Literature DB >> 8218533

Stochastic model neuron without resetting of dendritic potential: application to the olfactory system.

J P Rospars1, P Lánský.   

Abstract

A two-dimensional neuronal model, in which the membrane potential of the dendrite evolves independently from that at the trigger zone of the axon, is proposed and studied. In classical one-dimensional neuronal models the dendritic and axonal potentials cannot be distinguished, and thus they are reset to resting level after firing of an action potential, whereas in the present model the dendritic potential is not reset. The trigger zone is modelled by a simplified leaky integrator (RC circuit) and the dendritic compartment can be described by any of the classical one-dimensional neuronal models. The new model simulates observed features of the firing dynamics which are not displayed by classical models, namely positive correlation between interspike intervals and endogenous bursting. It gives a more natural account of features already accounted for in previous models, such as the absence of an upper limit for the coefficient of variation of intervals (i.e. irregular firing). It allows the first- and second-order neurons of the olfactory system to be described with the same basic assumptions, which was not the case in one-point models. Nevertheless it keeps the main qualitative properties found previously, such as the existence of three regimens of firing with increasing stimulus concentration and the sigmoid shape of the firing frequency of first-order neurons as a function of the logarithm of stimulus concentration.

Mesh:

Year:  1993        PMID: 8218533     DOI: 10.1007/bf00203125

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  29 in total

1.  RANDOM WALK MODELS FOR THE SPIKE ACTIVITY OF A SINGLE NEURON.

Authors:  G L GERSTEIN; B MANDELBROT
Journal:  Biophys J       Date:  1964-01       Impact factor: 4.033

2.  Variable initial depolarization in Stein's neuronal model with synaptic reversal potentials.

Authors:  P Lánský; M Musila
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

Review 3.  Dendritic transformations on random synaptic inputs as measured from a neuron's spike train--modeling and simulation.

Authors:  A F Kohn
Journal:  IEEE Trans Biomed Eng       Date:  1989-01       Impact factor: 4.538

4.  The distribution of the intervals between neural impulses in the maintained discharges of retinal ganglion cells.

Authors:  M W Levine
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

5.  An interpretation of 1/f fluctuations in neuronal spike trains during dream sleep.

Authors:  F Grüneis; M Nakao; M Yamamoto; T Musha; H Nakahama
Journal:  Biol Cybern       Date:  1989       Impact factor: 2.086

6.  A point process analysis of the spontaneous activity of anterior semicicular canal units in the anesthetized pigeon.

Authors:  M J Correia; J P Landolt
Journal:  Biol Cybern       Date:  1977-10-14       Impact factor: 2.086

Review 7.  Coding of odor intensity.

Authors:  P Lánský; J P Rospars
Journal:  Biosystems       Date:  1993       Impact factor: 1.973

8.  [The mechanisms of sensory transduction].

Authors:  Y Galifret
Journal:  J Physiol (Paris)       Date:  1978-06

9.  The Ornstein-Uhlenbeck process as a model for neuronal activity. I. Mean and variance of the firing time.

Authors:  L M Ricciardi; L Sacerdote
Journal:  Biol Cybern       Date:  1979-11       Impact factor: 2.086

10.  Dynamics of encoding in a population of neurons.

Authors:  B W Knight
Journal:  J Gen Physiol       Date:  1972-06       Impact factor: 4.086

View more
  4 in total

1.  On the parameter estimation for diffusion models of single neuron's activities. I. Application to spontaneous activities of mesencephalic reticular formation cells in sleep and waking states.

Authors:  J Inoue; S Sato; L M Ricciardi
Journal:  Biol Cybern       Date:  1995-08       Impact factor: 2.086

2.  Coding of odor intensity in a steady-state deterministic model of an olfactory receptor neuron.

Authors:  J P Rospars; P Lánský; H C Tuckwell; A Vermeulen
Journal:  J Comput Neurosci       Date:  1996-03       Impact factor: 1.621

3.  NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

Authors:  Kit Cheung; Simon R Schultz; Wayne Luk
Journal:  Front Neurosci       Date:  2016-01-14       Impact factor: 4.677

4.  Spike-Conducting Integrate-and-Fire Model.

Authors:  Go Ashida; Waldo Nogueira
Journal:  eNeuro       Date:  2018-09-07
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.