Document Detail


Competitive anatomical and physiological plasticity: a neurotrophic bridge.
MedLine Citation:
PMID:  11204395     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Understanding the mechanisms of competitive synaptic plasticity, both anatomical and physiological, is of central importance to developmental neuroscience. Neurotrophic factors (NTFs) are implicated at almost every level of synaptic plasticity, from rapid physiological effects to slower anatomical effects, in addition to being implicated in competitive plasticity. Previously, we have built and analysed a mathematical model of anatomical synaptic plasticity based on competition for neurotrophic support. Here, we extend our work to build a combined, anatomical and physiological model. We find that, in order to understand the mechanisms of competitive physiological plasticity, we must postulate a central role for the change in expression of NTF receptors (NTFRs) on afferent synaptic terminals. Only by supposing that the expression of NTFRs is governed by NTF uptake do we find that physiological plasticity is competitive in character. We perform a fixed point analysis that establishes when afferent segregation is possible as a function of the parameters in the model, and simulate the model numerically to shed further light on its properties. A very clear prediction emerges from our model: that, as the efficacy of a terminal that is destined to be retracted due to competitive interactions reduces to zero, the NTFRs on that terminal should be down-regulated. Furthermore, our model requires that this reduction in synaptic efficacy never occurs significantly before the down-regulation in NTFRs. Such a prediction should be testable, and renders our model capable of being invalidated, in contrast to many other models of synaptic competition, which merely impose rather than seek to illuminate the quintessential feature of developmental synaptic plasticity.
Authors:
T Elliott; A C Maddison; N R Shadbolt
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biological cybernetics     Volume:  84     ISSN:  0340-1200     ISO Abbreviation:  Biol Cybern     Publication Date:  2001 Jan 
Date Detail:
Created Date:  2001-02-02     Completed Date:  2001-03-29     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  7502533     Medline TA:  Biol Cybern     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  13-22     Citation Subset:  IM    
Affiliation:
Department of Psychology, University of Nottingham, UK. te@ecs.soton.ac.uk
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MeSH Terms
Descriptor/Qualifier:
Computer Simulation
Models, Neurological*
Neuronal Plasticity / physiology*
Neurons / physiology*
Synapses / physiology*

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