title: Recurrence network analysis of the synchronous EEG time series in normal and epileptic brains.
abstract: We sought to analyze the dynamic properties of brain electrical activity from healthy volunteers and epilepsy patients using recurrence networks. Phase-space trajectories of synchronous electroencephalogram signals were obtained through embedding dimension in phase-space reconstruction based on the distance set of space points. The recurrence matrix calculated from phase-space trajectories was identified with the adjacency matrix of a complex network. Then, we applied measures to characterize the complex network to this recurrence network. A detailed analysis revealed the following: (1) The recurrence networks of normal brains exhibited a sparser connectivity and smaller clustering coefficient compared with that of epileptic brains; (2) the small-world property existed in both normal and epileptic brains consistent with the previous empirical studies of structural and functional brain networks; and (3) the assortative property of the recurrence network was found by computing the assortative coefficients; their values increased from normal to epileptic brain which accurately suggested the difference of the states. These universal and non-universal characteristics of recurrence networks might help clearly understand the underlying neurodynamics of the brain and provide an efficient tool for clinical diagnosis.
authors.affiliation: Department of Neurology, The Affiliated Jiangyin Hospital of Southeast University of Medical College, Jiangyin, 214400, Jiangsu, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Lang
authors.forename: Dong-Bai
authors.initials: DB
authors.lastname: Liu
authors.forename: Shi-Min
authors.initials: SM
authors.lastname: Cai
authors.forename: Lei
authors.initials: L
authors.lastname: Hong
authors.forename: Pei-Ling
authors.initials: PL
authors.lastname: Zhou
mesh_terms: D001921:Brain / Q000503:physiopathology*; D016000:Cluster Analysis; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology*; D006801:Humans; D025341:Principal Component Analysis