Literature DB >> 3196774

The adaptation ability of neuronal models subject to a current step stimulus.

F Awiszus1.   

Abstract

Three neuronal models of the spike initiating process were investigated with respect to their ability to show adaptation to a current step: (i) the perfect integrator model (PIM), (ii) the leaky integrator model (LIM), and (iii) the Hodgkin-Huxley (HH)-model. It was found that although each neuronal model will generate different response spike trains to a given stimulus, all responses fulfilled the criteria of a deterministic neural response (Awiszus 1988). The results show that both PIM and LIM are unable to show adaptation regardless of the choice of model parameters whereas the HH-model shows a clear rate of discharge adaptation. The reason for this adaptation lies in the fact that there are conditions for the HH-model where a step stimulus is highly effective. These conditions are investigated by means of a phase plane analysis. Consequences of these results for the explanation of neuronal adaptation and the validity of the neuronal models investigated are discussed.

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Mesh:

Year:  1988        PMID: 3196774     DOI: 10.1007/bf00332919

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


  16 in total

1.  Impulse activity and receptor potential of primary and secondary endings of isolated mammalian muscle spindles.

Authors:  C C Hunt; D Ottoson
Journal:  J Physiol       Date:  1975-10       Impact factor: 5.182

2.  Thresholds and plateaus in the Hodgkin-Huxley nerve equations.

Authors:  R FITZHUGH
Journal:  J Gen Physiol       Date:  1960-05       Impact factor: 4.086

3.  Behavior of solutions of the Hodgkin-Huxley equations and its relation to properties of mechanoreceptors.

Authors:  I Nemoto; S Miyazaki; M Saito; T Utsunomiya
Journal:  Biophys J       Date:  2009-01-01       Impact factor: 4.033

4.  The mechanical properties of dynamic nuclear bag fibres, static nuclear bag fibres and nuclear chain fibres in isolated cat muscle spindles.

Authors:  I A Boyd
Journal:  Prog Brain Res       Date:  1976       Impact factor: 2.453

5.  Neuronal spike trains and stochastic point processes. I. The single spike train.

Authors:  D H Perkel; G L Gerstein; G P Moore
Journal:  Biophys J       Date:  1967-07       Impact factor: 4.033

6.  On numerical integration of the Hodgkin and Huxley equations for a membrane action potential.

Authors:  J W Moore; F Ramon
Journal:  J Theor Biol       Date:  1974-05       Impact factor: 2.691

7.  The encoder mechanism of receptor neurons.

Authors:  B Michaelis; R A Chaplain
Journal:  Kybernetik       Date:  1973-07

8.  The frequency response, coherence, and information capacity of two neuronal models.

Authors:  R B Stein; A S French; A V Holden
Journal:  Biophys J       Date:  1972-03       Impact factor: 4.033

9.  Membrane properties of the stretch receptor neurones of crayfish with particular reference to mechanisms of sensory adaptation.

Authors:  S Nakajima; K Onodera
Journal:  J Physiol       Date:  1969-01       Impact factor: 5.182

10.  The frequency response function and sinusoidal threshold properties of the Hodgkin-Huxley model of action potential encoding.

Authors:  A S French
Journal:  Biol Cybern       Date:  1984       Impact factor: 2.086

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  5 in total

1.  The relationship between a neuronal cross-correlogram and the underlying postsynaptic current.

Authors:  F Awiszus
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

2.  Analytical reconstruction of the neuronal input current from spike train data.

Authors:  F Awiszus
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

3.  The singularly perturbed Hodgkin-Huxley equations as a tool for the analysis of repetitive nerve activity.

Authors:  F Awiszus; J Dehnhardt; T Funke
Journal:  J Math Biol       Date:  1990       Impact factor: 2.259

4.  Continuous functions for the analysis of sensory transduction.

Authors:  F Awiszus
Journal:  Biol Cybern       Date:  1989       Impact factor: 2.086

Review 5.  On the description of neuronal output properties using spike train data.

Authors:  F Awiszus
Journal:  Biol Cybern       Date:  1989       Impact factor: 2.086

  5 in total

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