Literature DB >> 8324064

A language to describe the growth of neurites.

P Hamilton1.   

Abstract

How can biological plasticity been added to a simulation of neuritic growth? Coming from this question, we have chosen a new access to simulate neuritic growth under the very aspect of meaningful and progredient development of single cells. Based on a specific description-language, we have set up a computer-program, to construct neurite-models and to simulate neuritic interaction during their development. Instead of using mathematical equations, we define various types of cytoskeletons by taking a specified graph grammar. Using this technique, we are able to define strings, combined with other influencing parameters, which allow the setting up of very naturally behaving artificial nervecells, in which distinct statistical variance and fixed rules as given in DNA operate together. In this paper, we want to discuss the underlying principles of the given grammar and to show some results from these computer-simulations, which enable us to study growth, development and other specific characteristics of neurites within a simulator in comparison to in vivo-experiments.

Mesh:

Year:  1993        PMID: 8324064     DOI: 10.1007/bf00200816

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


  13 in total

1.  Developmental algorithms for multicellular organisms: a survey of L-systems.

Authors:  A Lindenmayer
Journal:  J Theor Biol       Date:  1975-10       Impact factor: 2.691

Review 2.  Plasticity in the neocortex: mechanisms underlying recovery from early brain damage.

Authors:  B Kolb; I Q Whishaw
Journal:  Prog Neurobiol       Date:  1989       Impact factor: 11.685

3.  Local control of neurite development by nerve growth factor.

Authors:  R B Campenot
Journal:  Proc Natl Acad Sci U S A       Date:  1977-10       Impact factor: 11.205

4.  Model for membrane movements in the neural growth cone.

Authors:  D Bray
Journal:  Nature       Date:  1973-07-13       Impact factor: 49.962

5.  Fine structure of dendritic and axonal growth cones in embryonic chick spinal cord.

Authors:  R P Skoff; V Hamburger
Journal:  J Comp Neurol       Date:  1974-01-15       Impact factor: 3.215

6.  Mathematical models for cellular interactions in development. II. Simple and branching filaments with two-sided inputs.

Authors:  A Lindenmayer
Journal:  J Theor Biol       Date:  1968-03       Impact factor: 2.691

Review 7.  Sympathetic sprouting in the central nervous system: a model for studies of axonal growth in the mature mammalian brain.

Authors:  K A Crutcher
Journal:  Brain Res       Date:  1987-05       Impact factor: 3.252

8.  Different factors from the central nervous system and periphery regulate the survival of sensory neurones.

Authors:  A M Davies; H Thoenen; Y A Barde
Journal:  Nature       Date:  1986 Feb 6-12       Impact factor: 49.962

Review 9.  Model for the study of plasticity of the human nervous system: features of residual spinal cord motor activity resulting from established post-traumatic injury.

Authors:  M R Dimitrijevic
Journal:  Ciba Found Symp       Date:  1988

10.  Branch input resistance and steady attenuation for input to one branch of a dendritic neuron model.

Authors:  W Rall; J Rinzel
Journal:  Biophys J       Date:  1973-07       Impact factor: 4.033

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  5 in total

1.  Models and simulation of 3D neuronal dendritic trees using Bayesian networks.

Authors:  Pedro L López-Cruz; Concha Bielza; Pedro Larrañaga; Ruth Benavides-Piccione; Javier DeFelipe
Journal:  Neuroinformatics       Date:  2011-12

Review 2.  Mathematical models of neuronal growth.

Authors:  Hadrien Oliveri; Alain Goriely
Journal:  Biomech Model Mechanobiol       Date:  2022-01-07

3.  Peptide vocabulary analysis reveals ultra-conservation and homonymity in protein sequences.

Authors:  Derek Gatherer
Journal:  Bioinform Biol Insights       Date:  2009-11-24

4.  A framework for modeling the growth and development of neurons and networks.

Authors:  Frederic Zubler; Rodney Douglas
Journal:  Front Comput Neurosci       Date:  2009-11-20       Impact factor: 2.380

5.  A computational model of bidirectional axonal growth in micro-tissue engineered neuronal networks (micro-TENNs).

Authors:  Toma Marinov; Haven A López Sánchez; Liang Yuchi; Dayo O Adewole; D Kacy Cullen; Reuben H Kraft
Journal:  In Silico Biol       Date:  2020
  5 in total

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