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Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex

Overview of attention for article published in PLoS Computational Biology, January 2013
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Title
Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex
Published in
PLoS Computational Biology, January 2013
DOI 10.1371/journal.pcbi.1002848
Pubmed ID
Authors

Pengsheng Zheng, Christos Dimitrakakis, Jochen Triesch

Abstract

The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of neuronal plasticity plays an essential role in the formation and maintenance of cortical circuits.

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Geographical breakdown

Country Count As %
Germany 9 4%
United States 9 4%
Switzerland 4 2%
France 4 2%
United Kingdom 4 2%
Australia 2 <1%
Japan 1 <1%
Belarus 1 <1%
Unknown 210 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 70 29%
Researcher 51 21%
Student > Master 28 11%
Professor 17 7%
Student > Bachelor 12 5%
Other 41 17%
Unknown 25 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 23%
Computer Science 47 19%
Neuroscience 40 16%
Physics and Astronomy 23 9%
Engineering 19 8%
Other 31 13%
Unknown 27 11%