Clustered organization of cortical connectivity. Export

@article{citeulike:5630257, abstract = {Long-range corticocortical connectivity in mammalian brains possesses an intricate, nonrandom organization. Specifically, projections are arranged in "small-world" networks, forming clusters of cortical areas, which are closely linked among each other, but less frequently with areas in other clusters. In order to delineate the structure of cortical clusters and identify their members, we developed a computational approach based on evolutionary optimization. In different compilations of connectivity data for the cat and macaque monkey brain, the algorithm identified a small number of clusters that broadly agreed with functional cortical subdivisions. We propose a simple spatial growth model for evolving clustered connectivity, and discuss structural and functional implications of the clustered, small-world organization of cortical networks.}, author = {Hilgetag, Claus C. and Kaiser, Marcus}, citeulike-article-id = {5630257}, citeulike-linkout-0 = {http://dx.doi.org/10.1385/NI:2:3:353}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15365196}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15365196}, doi = {10.1385/NI:2:3:353}, issn = {1539-2791}, journal = {Neuroinformatics}, keywords = {connectivity, ideas, networks}, number = {3}, pages = {353--360}, posted-at = {2009-08-24 10:58:59}, priority = {2}, title = {Clustered organization of cortical connectivity.}, url = {http://dx.doi.org/10.1385/NI:2:3:353}, volume = {2}, year = {2004} }

TY - JOUR ID - citeulike:5630257 L3 - citeulike-article-id:5630257 N2 - Long-range corticocortical connectivity in mammalian brains possesses an intricate, nonrandom organization. Specifically, projections are arranged in "small-world" networks, forming clusters of cortical areas, which are closely linked among each other, but less frequently with areas in other clusters. In order to delineate the structure of cortical clusters and identify their members, we developed a computational approach based on evolutionary optimization. In different compilations of connectivity data for the cat and macaque monkey brain, the algorithm identified a small number of clusters that broadly agreed with functional cortical subdivisions. We propose a simple spatial growth model for evolving clustered connectivity, and discuss structural and functional implications of the clustered, small-world organization of cortical networks. IS - 3 JF - Neuroinformatics SN - 1539-2791 EP - 360 TI - Clustered organization of cortical connectivity. VL - 2 SP - 353 KW - connectivity KW - ideas KW - networks AU - Hilgetag, Claus AU - Kaiser, Marcus PY - 2004/// UR - http://dx.doi.org/10.1385/NI:2:3:353 ER -