title: Variability of spike firing during θ-coupled replay of memories in a simulated attractor network.
abstract: Simulation work has recently shown that attractor networks can reproduce Poisson-like variability of single cell spiking, with coefficient of variation (Cv(2)) around unity, consistent with cortical data. However, the use of local variability (Lv) measures has revealed area- and layer-specific deviations from Poisson-like firing. In order to test these findings in silico we used a biophysically detailed attractor network model. We show that Lv well above 1, specifically found in superficial cortical layers and prefrontal areas, can indeed be reproduced in such networks and is consistent with periodic replay rather than persistent firing. The memory replay at the theta time scale provides a framework for a multi-item memory storage in the model. This article is part of a Special Issue entitled Neural Coding.
authors: Royal Institute of Technology, Department of Computational Biology, Roslagstullsbacken 35, 11421 Stockholm, Sweden. lundqvist@nada.kth.se
authors: Mikael
authors: M
authors: Lundqvist
authors: Pawel
authors: P
authors: Herman
authors: Anders
authors: A
authors: Lansner
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology; D000882:Haplorhini; D008568:Memory / Q000502:physiology; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D011897:Random Allocation; D013826:Theta Rhythm / Q000502:physiology*