title: Collective bursting in layer IV. Synchronization by small thalamic inputs and recurrent connections.
abstract: Layer IV is believed to be the cortical signal amplifier, for example, of thalamic signals. A previous spiny stellate recurrent network model of this layer is made more realistic by the addition of inhibitory basket neurons. We study the persistence and characteristics of previously observed collective firing behavior, and investigate what additional features would need to be implemented to generate in vivo type neuronal firing. It is shown that neuronal activity is only coarsely synchronized within the network. By applying methods of noise-cleaning, it emerges that the firing of individual neurons is of low-dimensional hyperchaotic nature, as found in the analysis of measured cat in vivo spike trains. In order to reproduce in vivo firing patterns, it is sufficient to have time-varying thalamic input. Conclusions from low-dimensional hyperchaotic behavior of network-embedded neurons are drawn. We interpret observed in vivo pattern-sharpening features of stimuli and outline possible connections to epilepsy. From our results, it follows that emergent global behavior is likely to be the result of the interaction between comparably simple neuronal components, driven by input specificity.
authors.affiliation: Institut für Neuroinformatik der Universität Zürich UNIZH und der Eidgenössischen Technischen Hochschule Zürich ETHZ, Winterthurerstr. 190, CH-8057, Zürich, Switzerland. ruedi@ini.phys.ethz.ch
authors.forename: Ruedi
authors.initials: R
authors.lastname: Stoop
authors.forename: Daniel
authors.initials: D
authors.lastname: Blank
authors.forename: Albert
authors.initials: A
authors.lastname: Kern
authors.forename: Jan Jan
authors.initials: JJ
authors.lastname: v d  Vyver
authors.forename: Markus
authors.initials: M
authors.lastname: Christen
authors.forename: Stefano
authors.initials: S
authors.lastname: Lecchini
authors.forename: Clemens
authors.initials: C
authors.lastname: Wagner
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000344:Afferent Pathways / Q000502:physiology; D000818:Animals; D002415:Cats; D002540:Cerebral Cortex / Q000502:physiology*; D005260:Female; D017709:Fractals; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D013788:Thalamus / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology