title: Multiscale evolving complex network model of functional connectivity in neuronal cultures.
abstract: Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust, and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological self-organization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modeling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.
authors: Cybernetics Research Group, School of Systems Engineering, University of Reading, Reading, RG6 6AY, UK. matthew.spencer@reading.ac.uk
authors: Matthew C
authors: MC
authors: Spencer
authors: Julia H
authors: JH
authors: Downes
authors: Dimitris
authors: D
authors: Xydas
authors: Mark W
authors: MW
authors: Hammond
authors: Victor M
authors: VM
authors: Becerra
authors: Kevin
authors: K
authors: Warwick
authors: Benjamin J
authors: BJ
authors: Whalley
authors: Slawomir J
authors: SJ
authors: Nasuto
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002478:Cells, Cultured; D003198:Computer Simulation; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D051381:Rats; D009435:Synaptic Transmission / Q000502:physiology*