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Efficiency and Cost of Economical Brain Functional Networks
Open accessAbstract
Brain anatomical networks are sparse, complex, and have economical small-world properties. We investigated the efficiency and cost of human brain functional networks measured using functional magnetic resonance imaging (fMRI) in a factorial design: two groups of healthy old (N = 11; mean age = 66.5 years) and healthy young (N = 15; mean age = 24.7 years) volunteers were each scanned twice in a no-task or "resting" state following placebo or a single dose of a dopamine receptor antagonist (sulpiride 400 mg). Functional connectivity between 90 cortical and subcortical regions was estimated by wavelet correlation analysis, in the frequency interval 0.06-0.11 Hz, and thresholded to construct undirected graphs. These brain functional networks were small-world and economical in the sense of providing high global and local efficiency of parallel information processing for low connection cost. Efficiency was reduced disproportionately to cost in older people, and the detrimental effects of age on efficiency were localised to frontal and temporal cortical and subcortical regions. Dopamine antagonism also impaired global and local efficiency of the network, but this effect was differentially localised and did not interact with the effect of age. Brain functional networks have economical small-world properties-supporting efficient parallel information transfer at relatively low cost-which are differently impaired by normal aging and pharmacological blockade of dopamine transmission.
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“A related measure is global efficiency, which is the inverse of path length, 60 but which has a greater relative contribution from short-distance connections. 1”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [1]
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“The total number of connections in a network can also be regarded as an estimate of the cost in establishing a particular configuration. 1”
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“Efficiency and path length are related measures (Achard & Bullmore, 2007).”
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Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · PubMed · Cited by 21,012
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471
Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J., & Wouters, E. (2015) · Gerontology · doi:10.1159/000430949 · Cited by 19,852
Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly
Kangas, M., Korpelainen, R., Vikman, I., Nyberg, L., & Jämsä, T. J. (2014) · Gerontology · doi:10.1159/000362720 · Cited by 19,007
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319
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
Strogatz, S. H. (2001) · Nature · doi:10.1038/35065725 · Cited by 8,236
Flagged first, then by citations
Research works printed but not linked: 1
- LezakMD 1995 Neuropsychological assessment New York Oxford University Press 1026
Cited by
Sorted by citations
Items 201–300 of 1,003
Age‐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
Initiative, A. D. N., Chong-yaw Wee, A., Yang, S., Yap, P., & Shen, D. G. (2015) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9408-2 · Cited by 173
Xu, P., Huang, R., Wang, J., Dam, N. T. V., Xie, T., Dong, Z.-Y., Chen, C., Gu, R., Zang, Y., Yong He, A., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.060 · Cited by 180
LSD alters dynamic integration and segregation in the human brain
Luppi, A. I., Carhart-Harris, R. L., Roseman, L., Pappas, I., Menon, D. K., & Stamatakis, E. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117653 · Cited by 165
Duan, L. F., Zhang, Y.-J., & Zhu, C.-Z. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.014 · Cited by 175
Stam, C. J. (2010) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2010.06.024 · Cited by 173
Brain network local interconnectivity loss in aging APOE -4 allele carriers
Brown, J. A., Terashima, K. H., Burggren, A. C., Ercoli, L. M., Miller, K. J., Small, G. W., & Bookheimer, S. Y. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1109038108 · Cited by 174
Emergence of a Small-World Functional Network in Cultured Neurons
Downes, J. H., Hammond, M. W., Xydas, D., Spencer, M. C., Becerra, V. M., Warwick, K., Whalley, B. J., & Nasuto, S. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002522 · Cited by 167
Brain Connectivity Analysis: A Short Survey
Lang, E. W., Tomé, A. M., Keck, I. R., Górriz, J. M., & Puntonet, C. G. (2012) · Computational Intelligence and Neuroscience · doi:10.1155/2012/412512 · Cited by 185
