The complex hierarchical topology of EEG functional connectivity
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[1] Andrzej Rucinski,et al. Random graphs , 2006, SODA.
[2] Mario A. Parra,et al. Comparison of network analysis approaches on EEG connectivity in beta during Visual Short-term Memory binding tasks , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[3] C. Stam,et al. Opportunities and methodological challenges in EEG and MEG resting state functional brain network research , 2015, Clinical Neurophysiology.
[4] Edwin van Dellen,et al. The minimum spanning tree: An unbiased method for brain network analysis , 2015, NeuroImage.
[5] S. Boccaletti,et al. Complex network theory and the brain , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.
[6] C. Stam. Modern network science of neurological disorders , 2014, Nature Reviews Neuroscience.
[7] Jonas Richiardi,et al. Graph analysis of functional brain networks: practical issues in translational neuroscience , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.
[8] C J Stam,et al. The trees and the forest: Characterization of complex brain networks with minimum spanning trees. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[9] C. Stam,et al. Alzheimer's disease: connecting findings from graph theoretical studies of brain networks , 2013, Neurobiology of Aging.
[10] José M. F. Moura,et al. Discrete Signal Processing on Graphs , 2012, IEEE Transactions on Signal Processing.
[11] O. Sporns,et al. The economy of brain network organization , 2012, Nature Reviews Neuroscience.
[12] C. Stam,et al. The correlation of metrics in complex networks with applications in functional brain networks , 2011 .
[13] O. Sporns,et al. Rich-Club Organization of the Human Connectome , 2011, The Journal of Neuroscience.
[14] D. Long. Networks of the Brain , 2011 .
[15] Thomas E. Nichols,et al. Brain Network Analysis: Separating Cost from Topology Using Cost-Integration , 2011, PloS one.
[16] R. Oostenveld,et al. An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias , 2011, NeuroImage.
[17] Olaf Sporns,et al. Weight-conserving characterization of complex functional brain networks , 2011, NeuroImage.
[18] Robert Oostenveld,et al. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..
[19] Edward T. Bullmore,et al. Modular and Hierarchically Modular Organization of Brain Networks , 2010, Front. Neurosci..
[20] Olaf Sporns,et al. Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.
[21] E. Bullmore,et al. Behavioral / Systems / Cognitive Functional Connectivity and Brain Networks in Schizophrenia , 2010 .
[22] A. Cichocki,et al. A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG , 2010, NeuroImage.
[23] O. Sporns,et al. Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.
[24] Michael G. Neubauer,et al. Sum of squares of degrees in a graph , 2008, 0808.2234.
[25] K. Gurney,et al. Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence , 2008, PloS one.
[26] Jean-Loup Guillaume,et al. Fast unfolding of communities in large networks , 2008, 0803.0476.
[27] E. Todeva. Networks , 2007 .
[28] L. D. Costa,et al. Rich-club phenomenon across complex network hierarchies , 2007, physics/0701290.
[29] O. Sporns. Small-world connectivity, motif composition, and complexity of fractal neuronal connections. , 2006, Bio Systems.
[30] M E J Newman,et al. Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[31] C. Stam,et al. Small-world networks and functional connectivity in Alzheimer's disease. , 2006, Cerebral cortex.
[32] Madalena Costa,et al. Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[33] N. Birbaumer,et al. BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.
[34] G. Cecchi,et al. Scale-free brain functional networks. , 2003, Physical review letters.
[35] M. Newman,et al. Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.
[36] S. Bornholdt,et al. Handbook of Graphs and Networks: From the Genome to the Internet , 2003 .
[37] M. Newman,et al. Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[38] E. Ravasz,et al. Hierarchical organization in complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] M. Newman,et al. Random Graphs as Models of Networks , 2002, cond-mat/0202208.
[40] Phillip Bonacich,et al. Eigenvector-like measures of centrality for asymmetric relations , 2001, Soc. Networks.
[41] A. Barabasi,et al. Mean-field theory for scale-free random networks , 1999, cond-mat/9907068.
[42] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[43] Bruce A. Reed,et al. A Critical Point for Random Graphs with a Given Degree Sequence , 1995, Random Struct. Algorithms.
[44] G. Edelman,et al. A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[45] Claude E. Shannon,et al. The mathematical theory of communication , 1950 .
[46] J. Petersen. Die Theorie der regulären graphs , 1891 .
[47] A. OPPENHEIM.,et al. The Industrial Applications of Oxygen , 1876, Nature.
[48] Robin Wilson,et al. Modern Graph Theory , 2013 .
[49] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[50] R. Solé,et al. Information Theory of Complex Networks: On Evolution and Architectural Constraints , 2004 .
[51] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[52] A. Andrew,et al. Emergence of Scaling in Random Networks , 1999 .
[53] T. Snijders. The degree variance: An index of graph heterogeneity , 1981 .
[54] Sharon L. Milgram,et al. The Small World Problem , 1967 .