotto, N. R., Rossi, A., & Rossi, S. (2014) · Human Brain Mapping · doi:10.1002/hbm.22495 · Cited by 175
Declining functional connectivity and changing hub locations in Alzheimer’s disease: an EEG study
Engels, M. M. A., Stam, C. J., van der Flier, W. M., Scheltens, P., de Waal, H., & van Straaten, E. C. W. (2015) · BMC Neurology · doi:10.1186/s12883-015-0400-7 · Cited by 181
Self-citationAge‐related changes in topological organization of structural brain networks in healthy individuals
Wu, K., Taki, Y., Sato, K., Kinomura, S., Goto, R., Okada, K., Kawashima, R., Yong He, A., Evans, A. C., & Fukuda, H. (2011) · Human Brain Mapping · doi:10.1002/hbm.21232 · Cited by 174
Loss of network efficiency associated with cognitive decline in chronic epilepsy
Vlooswijk, M. C. G., Vaessen, M. J., Jansen, J. F. A., de Krom, M. C. T. F. M., Majoie, M., Hofman, P. A. M., Aldenkamp, A. P., & Backes, W. H. (2011) · Neurology · doi:10.1212/wnl.0b013e31822cfc2f · Cited by 173
Stam, C. J. (2010) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2010.06.024 · Cited by 173
Self-citationKarama, S., Colom, R., Johnson, W., Deary, I. J., Haier, R. J., Waber, D. P., Lepage, C., Ganjavi, H., Jung, R. E., & Evans, A. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.016 · Cited by 178
Intact Bilateral Resting-State Networks in the Absence of the Corpus Callosum
Tyszka, J. M., Kennedy, D. P., Adolphs, R., & Paul, L. K. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1453-11.2011 · Cited by 175
Entropy and the Brain: An Overview
Keshmiri, S. (2020) · Entropy · doi:10.3390/e22090917 · Cited by 176
Brain network dynamics in high-functioning individuals with autism
Watanabe, T., & Rees, G. (2017) · Nature Communications · doi:10.1038/ncomms16048 · Cited by 165
BOLD fMRI Correlation Reflects Frequency-Specific Neuronal Correlation
Hipp, J. F., & Siegel, M. (2015) · Current Biology · doi:10.1016/j.cub.2015.03.049 · Cited by 166
Yu, M., Engels, M. M. A., Hillebrand, A., van Straaten, E. C. W., Gouw, A. A., Teunissen, C. E., van der Flier, W. M., Scheltens, P., & Stam, C. J. (2017) · Brain · doi:10.1093/brain/awx050 · Cited by 165
Self-citationDrakesmith, M., Caeyenberghs, K., Dutt, A., Lewis, G., David, A. S., & Jones, D. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.011 · Cited by 157
Dynamic reorganization of brain functional networks during cognition
Bola, M., & Sabel, B. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.057 · Cited by 162
Boersma, M., Smit, D. J. A., Boomsma, D. I., de Geus, E. J. C., de Waal, H. A. D., & Stam, C. J. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0106 · Cited by 160
Self-citationThe relation between structural and functional connectivity patterns in complex brain networks
Stam, C. J., van Straaten, E. C. W., van Dellen, E., Tewarie, P. K. B., Gong, G., Hillebrand, A., Meier, J. M., & Mieghem, P. V. (2015) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2015.02.011 · Cited by 154
Self-citationAutism As a Disorder of High Intelligence
Crespi, B. J. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00300 · Cited by 156
Structure out of chaos: Functional brain network analysis with EEG, MEG, and functional MRI
van Straaten, E. C. W., & Stam, C. J. (2012) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.10.010 · Cited by 164
Self-citationGABA and glutamate in schizophrenia: A 7 T 1H-MRS study
Marsman, A., Mandl, R. C. W., Klomp, D. W. J., Bohlken, M. M., Boer, V. O., Андрейченко, А. Е., Cahn, W., Kahn, R. S., Luijten, P. R., & Pol, H. E. H. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.10.005 · Cited by 159
Self-citationResting state functional MRI in Alzheimer's Disease
Vemuri, P., Jones, D. T., & Jack, C. R. (2012) · Alzheimer s Research & Therapy · doi:10.1186/alzrt100 · Cited by 153
Burgaleta, M., Johnson, W., Waber, D. P., Colom, R., & Karama, S. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.038 · Cited by 159
van Dellen, E., Douw, L., Baayen, J. C., Heimans, J. J., Ponten, S. C., Vandertop, W. P., Velis, D. N., Stam, C. J., & Reijneveld, J. C. (2009) · PLoS ONE · doi:10.1371/journal.pone.0008081 · Cited by 151
Self-citationMcDonough, I. M., & Nashiro, K. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00409 · Cited by 153
Miraglia, F., Vecchio, F., Bramanti, P., & Rossini, P. M. (2016) · Clinical Neurophysiology · doi:10.1016/j.clinph.2015.07.040 · Cited by 150
Cognitive decline in Parkinson’s disease: the complex picture
Biundo, R., Weis, L., & Antonini, A. (2016) · npj Parkinson s Disease · doi:10.1038/npjparkd.2016.18 · Cited by 150
Fornito, A., & Bullmore, E. T. (2010) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e328337d78d · Cited by 146
Cognition is related to resting-state small-world network topology: an magnetoencephalographic study
Douw, L., Schoonheim, M. M., Landi, D., van der Meer, M. L., Geurts, J. J. G., Reijneveld, J. C., Klein, M., & Stam, C. J. (2010) · Neuroscience · doi:10.1016/j.neuroscience.2010.11.039 · Cited by 149
Self-citationWilkins, R. W., Hodges, D. A., Laurienti, P. J., Steen, M. R., & Burdette, J. H. (2014) · Scientific Reports · doi:10.1038/srep06130 · Cited by 159
The impact of epilepsy surgery on the structural connectome and its relation to outcome
Taylor, P. N., Sinha, N., Wang, Y., Vos, S. B., de Tisi, J., Miserocchi, A., McEvoy, A. W., Winston, G. P., & Duncan, J. S. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.01.028 · Cited by 148