Double dissociation of two cognitive control networks in patients with focal brain lesions
Nomura, E. M., Gratton, C., Visser, R. M., Kayser, A. S., Pérez, F., & D’Esposito, M. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002431107 · Cited by 167
Chimera-like States in Modular Neural Networks
Hizanidis, J., Kouvaris, N. E., Zamora-López, G., Dı́az-Guilera, A., & Antonopoulos, C. G. (2016) · Scientific Reports · doi:10.1038/srep19845 · Cited by 167
Entropy and the Brain: An Overview
Keshmiri, S. (2020) · Entropy · doi:10.3390/e22090917 · Cited by 176
Deery, H. A., Paolo, R. D., Moran, C., Egan, G. F., & Jamadar, S. D. (2022) · Psychophysiology · doi:10.1111/psyp.14159 · Cited by 188
Dopamine-Dependent Architecture of Cortico-Subcortical Network Connectivity
Cole, D. M., Oei, N. Y. L., Soeter, R. P., Both, S., van Gerven, J., Rombouts, S. A. R. B., & Beckmann, C. F. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs136 · Cited by 164
Subcortical contributions to large-scale network communication
Bell, P. T., & Shine, J. M. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.036 · Cited by 168
Disrupted Functional Brain Connectome in Patients with Posttraumatic Stress Disorder
Lei, D., Li, K., Li, L., Chen, F., Huang, X., Lui, S., Li, J., Bi, F., & Gong, Q. (2015) · Radiology · doi:10.1148/radiol.15141700 · Cited by 167
Shafi, M. M., Westover, M. B., Fox, M., & Pascual‐Leone, Á. (2012) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2012.08035.x · Cited by 172
A Dynamic Core Network and Global Efficiency in the Resting Human Brain
de Pasquale, F., Penna, S. D., Sporns, O., Romani, G. L., & Corbetta, M. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv185 · Cited by 163
Chen, Z. J., Yong He, A., Rosa‐Neto, P., Gong, G., & Evans, A. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.010 · Cited by 165
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
Batallé, D., Eixarch, E., Figueras, F., Muñoz‐Moreno, E., Bargalló, N., Illa, M., Acosta‐Rojas, R., Amat‐Roldan, I., & Gratacós, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.059 · Cited by 162
Kawai, Y., Park, J., & Asada, M. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.01.002 · Cited by 173
Wang, L. Y., Li, Y., Metzak, P. D., Yong He, A., & Woodward, T. S. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.044 · Cited by 163
Redcay, E., Moran, J. M., Mavros, P. L., Tager-Flusberg, H., Gabrieli, J. D. E., & Whitfield-Gabrieli, S. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00573 · Cited by 158
Drakesmith, 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
Functional Specialization in the Human Brain Estimated By Intrinsic Hemispheric Interaction
Wang, D., Buckner, R. L., & Liu, H. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0787-14.2014 · Cited by 157
Labus, J. S., Dinov, I. D., Jiang, Z., Ashe-McNalley, C., Zamanyan, A., Shi, Y., Hong, J., Gupta, A., Tillisch, K., Ebrat, B., et al. (2013) · Pain · doi:10.1016/j.pain.2013.09.020 · Cited by 159
Dynamic brain functional connectivity modulated by resting-state networks
Di, X., & Biswal, B. B. (2013) · Brain Structure and Function · doi:10.1007/s00429-013-0634-3 · Cited by 158
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
Imaging Functional and Structural Brain Connectomics in Attention-Deficit/Hyperactivity Disorder
Cao, M., Shu, N., Cao, Q., Wang, Y., & Yong He, A. (2014) · Molecular Neurobiology · doi:10.1007/s12035-014-8685-x · Cited by 161
Network Analysis Reveals Increased Integration during Emotional and Motivational Processing
Kinnison, J., Padmala, S., Choi, J.-M., & Pessoa, L. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0821-12.2012 · Cited by 153
Ye, M., Yang, T., Qing, P., Lei, X., Qiu, J., & Liu, G. (2015) · PLoS ONE · doi:10.1371/journal.pone.0133775 · Cited by 155
Altered Anatomical Network in Early Blindness Revealed by Diffusion Tensor Tractography
Shu, N., Liu, Y., Li, J., Li, Y., Yu, C., & Jiang, T. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007228 · Cited by 153
Chennu, S., O’Connor, S., Adapa, R., Menon, D. K., & Bekinschtein, T. A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004669 · Cited by 153
Graph theoretical framework of brain networks in multiple sclerosis: a review of concepts
Fleischer, V., Radetz, A., Ciolac, D., Muthuraman, M., Gonzalez-Escamilla, G., Zipp, F., & Groppa, S. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2017.10.033 · Cited by 151
Yu, H., Zeng, F., Liu, D., Wang, J., & Liu, J. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3530922 · Cited by 150
Abnormal topological organization of structural brain networks in schizophrenia
