title: Lag synchrony measures dynamical processes underlying progression of seizure states.
abstract: We investigate the dynamics of bursting behavior in an intact hippocampal preparation using causal entropy, an adaptive measure of lag synchrony. This analysis, together with a heuristic model of coupled bursting networks, separates experimentally observed bursting dynamics into two dynamical regimes, when bursting is driven by (1) the intranetwork dynamics of a single region, or (2) internetwork feedback between spatially disjoint neural populations. Our results suggest that the abrupt transition between these two states heralds the gradual desynchronization of bursting activity. These results illustrate how superficially homogeneous behavior across loosely coupled networks may harbor hidden, but robust, dynamical processes.
authors.affiliation: Neuroscience Program, Department of Physics and Biophysics Research Division, University of Michigan, Ann Arbor, Michigan 48109, USA.
authors.forename: Benjamin H
authors.initials: BH
authors.lastname: Singer
authors.forename: Miron
authors.initials: M
authors.lastname: Derchansky
authors.forename: Peter L
authors.initials: PL
authors.lastname: Carlen
authors.forename: Michał
authors.initials: M
authors.lastname: Zochowski
mesh_terms: D000200:Action Potentials; D000818:Animals; D001683:Biological Clocks; D002478:Cells, Cultured; D003198:Computer Simulation; D006624:Hippocampus / Q000503:physiopathology*; D051379:Mice; D008810:Mice, Inbred C57BL; D008959:Models, Neurological; D009415:Nerve Net / Q000503:physiopathology*; D009474:Neurons; D012640:Seizures / Q000503:physiopathology*; D009435:Synaptic Transmission; D013997:Time Factors