Graph properties of synchronized cortical networks during visual working memory maintenance
Palva, S., Monto, S., & Palva, J. M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.031 · Cited by 141
Impaired Structural Motor Connectome in Amyotrophic Lateral Sclerosis
Verstraete, E., Veldink, J. H., Mandl, R. C. W., van den Berg, L. H., & van den Heuvel, M. P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024239 · Cited by 152
Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants
Kernbach, J. M., Yeo, B. T. T., Smallwood, J., Margulies, D. S., de Schotten, M. T., Walter, H., Sabuncu, M. R., Holmes, A. J., Gramfort, A., Varoquaux, G. P., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1804876115 · Cited by 142
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
Schröter, M. S., Spoormaker, V. I., Schorer, A., Wohlschläger, A. M., Czisch, M., Kochs, E. F., Zimmer, C., Hemmer, B., Schneider, G. H., Jordan, D., et al. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.6046-11.2012 · Cited by 148
White Matter Network Abnormalities Are Associated with Cognitive Decline in Chronic Epilepsy
Vaessen, M. J., Jansen, J. F. A., Vlooswijk, M. C. G., Hofman, P. A. M., Majoie, M., Aldenkamp, A. P., & Backes, W. H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr298 · Cited by 148
The brain matures with stronger functional connectivity and decreased randomness of its network
Smit, D. J. A., Boersma, M., Schnack, H. G., Micheloyannis, S., Boomsma, D. I., Hulshoff Pol, H. E., Stam, C. J., & de Geus, E. J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036896 · Cited by 143
Self-citationImpaired functional integration in multiple sclerosis: a graph theory study
Rocca, M. A., Valsasina, P., Meani, A., Falini, A., Comı, G., & Filippi, M. (2014) · Brain Structure and Function · doi:10.1007/s00429-014-0896-4 · Cited by 150
Ozdemir, R. A., Tadayon, E., Boucher, P. O., Momi, D., Karakhanyan, K., Fox, M., Halko, M. A., Pascual‐Leone, Á., Shafi, M. M., & Santarnecchi, E. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911240117 · Cited by 145
Lim, S. I., Han, C. E., Uhlhaas, P. J., & Kaiser, M. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht333 · Cited by 154
Markett, S. A., Reuter, M., Montag, C., Voigt, G., Lachmann, B., Rudorf, S., Elger, C. E., & Weber, B. (2013) · Human Brain Mapping · doi:10.1002/hbm.22285 · Cited by 147
Monti, M. M., Lutkenhoff, E. S., Rubinov, M., Boveroux, P., Vanhaudenhuyse, A., Gosseries, O., Bruno, M., Noirhomme, Q., Boly, M., & Laureys, S. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003271 · Cited by 140
Evolving networks in the human epileptic brain
Lehnertz, K., Ansmann, G., Bialonski, S., Dickten, H., Geier, C., & Porz, S. (2013) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2013.06.009 · Cited by 135
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
Genetic control of functional brain network efficiency in children
van den Heuvel, M. P., van Soelen, I. L. C., Stam, C. J., Kahn, R. S., Boomsma, D. I., & Hulshoff Pol, H. E. (2013) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.06.007 · Cited by 127
Self-citationThe integrated information theory of consciousness: A case of mistaken identity
Merker, B., Williford, K., & Rudrauf, D. (2022) · Behavioral and Brain Sciences · doi:10.1017/s0140525x21000881 · Cited by 49
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
Efficient resting-state EEG network facilitates motor imagery performance
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Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2017) · Scientific Reports · doi:10.1038/s41598-017-15795-7 · Cited by 144
Gorges, M., Müller, H., Lulé, D. E., Pinkhardt, E. H., Ludolph, A. C., & Kassubek, J. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.12.026 · Cited by 134
Verstraete, E., Veldink, J. H., van den Berg, L. H., & van den Heuvel, M. P. (2013) · Human Brain Mapping · doi:10.1002/hbm.22258 · Cited by 132
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Lo, C. Z., Su, T.-W., Huang, C., Hung, C., Chen, W.-L., Lan, T., Lin, C., & Bullmore, E. T. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1502052112 · Cited by 125
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Metadata
- Authors
- van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E.
- Affiliations
- University Medical Center Utrecht (NL)
- Venue
- Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2009-06-10
- Volume
- 29
- Issue
- 23
- Pages
- 7619-7624
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6665421
- OpenAlex
- W2165985389
- Cited by
- 1,078
- References
- 42
- Citations by year
- 2026: 33 · 2025: 39 · 2024: 42 · 2023: 40 · 2022: 51 · 2021: 69 · 2020: 74 · 2019: 68 · 2018: 61 · 2017: 85 · 2016: 85 · 2015: 94 · 2014: 72 · 2013: 96 · 2012: 74
- FWCI
- 27.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Neuroscience (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion, other-oa)
- Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- functional brain networks, small-world networks, global efficiency, average path length, intelligence quotient, resting-state functional connectivity, graph theory, frontal cortex, parietal cortex, information integration
- MeSH terms
- Adult, Brain, Female, Humans, Intelligence, Intelligence Tests, Magnetic Resonance Imaging, Male, Neural Pathways, Cluster Analysis, Linear Models
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