Complex brain networks: graph theoretical analysis of structural and functional systems. Export

@article{citeulike:4025955, abstract = {Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.}, author = {Bullmore, Ed and Sporns, Olaf}, citeulike-article-id = {4025955}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nrn2575}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nrn2575}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/19190637}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=19190637}, doi = {10.1038/nrn2575}, issn = {1471-0048}, journal = {Nature reviews. Neuroscience}, keywords = {review, small-world}, month = {March}, number = {3}, pages = {186--198}, posted-at = {2009-05-28 15:32:38}, priority = {2}, publisher = {Nature Publishing Group}, title = {Complex brain networks: graph theoretical analysis of structural and functional systems.}, url = {http://dx.doi.org/10.1038/nrn2575}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:4025955 L3 - citeulike-article-id:4025955 N2 - Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field. IS - 3 JF - Nature reviews. Neuroscience SN - 1471-0048 EP - 198 TI - Complex brain networks: graph theoretical analysis of structural and functional systems. PB - Nature Publishing Group VL - 10 SP - 186 KW - review KW - small-world AU - Bullmore, Ed AU - Sporns, Olaf PY - 2009/03/04/ UR - http://dx.doi.org/10.1038/nrn2575 ER -