Zhang, Y., Lin, L., Lin, C., Zhou, Y., Chou, K., Lo, C. Z., Su, T., & Jiang, T. (2012) · Schizophrenia Research · doi:10.1016/j.schres.2012.08.021 · Cited by 149
Toward Developmental Connectomics of the Human Brain
Cao, M., Huang, H., Peng, Y., Dong, Q., & Yong He, A. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00025 · Cited by 156
Connectivity brain networks based on wavelet correlation analysis in Parkinson fMRI data
Skidmore, F. M., Korenkevych, D., Liu, Y., He, G., Bullmore, E. T., & Pardalos, P. M. (2011) · Neuroscience Letters · doi:10.1016/j.neulet.2011.05.030 · Cited by 154
Self-citationYu, Q., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Rachakonda, S., He, H., Gruner, W. E., Pearlson, G. D., Kiehl, K. A., & Calhoun, V. D. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025423 · Cited by 148
Age-related changes in the central auditory system
Ouda, L., Profant, O., & Syka, J. (2015) · Cell and Tissue Research · doi:10.1007/s00441-014-2107-2 · Cited by 153
Ismail, L. E., & Karwowski, W. (2020) · IEEE Access · doi:10.1109/access.2020.3018995 · Cited by 159
Fornito, A., & Bullmore, E. T. (2010) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e328337d78d · Cited by 146
Self-citationTermenón, M., Jaillard, A. S., Delon‐Martin, C., & Achard, S. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.062 · Cited by 154
Self-citationFan, F., Liao, X., Lei, T., Zhao, T., Xia, M., Men, W., Wang, Y., Hu, M., Liu, J., Qin, S., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117581 · Cited by 156
Viol, A., Palhano-Fontes, F., Onias, H., de Araújo, D. B., & Viswanathan, G. M. (2017) · Scientific Reports · doi:10.1038/s41598-017-06854-0 · Cited by 141
Guye, M., Bartoloméi, F., & Ranjeva, J. (2008) · Current Opinion in Neurology · doi:10.1097/wco.0b013e3283065cfb · Cited by 149
Functional brain network modularity predicts response to cognitive training after brain injury
Arnemann, K. L., Chen, A. J.-W., Novakovic-Agopian, T., Gratton, C., Nomura, E. M., & D’Esposito, M. (2015) · Neurology · doi:10.1212/wnl.0000000000001476 · 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
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
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
Tuladhar, A. M., van Dijk, E., Zwiers, M. P., van Norden, A. G. W., de Laat, K. F., Shumskaya, E., Norris, D. G., & de Leeuw, F.-E. (2016) · Human Brain Mapping · doi:10.1002/hbm.23032 · Cited by 142
Pereira, J. B., Mijalkov, M., Kakaei, E., Mecocci, P., Vellas, B., Tsolaki, M., Kłoszewska, I., Soininen, H., Spenger, C., Lovestone, S., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw128 · Cited by 142
Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome
Qi, P., Ru, H., Gao, L., Zhang, X., Zhou, T., Tian, Y., Thakor, N. V., Bezerianos, A., Li, J., & Sun, Y. (2019) · Engineering · doi:10.1016/j.eng.2018.11.025 · Cited by 144
Altered network properties of the fronto-parietal network and the thalamus in impaired consciousness
Crone, J. S., Soddu, A., Höller, Y., Vanhaudenhuyse, A., Schurz, M., Bergmann, J., Schmid, E. V., Trinka, E., Laureys, S., & Kronbichler, M. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2013.12.005 · Cited by 148
Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey
Liu, J., Li, M., Pan, Y. F., Lan, W., Zheng, R., Wu, F., & Wang, J. (2017) · Complexity · doi:10.1155/2017/8362741 · Cited by 147
Reorganization of Functional Networks in Mild Cognitive Impairment
Buldú, J. M., Bajo, R., Maestú, F., Castellanos, N. P., Leyva, I., Gil, P., Sendiña–Nadal, I., Almendral, J. A., Nevado, Á., del Pozo, F., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019584 · Cited by 144
Altered Network Topologies and Hub Organization in Adults with Autism: A Resting-State fMRI Study
Itahashi, T., Yamada, T., Watanabe, H., Nakamura, M., Jimbo, D., Shioda, S., Toriizuka, K., Kato, N., & Hashimoto, R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094115 · Cited by 143
Cao, C., & Slobounov, S. (2009) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2027704 · Cited by 140
Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography
Dinh, S. T., Nickel, M. M., Tiemann, L., May, E. S., Heitmann, H., Hohn, V. D., Edenharter, G. M., Utpadel-Fischler, D., Tölle, T. R., Sauseng, P., et al. (2019) · Pain · doi:10.1097/j.pain.0000000000001666 · Cited by 173
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
Jin, C., Gao, C., Chen, C., Ma, S., Netra, R., Wang, Y., Zhang, M., & Li, D. (2011) · Neuroscience Letters · doi:10.1016/j.neulet.2011.08.017 · Cited by 136
Shu, N., Wang, X., Bi, Q., Zhao, T., & Han, Y. (2018) · Radiology · doi:10.1148/radiol.2017162696 · Cited by 135
Changes in whole-brain functional networks and memory performance in aging
