Literature DB >> 1912005

A computer based model for realistic simulations of neural networks. I. The single neuron and synaptic interaction.

O Ekeberg1, P Wallén, A Lansner, H Tråvén, L Brodin, S Grillner.   

Abstract

The use of computer simulations as a neurophysiological tool creates new possibilities to understand complex systems and to test whether a given model can explain experimental findings. Simulations, however, require a detailed specification of the model, including the nerve cell action potential and synaptic transmission. We describe a neuron model of intermediate complexity, with a small number of compartments representing the soma and the dendritic tree, and equipped with Na+, K+, Ca2+, and Ca2+ dependent K+ channels. Conductance changes in the different compartments are used to model conventional excitatory and inhibitory synaptic interactions. Voltage dependent NMDA-receptor channels are also included, and influence both the electrical conductance and the inflow of Ca2+ ions. This neuron model has been designed for the analysis of neural networks and specifically for the simulation of the network generating locomotion in a simple vertebrate, the lamprey. By assigning experimentally established properties to the simulated cells and their synapses, it has been possible to verify the sufficiency of these properties to account for a number of experimental findings of the network in operation. The model is, however, sufficiently general to be useful for realistic simulation also of other neural systems.

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Year:  1991        PMID: 1912005     DOI: 10.1007/bf00202382

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


  30 in total

Review 1.  Neuronal network generating locomotor behavior in lamprey: circuitry, transmitters, membrane properties, and simulation.

Authors:  S Grillner; P Wallén; L Brodin; A Lansner
Journal:  Annu Rev Neurosci       Date:  1991       Impact factor: 12.449

2.  Computer simulations of N-methyl-D-aspartate receptor-induced membrane properties in a neuron model.

Authors:  L Brodin; H G Tråvén; A Lansner; P Wallén; O Ekeberg; S Grillner
Journal:  J Neurophysiol       Date:  1991-08       Impact factor: 2.714

3.  A computer program for simulating a network of interacting neurons. I. Organization and physiological assumptions.

Authors:  D H Perkel
Journal:  Comput Biomed Res       Date:  1976-02

4.  Activation of N-methyl-D-aspartate (NMDA) receptors augments repolarizing responses in lamprey spinal neurons.

Authors:  R H Hill; L Brodin; S Grillner
Journal:  Brain Res       Date:  1989-10-16       Impact factor: 3.252

5.  Agonist- and voltage-gated calcium entry in cultured mouse spinal cord neurons under voltage clamp measured using arsenazo III.

Authors:  M L Mayer; A B MacDermott; G L Westbrook; S J Smith; J L Barker
Journal:  J Neurosci       Date:  1987-10       Impact factor: 6.167

6.  Motoneurone models based on 'voltage clamp equations' for peripheral nerve.

Authors:  D Kernell; H Sjöholm
Journal:  Acta Physiol Scand       Date:  1972-12

7.  A model for repetitive firing in neurons.

Authors:  R J MacGregor; R M Oliver
Journal:  Kybernetik       Date:  1974

Review 8.  Excitatory amino acid transmitters.

Authors:  J C Watkins; R H Evans
Journal:  Annu Rev Pharmacol Toxicol       Date:  1981       Impact factor: 13.820

9.  Autorhythmicity and entrainment in excitable membranes.

Authors:  A V Holden
Journal:  Biol Cybern       Date:  1980       Impact factor: 2.086

10.  Ionic mechanisms of 3 types of functionally different neurons in the lamprey spinal cord.

Authors:  R H Hill; P Arhem; S Grillner
Journal:  Brain Res       Date:  1985-12-09       Impact factor: 3.252

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  36 in total

1.  Simulations of neuromuscular control in lamprey swimming.

Authors:  O Ekeberg; S Grillner
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1999-05-29       Impact factor: 6.237

2.  Presynaptic inhibition and antidromic spikes in primary afferents of the crayfish: a computational and experimental analysis.

Authors:  D Cattaert; F Libersat; A El Manira A
Journal:  J Neurosci       Date:  2001-02-01       Impact factor: 6.167

3.  Interaction between metabotropic and ionotropic glutamate receptors regulates neuronal network activity.

Authors:  P Krieger; J Hellgren-Kotaleski; P Kettunen; A J El Manira
Journal:  J Neurosci       Date:  2000-07-15       Impact factor: 6.167

4.  Modelling inter-segmental coordination of neuronal oscillators: synaptic mechanisms for uni-directional coupling during swimming in Xenopus tadpoles.

Authors:  Mark J Tunstall; Alan Roberts; S R Soffe
Journal:  J Comput Neurosci       Date:  2002 Sep-Oct       Impact factor: 1.621

5.  Computer simulation of the segmental neural network generating locomotion in lamprey by using populations of network interneurons.

Authors:  J Hellgren; S Grillner; A Lansner
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

6.  Universality in neural networks: the importance of the 'mean firing rate'.

Authors:  W Gerstner; J L van Hemmen
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

7.  Simulation and robotics studies of salamander locomotion: applying neurobiological principles to the control of locomotion in robots.

Authors:  Auke Jan Ijspeert; Alessandro Crespi; Jean-Marie Cabelguen
Journal:  Neuroinformatics       Date:  2005

8.  Systems-level modeling of neuronal circuits for leech swimming.

Authors:  M Zheng; W O Friesen; T Iwasaki
Journal:  J Comput Neurosci       Date:  2006-09-19       Impact factor: 1.621

9.  Frequency control of motor patterning by negative sensory feedback.

Authors:  Jessica Ausborn; Wolfgang Stein; Harald Wolf
Journal:  J Neurosci       Date:  2007-08-29       Impact factor: 6.167

10.  Silicon neuron simulation with SPICE: tool for neurobiology and neural networks.

Authors:  M Grattarola; M Bove; S Martinoia; G Massobrio
Journal:  Med Biol Eng Comput       Date:  1995-07       Impact factor: 2.602

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