The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Heritability of “small‐world” networks in the brain: A graph theoretical analysis of resting‐state EEG functional connectivity
Open accessAbstract
Recent studies have shown that resting‐state functional networks as studied with fMRI, EEG, and MEG may be so‐called small‐world networks. We investigated to what extent the characteristic features of small‐world networks are genetically determined. To represent functional connectivity between brain areas, we measured resting EEG in 574 twins and their siblings and calculated the synchronization likelihood between each pair of electrodes. We applied a threshold to obtain a binary graph from which we calculated the clustering coefficient C (describing local interconnectedness) and average path length L (describing global interconnectedness) for each individual. Modeling of MZ and DZ twin and sibling resemblance indicated that across various frequency bands 46–89% of the individual differences in C and 37–62% of the individual differences in L are heritable. It is asserted that C, L, and a small‐world organization are viable markers of genetic differences in brain organization. Hum Brain Mapp, 2008. © 2007 Wiley‐Liss, Inc.
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Cites
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Classical twin studies and beyond
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BackgroundMethodInfluentialSelf-citationAdaptive reconfiguration of fractal small-world human brain functional networks
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How do brain tumors alter functional connectivity? A magnetoencephalography study
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Complex brain networks: graph theoretical analysis of structural and functional systems
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Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory
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Self-citationEfficiency of Functional Brain Networks and Intellectual Performance
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Self-citationSchizophrenia, neuroimaging and connectomics
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Graph-based network analysis of resting-state functional MRI
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Genetic control over the resting brain
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Network analysis of resting state EEG in the developing young brain: structure comes with maturation
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Sleep deprivation leads to a loss of functional connectivity in frontal brain regions
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Self-citationThe 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
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“Graph theoretical properties of neural networks have been studied before in healthy subjects [17-21], and in patients with brain pathology such as Alzheimer's disease (AD) [22,23], schizophrenia [24,25] and brain tumors [8].”
BackgroundSelf-citationGenetic 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-citationBrain connectivity in normally developing children and adolescents
Khundrakpam, B. S., Lewis, J. D., Zhao, L., Chouinard-Decorte, F., & Evans, A. C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.062 · Cited by 91
A Healthy Brain in a Healthy Body: Brain Network Correlates of Physical and Mental Fitness
Douw, L., Nieboer, D., van Dijk, B. W., Stam, C. J., & Twisk, J. W. R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0088202 · Cited by 57
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Metadata
- Authors
- Smit, D. J. A., Stam, C. J., Posthuma, D., Boomsma, D. I., & de Geus, E. J. C.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2007-12-06
- Volume
- 29
- Issue
- 12
- Pages
- 1368-1378
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2107612402
- Cited by
- 275
- References
- 7
- FWCI
- 4.18
- Type
- journal article
- Language
- en
- Open access
- green
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