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Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity

Overview of attention for article published in Journal of Computational Neuroscience, March 2007
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Title
Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity
Published in
Journal of Computational Neuroscience, March 2007
DOI 10.1007/s10827-007-0022-1
Pubmed ID
Authors

Naoki Masuda, Hiroshi Kori

Abstract

Spike-timing-dependent plasticity (STDP) with asymmetric learning windows is commonly found in the brain and useful for a variety of spike-based computations such as input filtering and associative memory. A natural consequence of STDP is establishment of causality in the sense that a neuron learns to fire with a lag after specific presynaptic neurons have fired. The effect of STDP on synchrony is elusive because spike synchrony implies unitary spike events of different neurons rather than a causal delayed relationship between neurons. We explore how synchrony can be facilitated by STDP in oscillator networks with a pacemaker. We show that STDP with asymmetric learning windows leads to self-organization of feedforward networks starting from the pacemaker. As a result, STDP drastically facilitates frequency synchrony. Even though differences in spike times are lessened as a result of synaptic plasticity, the finite time lag remains so that perfect spike synchrony is not realized. In contrast to traditional mechanisms of large-scale synchrony based on mutual interaction of coupled neurons, the route to synchrony discovered here is enslavement of downstream neurons by upstream ones. Facilitation of such feedforward synchrony does not occur for STDP with symmetric learning windows.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Switzerland 2 1%
United Kingdom 2 1%
Germany 1 <1%
Korea, Republic of 1 <1%
Belarus 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 122 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 29%
Researcher 32 24%
Student > Master 12 9%
Student > Bachelor 10 7%
Professor > Associate Professor 9 7%
Other 21 15%
Unknown 12 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 22%
Physics and Astronomy 24 18%
Neuroscience 16 12%
Psychology 12 9%
Computer Science 10 7%
Other 27 20%
Unknown 17 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 July 2012.
All research outputs
#15,626,815
of 23,848,132 outputs
Outputs from Journal of Computational Neuroscience
#169
of 314 outputs
Outputs of similar age
#68,248
of 78,571 outputs
Outputs of similar age from Journal of Computational Neuroscience
#3
of 3 outputs
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So far Altmetric has tracked 314 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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