The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
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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From Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer’s disease (2018) · cites this paper as Achard & Bullmore, 2007
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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
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Structural inequality and temporal brain dynamics across diverse samples
Baez, S., Hernandez, H., Moguilner, S., Cuadros, J., Santamaria‐Garcia, H., Medel, V., Migeot, J., Cruzat, J., Valdes‐Sosa, P. A., Lopera, F., et al. (2024) · Clinical and Translational Medicine · doi:10.1002/ctm2.70032 · Cited by 21
Ma, C., Wang, J., Zhang, J., Chen, K., Li, X., Shu, N., Chen, Y., Liu, Z., & Zhang, Z. (2017) · Molecular Neurobiology · doi:10.1007/s12035-016-0224-5 · Cited by 21
Rössler, J., Unterassner, L., Wyss, T., Haker, H., Brugger, P., Rössler, W., & Wotruba, D. (2019) · Schizophrenia Bulletin · doi:10.1093/schbul/sby079 · Cited by 20
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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