title: Noise-driven neocortical interaction: a simple generation mechanism for complex neuron spiking.
abstract: We discuss a generic scenario along which complex spiking behavior evolves in biologically realistic neural networks. Our nonlinear dynamics approach is based directly on rat neocortical in vitro recordings. Using this experimental data, we obtain a full overview on the possible spiking behaviors of pyramidal neurons that are engaged in binary interactions. Universality arguments imply that the observed spiking behaviors are largely independent from the specific properties of individual neurons; theoretical arguments and numerical experiments indicate that they should be observable in in vivo neocortical neuron networks.
authors.affiliation: Institut für Neuroinformatik, ETHZ/UNIZH, Zürich, Switzerland . ruedi@ini.phys.ethz.ch
authors.forename: R
authors.initials: R
authors.lastname: Stoop
authors.forename: K
authors.initials: K
authors.lastname: Schindler
authors.forename: L A
authors.initials: LA
authors.lastname: Bunimovich
mesh_terms: D000818:Animals; D001931:Brain Mapping; D046508:Culture Techniques; D004569:Electroencephalography; D005071:Evoked Potentials / Q000502:physiology; D019579:Neocortex / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D017966:Pyramidal Cells / Q000502:physiology; D051381:Rats; D013003:Somatosensory Cortex / Q000502:physiology; D009435:Synaptic Transmission / Q000502:physiology*