Literature DB >> 7578480

On the comparison of Feller and Ornstein-Uhlenbeck models for neural activity.

P Lánský1, L Sacerdote, F Tomassetti.   

Abstract

Diffusion processes have been extensively used to describe membrane potential behavior. In this approach the interspike interval has a theoretical counterpart in the first-passage-time of the diffusion model employed. Since the mathematical complexity of the first-passage-time problem increases with attempts to make the models more realistic it seems useful to compare the features of different models in order to highlight their relative performance. In this paper we compare the Feller and Ornstein-Uhlenbeck models under three different criteria derived from the level of information available about their parameters. We conclude that the Feller model is preferable when complete knowledge of the characterizing parameters is assumed. On the other hand, when only limited information about the parameters is available, such as the mean firing time and the histogram shape, no advantage arises from using this more complex model.

Mesh:

Year:  1995        PMID: 7578480     DOI: 10.1007/BF00201480

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


  15 in total

1.  A THEORETICAL ANALYSIS OF NEURONAL VARIABILITY.

Authors:  R B STEIN
Journal:  Biophys J       Date:  1965-03       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

3.  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

4.  Diffusion approximation of the neuronal model with synaptic reversal potentials.

Authors:  P Lánský; V Lánská
Journal:  Biol Cybern       Date:  1987       Impact factor: 2.086

5.  On the interspike intervals calculated from diffusion approximations of Stein's neuronal model with reversal potentials.

Authors:  M Musila; P Lánský
Journal:  J Theor Biol       Date:  1994-11-21       Impact factor: 2.691

6.  A theoretical basis for large coefficient of variation and bimodality in neuronal interspike interval distributions.

Authors:  W J Wilbur; J Rinzel
Journal:  J Theor Biol       Date:  1983-11-21       Impact factor: 2.691

7.  On approximations of Stein's neuronal model.

Authors:  P Lánský
Journal:  J Theor Biol       Date:  1984-04-21       Impact factor: 2.691

8.  Neuronal interspike time distributions and the estimation of neurophysiological and neuroanatomical parameters.

Authors:  H C Tuckwell; W Richter
Journal:  J Theor Biol       Date:  1978-03-20       Impact factor: 2.691

9.  Accuracy of neuronal interspike times calculated from a diffusion approximation.

Authors:  H C Tuckwell; D K Cope
Journal:  J Theor Biol       Date:  1980-04-07       Impact factor: 2.691

10.  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

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  5 in total

1.  Parameter estimation for a leaky integrate-and-fire neuronal model from ISI data.

Authors:  Paul Mullowney; Satish Iyengar
Journal:  J Comput Neurosci       Date:  2007-07-28       Impact factor: 1.621

2.  Some Dissimilarity Measures of Branching Processes and Optimal Decision Making in the Presence of Potential Pandemics.

Authors:  Niels B Kammerer; Wolfgang Stummer
Journal:  Entropy (Basel)       Date:  2020-08-08       Impact factor: 2.524

3.  Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process.

Authors:  Patrick Jahn; Rune W Berg; Jørn Hounsgaard; Susanne Ditlevsen
Journal:  J Comput Neurosci       Date:  2011-04-09       Impact factor: 1.621

4.  A stochastic model and a functional central limit theorem for information processing in large systems of neurons.

Authors:  Reinhard Höpfner; Klaus Brodda
Journal:  J Math Biol       Date:  2005-12-28       Impact factor: 2.164

Review 5.  The dynamic brain: from spiking neurons to neural masses and cortical fields.

Authors:  Gustavo Deco; Viktor K Jirsa; Peter A Robinson; Michael Breakspear; Karl Friston
Journal:  PLoS Comput Biol       Date:  2008-08-29       Impact factor: 4.475

  5 in total

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