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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biological Cyberneti...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biological Cybernetics
Article . 2001 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Article . 2001
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Competitive anatomical and physiological plasticity: a neurotrophic bridge

Authors: Elliott, Terry; Maddison, Adam C; Shadbolt, Nigel R;

Competitive anatomical and physiological plasticity: a neurotrophic bridge

Abstract

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.

Country
United Kingdom
Related Organizations
Keywords

Neurons, Neuronal Plasticity, Neural biology, fixed point analysis, Models, Neurological, Synapses, Computer Simulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Average
Top 10%
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