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Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the Neocortex

Overview of attention for article published in PLoS Computational Biology, September 2012
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Title
Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the Neocortex
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002689
Pubmed ID
Authors

Moritz Deger, Moritz Helias, Stefan Rotter, Markus Diesmann

Abstract

Structural plasticity governs the long-term development of synaptic connections in the neocortex. While the underlying processes at the synapses are not fully understood, there is strong evidence that a process of random, independent formation and pruning of excitatory synapses can be ruled out. Instead, there must be some cooperation between the synaptic contacts connecting a single pre- and postsynaptic neuron pair. So far, the mechanism of cooperation is not known. Here we demonstrate that local correlation detection at the postsynaptic dendritic spine suffices to explain the synaptic cooperation effect, without assuming any hypothetical direct interaction pathway between the synaptic contacts. Candidate biomolecular mechanisms for dendritic correlation detection have been identified previously, as well as for structural plasticity based thereon. By analyzing and fitting of a simple model, we show that spike-timing correlation dependent structural plasticity, without additional mechanisms of cross-synapse interaction, can reproduce the experimentally observed distributions of numbers of synaptic contacts between pairs of neurons in the neocortex. Furthermore, the model yields a first explanation for the existence of both transient and persistent dendritic spines and allows to make predictions for future experiments.

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Geographical breakdown

Country Count As %
Germany 5 5%
United Kingdom 4 4%
Switzerland 2 2%
France 1 <1%
Belgium 1 <1%
Spain 1 <1%
Greece 1 <1%
United States 1 <1%
Unknown 85 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 28%
Student > Ph. D. Student 25 25%
Student > Master 11 11%
Professor 10 10%
Student > Doctoral Student 6 6%
Other 13 13%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 26%
Neuroscience 24 24%
Computer Science 12 12%
Physics and Astronomy 8 8%
Mathematics 7 7%
Other 14 14%
Unknown 10 10%