Sala‐Llonch, R., Junqué, C., Arenaza‐Urquijo, E. M., Dídac Vidal-piñeiro, A., Valls‐Pedret, C., Palacios, E. M., Doménech, S., Salvà, A., Bargalló, N., & Bartrés‐Faz, D. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.04.007 · Cited by 141
Generic aspects of complexity in brain imaging data and other biological systems
Bullmore, E. T., Barnes, A., Bassett, D. S., Fornito, A., Kitzbichler, M. G., David Meunier, A., & Suckling, J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.032 · Cited by 136
Self-citationFractal connectivity of long-memory networks
Achard, S., Bassett, D. S., Meyer‐Lindenberg, A., & Bullmore, E. T. (2008) · Physical Review E · doi:10.1103/physreve.77.036104 · Cited by 133
Self-citationCole, D. M., Beckmann, C. F., Oei, N. Y. L., Both, S., van Gerven, J., & Rombouts, S. A. R. B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.034 · Cited by 134
Valencia, M., Martinerie, J. M., Dupont, S., & Chávez, M. (2008) · Physical Review E · doi:10.1103/physreve.77.050905 · Cited by 133
Parietofrontal integrity determines neural modulation associated with grasping imagery after stroke
Buch, E. R., Shanechi, A. M., Fourkas, A. D., Weber, C., Birbaumer, N., & Cohen, L. G. (2012) · Brain · doi:10.1093/brain/awr331 · Cited by 141
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
Self-citationGlobally Altered Structural Brain Network Topology in Grapheme-Color Synesthesia
Hänggi, J., Wotruba, D., & Jäncke, L. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0964-10.2011 · Cited by 132
Changes in Brain Network Efficiency and Working Memory Performance in Aging
Stanley, M. L., Simpson, S. L., Dagenbach, D., Lyday, R. G., Burdette, J. H., & Laurienti, P. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123950 · Cited by 137
Hadley, J. A., Kraguljac, N. V., White, D. M., Hoef, L. V., Tabora, J., & Lahti, A. C. (2016) · Schizophrenia · doi:10.1038/npjschz.2016.14 · Cited by 130
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
Self-citationSuo, X., Lei, D., Li, K., Chen, F., Li, F. Y., Li, L., Huang, X., Lui, S., Li, L., Kemp, G. J., et al. (2015) · Human Brain Mapping · doi:10.1002/hbm.22871 · Cited by 135
Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients
Chong-yaw Wee, A., Yap, P., Denny, K., Browndyke, J. N., Potter, G. G., Welsh-Bohmer, K. A., Wang, L., & Shen, D. G. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037828 · Cited by 125
Dídac Vidal-piñeiro, A., eValls-Pedret, C., Fernández‐Cabello, S., Arenaza‐Urquijo, E. M., Sala-Llonch, R., Solana, E., Bargalló, N., Junqué, C., Ros, E., & Bartrés‐Faz, D. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00256 · Cited by 140
Vaessen, M. J., Hofman, P. A. M., Tijssen, H. N., Aldenkamp, A. P., Jansen, J. F. A., & Backes, W. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.011 · Cited by 125
Mapping the Alzheimer’s Brain with Connectomics
Xie, T., & Yong He, A. (2012) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2011.00077 · Cited by 129
Corticocortical Evoked Potentials Reveal Projectors and Integrators in Human Brain Networks
Keller, C. J., Honey, C. J., Entz, L., Bickel, S., Groppe, D. M., Toth, E., Ulbert, I., Lado, F. A., & Mehta, A. D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4289-13.2014 · Cited by 130
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Liu, J., Zhao, L., Li, G., Xiong, S., Nan, J., Li, J., Yuan, K., von Deneen, K. M., Liang, F., Qin, W., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051250 · Cited by 128
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Metadata
- Authors
- Achard, S., & Bullmore, E.
- Affiliations
- University of Cambridge (GB)
- ORCID
- Achard, Sophie
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2007-02-02
- Volume
- 3
- Issue
- 2
- Pages
- e17
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC1794324
- OpenAlex
- W1974764791
- Cited by
- 2,553
- References
- 55
- Citations by year
- 2026: 103 · 2025: 147 · 2024: 150 · 2023: 142 · 2022: 162 · 2021: 201 · 2020: 169 · 2019: 162 · 2018: 185 · 2017: 175 · 2016: 157 · 2015: 144 · 2014: 130 · 2013: 143 · 2012: 115
- FWCI
- 26.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Wellcome Trust
- Medical Research Council
- National Institute of Mental Health
- 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, network efficiency, network cost, aging, sulpiride, dopamine receptor antagonism, functional connectivity, resting state, wavelet correlation, graph theory, frontal cortex, temporal cortex, subcortical structures
- MeSH terms
- Adult, Aged, Aging, Brain, Brain Mapping, Computer Simulation, Female, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net, Neurons, Dopamine Antagonists
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