Dynamic functional connectivity. Export

@article{citeulike:1189180, abstract = {Recent studies show that anatomical and functional brain networks exhibit similar small-world properties. However, the networks that are compared often differ in what the nodes represent (e.g. sensors or brain areas), what kind of connectivity is measured, and what temporal and spatial scales are probed. Here, I review studies of large-scale connectivity and recent results from a variety of real-time recording techniques, which together suggest that an adequate description of brain organization requires a hierarchy of networks rather than the single, binary networks that are currently in vogue. Pattern analysis methods now offer a principled way for constructing such network hierarchies. As shown at the end of this review, a correspondence principle can be formulated to guide the interpretation across network levels and to relate nodes to well defined anatomical entities.}, address = {Laboratory for Human Brain Dynamics, RIKEN Brain Science Institute, 2-1 Hirosawa, Wakoshi, Saitama, Japan 351-0198.}, author = {Ioannides, Andreas A A.}, citeulike-article-id = {1189180}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.conb.2007.03.008}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/17379500}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=17379500}, citeulike-linkout-3 = {http://www.scopus.com/record/display.url?view=extended&origin=resultslist&eid=2-s2.0-34247145800}, day = {20}, doi = {10.1016/j.conb.2007.03.008}, issn = {0959-4388}, journal = {Curr Opin Neurobiol}, keywords = {dynamics, functional-connectivity}, month = {March}, posted-at = {2007-03-27 13:43:30}, priority = {4}, title = {Dynamic functional connectivity.}, url = {http://dx.doi.org/10.1016/j.conb.2007.03.008}, year = {2007} }

TY - JOUR ID - citeulike:1189180 L3 - citeulike-article-id:1189180 N2 - Recent studies show that anatomical and functional brain networks exhibit similar small-world properties. However, the networks that are compared often differ in what the nodes represent (e.g. sensors or brain areas), what kind of connectivity is measured, and what temporal and spatial scales are probed. Here, I review studies of large-scale connectivity and recent results from a variety of real-time recording techniques, which together suggest that an adequate description of brain organization requires a hierarchy of networks rather than the single, binary networks that are currently in vogue. Pattern analysis methods now offer a principled way for constructing such network hierarchies. As shown at the end of this review, a correspondence principle can be formulated to guide the interpretation across network levels and to relate nodes to well defined anatomical entities. JF - Curr Opin Neurobiol SN - 0959-4388 AD - Laboratory for Human Brain Dynamics, RIKEN Brain Science Institute, 2-1 Hirosawa, Wakoshi, Saitama, Japan 351-0198. TI - Dynamic functional connectivity. KW - dynamics KW - functional-connectivity AU - Ioannides, Andreas A PY - 2007/03/20/ UR - http://dx.doi.org/10.1016/j.conb.2007.03.008 ER -