Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches. Export

@article{citeulike:4561481, abstract = {Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics.}, author = {Pajevic, Sinisa and Plenz, Dietmar}, citeulike-article-id = {4561481}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.1000271}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19180180}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19180180}, day = {30}, doi = {10.1371/journal.pcbi.1000271}, issn = {1553-7358}, journal = {PLoS computational biology}, keywords = {avalanches, cascades, dynamical, network, neural, neuronal, pajevic\_s, plenz\_d, small-world}, month = {January}, number = {1}, pages = {e1000271+}, posted-at = {2009-06-30 21:10:32}, priority = {3}, publisher = {Public Library of Science}, title = {Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches.}, url = {http://dx.doi.org/10.1371/journal.pcbi.1000271}, volume = {5}, year = {2009} }

TY - JOUR ID - citeulike:4561481 L3 - citeulike-article-id:4561481 N2 - Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics. IS - 1 JF - PLoS computational biology SN - 1553-7358 TI - Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches. PB - Public Library of Science VL - 5 SP - e1000271 KW - avalanches KW - cascades KW - dynamical KW - network KW - neural KW - neuronal KW - pajevic_s KW - plenz_d KW - small-world AU - Pajevic, Sinisa AU - Plenz, Dietmar PY - 2009/01/30/ UR - http://dx.doi.org/10.1371/journal.pcbi.1000271 ER -