title: Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival.
abstract: Reduced models of neuronal activity such as integrate-and-fire models allow a description of neuronal dynamics in simple, intuitive terms and are easy to simulate numerically. We present a method to fit an integrate-and-fire-type model of neuronal activity, namely a modified version of the spike response model, to a detailed Hodgkin-Huxley-type neuron model driven by stochastic spike arrival. In the Hogkin-Huxley model, spike arrival at the synapse is modeled by a change of synaptic conductance. For such conductance spike input, more than 70% of the postsynaptic action potentials can be predicted with the correct timing by the integrate-and-fire-type model. The modified spike response model is based upon a linearized theory of conductance-driven integrate-and-fire neurons.
authors.affiliation: School of Computer and Communication Sciences and Brain-Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. renaud.jolivet@epfl.ch
authors.forename: Renaud
authors.initials: R
authors.lastname: Jolivet
authors.forename: Wulfram
authors.initials: W
authors.lastname: Gerstner
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology; D006801:Humans; D008433:Mathematics; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology; D013997:Time Factors